AUTOMATIC DETECTION OF ABNORMAL DRILL DATA ABNORMAL TREND FOR PREVENT RISK

专利摘要:
An abnormal tendency detection system for detecting one or more hazards can provide a safe and efficient drilling operation, as any of the hazard (s) can be avoided. Several indicators can be defined, including first, second, third and fourth indicators. Indicators are used to identify abnormal trends in a trend analysis. One or more thresholds can be defined. When a trend analysis indicates that a threshold has been reached or exceeded, an alarm may be triggered, a drill operation may be changed or a combination thereof.
公开号:FR3073555A1
申请号:FR1858056
申请日:2018-09-07
公开日:2019-05-17
发明作者:Hewei Tang；Shang Zhang；Feifei Zhang；Suresh Venugopal；Youli Mao
申请人:Landmark Graphics Corp；
IPC主号:

专利说明:

AUTOMATIC DETECTION OF ABNORMAL TREND OF DRILLING DATA IN REAL TIME FOR RISK PREVENTON
TECHNICAL AREA
The present invention relates to the detection and analysis of abnormal trends, and more particularly to the detection and analysis of abnormal trends for the analysis of drilling data in real time, for example in exploration and recovery applications. hydrocarbons.
CONTEXT
Detecting and preventing abnormal behaviors, conditions or risks during a hydrocarbon operation provides a safe and efficient environment for recovering hydrocarbons. The present description relates in general to an abnormal trend detection and analysis for real-time drilling data, for example drilling data associated with a hydrocarbon, such as an application for exploration, production or recovery of oil and gas. Risk prevention is necessary during a specific drilling operation to ensure a safe and efficient drilling operation. Current drilling risk prevention systems are generally physical models. These physical-based models have many application-level limitations, such as: (a) physical models usually require high quality input data, (b) physical models are based on specific assumptions with a field of limited application, and (c) systems based on physical models usually require significant computational costs. Optimizing abnormal trend detection is necessary to provide effective and efficient trend analysis, for example to prevent risks in oil exploration, recovery and drilling operations.
Current data-driven models also have several drawbacks. For example, hydrocarbon operations can include one or more sensors placed on or around equipment or on a site. The data from these sensors can contain a lot of noise, so the data is not easily analyzed or does not provide useful information to detect or prevent a risk during an oil and gas operation. For example, the data may contain noise such that a trend cannot be determined, since the analysis of the data does not provide a trend indicating abnormal behavior, but rather represents a trend indicating noise. In addition, current methods of detecting a behavior, a condition or a
2017-IPM-101598-U1-FR abnormal risk are based on a difference between a peak value and a predicted value. This predicted value may be unreliable and thus provide inaccurate information.
Thus, the reliable detection of an abnormal behavior, condition or risk for a hydrocarbon operation is necessary. The present invention provides such reliable detection by applying specific models to time series data to obtain a probability value which produces reliable information for abnormal trend analysis.
BRIEF DESCRIPTION OF THE DRAWINGS
FIG. 1 is a graph illustrating two real-time blow indicators calculated from real-time drilling data, according to one or more aspects of the present description.
FIG. 2 is a graph illustrating a method for detecting an abnormal upward trend in real time, according to one or more aspects of the present description.
FIG. 3 is a graph illustrating a method for detecting the tendency to accelerate a deceleration in real time, according to one or more aspects of the present description.
FIG. 4 is a diagram illustrating an example of an abnormal trend detection system, according to one or more aspects of the present description.
FIG. 5 is a diagram illustrating an example of an information processing system, according to one or more aspects of the present description.
FIG. 6 illustrates an example of an abnormal trend analysis system according to one or more aspects of the present invention.
Figure 7 is a flow chart for abnormal trend analysis of data according to one or more aspects of the present invention.
Figure 8 is a flow chart for detecting an abnormal trend in a drilling operation using real time data according to one or more aspects of the present invention.
FIG. 9 illustrates an example of an abnormal trend analysis system according to one or more aspects of the present invention.
FIG. 10 illustrates an example of an abnormal trend analysis system according to one or more aspects of the present invention.
Figure 11 illustrates a schematic diagram of an example of an abnormal trend detection environment according to one or more aspects of the present invention.
2017-IPM-101598-U1-EN
Although embodiments of this description have been illustrated and described and are defined with reference to examples of embodiments of the description, such references do not imply a limitation on the description, and no such limitation does must be deducted. The object described is susceptible to modifications, alterations and considerable equivalents in terms of form and function, as will be apparent to those skilled in the art and having the advantage of this description. The embodiments discussed and described in this description are only examples and do not fully cover the scope of the description.
In one or more implementations, all of the components shown in each figure may not be required, and one or more implementations may include additional components not shown in a figure. Variations in the arrangement and type of components can be made without departing from the scope of the description in question. Additional components, different components or fewer components may be used in the context of the description in question.
DETAILED DESCRIPTION
Illustrative embodiments of the present description are described in detail here. For the sake of clarity, all the characteristics of an actual implementation are not described in this description. Note, of course, that in the development of any real embodiment, many specific implementation decisions must be made to achieve specific implementation objectives, such as compliance with system constraints and activities, which may vary from one implementation to another. Furthermore, it will be understood that such a development effort could be complex and tedious, but would nevertheless constitute a routine undertaking for those skilled in the art having the advantage of the present description. In addition, the following examples should in no case be read to limit or define the scope of the description.
For any one or more exploration, service, production operations or any combination thereof in a reservoir or an identified site, drilling data can be obtained. This data can be obtained by a real-time information processing system and stored in a database internal or external to the information processing system. For a given operation or site, a drilling risk prevention system or an abnormal trend detection system may be necessary to ensure a safe and efficient drilling operation, for example for a drilling operation, exploitation, service, production or recovery of hydrocarbons associated with a well,
2017-IPM-101598-U1-FR a tank or a site. Current physical-based models for abnormal trend detection are generally or mainly physical-based and have several application-level limitations. For example, current physical-based models for drilling risk prevention require high quality data entry, all physical models based on specific assumptions with limited scope and significant computational costs.
Wells, also known as boreholes, are drilled to reach underground oil and other underground hydrocarbons. Information or data associated with a hydrocarbon operation is obtained, for example, during or after the drilling operation or both. This information or data may relate to parameters, conditions or both associated with the surface, downhole or both. In one or more embodiments, modular hardware and software units can be communicatively coupled to one or more sensors, controls, or both that are directly or indirectly coupled to equipment above or below the surface on a site such as a hydrocarbon operation site. One or more parameters associated with a hydrocarbon operation, such as a drilling operation, can be recorded in real time at any time interval (for example, a predefined or predetermined time period, a time period random or any other time interval) or at any depth interval. This information may include, for example, data associated with any operation on a site, including, but not limited to, information associated with a drill tower or other equipment on a site, characteristics of a or more earth formations crossed by the wellbore, the size or configuration of the wellbore, one or more environmental factors (such as one or more of temperature, humidity, release of gas, vapor, fluids or other materials and all other factors). The collection of information relating to the conditions at the surface and downhole, commonly known as “data logging”, can be carried out by several methods described below.
The data or information collected on a site can be used in one or more embodiments, to detect, prevent or both, one or more abnormal behaviors, conditions or risks (collectively called abnormal conditions). In any one or more embodiments, one or more abnormal conditions may include any one or more of a blow of formation, blockage of a drill pipe, loss of circulation of drilling fluid, swelling of the wellbore, a wellbore failure, jerk, warp of drill string, or other abnormal condition. For example, a formation blow ("blow") is the undesirable flow of formation fluid into a wellbore when the hydrostatic pressure of the
2017-IPM-101598-U1-FR wellbore is less than the pore pressure of the formation. Detection, control or both of a formation shot is necessary to avoid harming the surrounding environment or personnel, for example due to a rash. A blow can be observed by a drilling operator or by an engineer using one or more blow indicators. However, such hit indicators can be difficult to apply and may require significant field experience from staff to determine if a hit has occurred. In one or more embodiments, robust and reliable abnormal trend detection in real-time data is provided. First, the real-time trend is defined. Second, one or more smoothing techniques, probability analysis, or both are applied to account for local anomalous trends resulting from fluctuations and outliers in the actual data.
In one or more embodiments, an abnormal trend detection system for detecting one or more risks can enable a safe and effective drilling operation, since any one or more risks can be avoided. Several indicators can be defined, including a first, a second, a third and a fourth indicator. Indicators are used to identify abnormal trends in a trend analysis. One or more thresholds can be defined. When a trend analysis indicates that a threshold has been reached or exceeded, an alarm can be triggered.
The present description provides one or more embodiments for a drilling risk prevention system or an abnormal trend detection system which makes it possible to detect an abnormal data trend automatically in real time. Any one or more embodiments present a general abnormal trend detection algorithm for real-time drilling data analysis, which can be incorporated into a drilling management system, a real-time data monitoring system, any other risk prevention system or any combination thereof. In one or more embodiments, the drilling risk prevention system takes into account one or more uncertainties in the real time data such as fluctuations and distant values, so that the real time data coming, for example , from a drill tower, can be directly processed. As the drilling risk prevention system according to one or more aspects of this description is based on data, no limit is imposed on the physical scope and the system also provides a simple and rapid approach to preventing risks drilling. Thus, the drilling risk prevention system can be used effectively and efficiently in any real-time alert system for risk prevention and drilling management.
2017-IPM-101598-U1-EN
Techniques for measuring operating conditions or parameters at the surface and downhole, and the movement and position of a drilling rig at the same time as drilling the well, can be called "measurement while drilling" techniques. Or "MWD" as mentioned here. Measuring formation properties by a given MWD system (for example, as shown in Figure 6), while drilling a wellbore in an underground formation, can improve the speed of receiving measurement data and, therefore, be used by implementations described herein to detect an abnormal condition, such as a formation blow, during the drilling operation. Similar techniques, more focused on measuring the formation parameters of the type associated with wired tools, have been called "well drilling" or "LWD" techniques. Although distinctions between MWD and LWD may exist, the terms and LCF are often used interchangeably. For the purpose of explanation in this description, the term log drilling data will be used, it being understood that the term MCF includes surface measurements, MWD and LWD techniques.
In order to facilitate a better understanding of the present invention, the following examples of certain embodiments are given. In any case, the following examples should be interpreted as limiting, or defining, the scope of the invention. One or more embodiments of this description may be applicable to any type of drilling operation, including, but not limited to, an exploration, service or production operation for any type of well site or reservoir environment, including underground and underwater environments.
According to one or more aspects of the present description, an information processing system or computer equipment may be necessary. For the purposes of this description, an information processing system can include any instrument or aggregate of instruments that can be used to calculate, classify, process, transmit, receive, retrieve, create, switch, store, record, display, manifest, detect , record, reproduce, manipulate, or use any form of information, intelligence or data for commercial, scientific, control or other purposes. For example, an information processing system can be a personal computer, a network storage device or any other suitable device and can vary in size, shape, performance, functionality and price. The information processing system may include a random access memory (RAM), one or more processing resources such as a central processing unit (CPU) or a hardware or software control logic, a read only memory (MOR) or any other type of non-volatile memory. Additional components of the information processing system may include one or more disk drives, one or more network ports for
2017-IPM-101598-U1-FR communication with external devices as well as various input and output (FO) devices, such as a keyboard, mouse and video screen. The information processing system can also include one or more buses capable of transmitting communications between the various hardware components. The information processing system can also include one or more interface units capable of transmitting one or more signals to a controller, an actuator or a similar device.
For the purposes of this description, a computer-readable medium of an information processing system may include any instrument or aggregate of instruments which can retain data and / or instructions for a period of time. Computer readable media may include, for example, without limitation, storage media such as a direct access storage device (for example, a hard disk drive or a floppy drive), an access storage device sequential (for example, a tape drive), a compact disc (CD), a CD ROM (CD-ROM), a digital video disc (DVD), the "CLOUD", a random access memory (RAM), a read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory, biological memory, deoxyribonucleic acid (DNA) or molecular memory or any combination thereof, as well as communication media such as wires, optical fibers, microwaves, radio waves and other electromagnetic and / or optical media, and / or any combination thereof.
According to one or more embodiments of the present description, two problems of abnormal trend detection in the real-time data are solved. The first is to define the trend in real time. The second is to apply smoothing techniques and probability analysis to account for local abnormal trends resulting from fluctuations and outliers (or outliers) in the actual data. In one or more embodiments, any one or more defined trend indicators, for example, the four trend indicators defined below, may be used or applied in an automatic abnormal trend detection system in real time. Actual or real-time drilling data, for example drilling data from an offshore drilling tower, can be used with one or more algorithms applied in a real-time alarm system for blow detection according to a or more embodiments.
Figure 1 illustrates a real-time recording of two major indicators (blow indicators or trend indicators) for a gas hit during rotary drilling operations. An indicator, for example, a first hit indicator, is called FPG (group of flow parameters), which integrates parameters linked to a flow such as or y
2017-IPM-101598-U1-FR inclusive of, but not limited to, inbound flow, upward pipe pressure (SPP) and outbound flow. The other indicator, for example, a second hit indicator, is called DPG (drilling parameter group), which incorporates one or more parameters related to drilling, including, but not limited to, the penetration rate ( ROP), speed of rotation (RPM) and weight on wick (WOB). In the event of a hit, the GIF will exhibit an abnormal upward trend (as indicated by the solid line in the FPG), and the DPG will exhibit an accelerating trend in deceleration (as indicated by the solid line in the DPG). The dotted lines for the FPG and DPG graphics indicate the most suitable models. The x-axis represents time in Day: Hour: Minutes format. The y axis for the FPG represents gallons per minute (GPM) and the y axis for the DPG is dimensionless.
Figure 2 illustrates that, for abnormal uptrend detection, the DMA is calculated in real time based on the FPG data. Upward crossing of MA values creates a positive DMA value, indicating that the GIF has been increasing recently or indicating a recent upward trend in the GIF traced for a specified time interval or period. Two window sizes are used, for example a window size of one minute (illustrated by the line MA 1 min) and a window size of three minutes (illustrated by the line MA 3 min). The dotted arrows on the FPG graph in Figure 2 indicate an upward trend. The dotted line on the FPG chart indicates an upward trend. The solid line on the FPG graph indicates normalization or smoothing of the data. The x-axis represents time in Day: Hour: Minutes format. The y axis for the FPG represents gallons per minute (GPM) and the y axis for the DPG is dimensionless. In one or more embodiments, a threshold can be applied to define, trigger or otherwise indicate the alarm for hit detection. In one or more embodiments, a threshold may be defined, predetermined or predefined for any one or more trend indicators based, at least in part, on historical data or information, user-defined inputs, one or more several criteria associated with a drilling site or operation, any other factor or criterion, or any combination thereof.
FIG. 3 is a graph illustrating the method for detecting an acceleration tendency of the deceleration in real time. Such trend detection can be automatic or manual. The MK value of the DPG is first calculated with a window size, for example of five minutes (illustrated by the line MK 5 min), in real time. Then the real-time MAK values are calculated from MK for a window size, for example, of about one minute (illustrated by the line MAK 1 min) and three minutes (illustrated by the line MAK 3 min) , respectively. In one or more embodiments, a window size can be based on the criteria or factors for a given drilling operation and can be any
2017-IPM-101598-U1-FR time range. The DMAK value is finally calculated. A downward crossover of the MKA value creates a negative DMAK value, indicating that the data has recently increased at a slower speed than in the past or at a speed slower than a historic speed. This downward trend may indicate an abnormal condition. The solid arrows in Figure 3 indicate the trend of the DPG over the illustrated time series. The dotted arrows on the DPG graph indicate local downward and upward trends. The two dotted arrows from the DMAK graph to the DPG plot indicate when the DMAK value becomes negative, that is, a local downward and upward trend in DPG is detected. A threshold can be applied to define the alarm for blow detection. A threshold can be defined, predetermined or predefined based, at least in part, on historical data or information, user-defined inputs, one or more criteria associated with a site or an operation of drilling, any other factor or criteria or any combination thereof.
In one or more embodiments, an alarm can be triggered based, at least in part, on a trend analysis as illustrated in any one or more of Figures 1 to 3. The triggering of a alarm may include representing an alarm condition, for example, representing an alarm condition as illustrated in Figures 1 to 3 on a display of an information processing system, the communication that an alarm condition has occurred to one or more information processing systems including, but not limited to, a server, computer, laptop, tablet, cellular device, or other electronic device issuing an alarm, any other method of notifying an alarm, or any combination thereof.
FIG. 4 is a diagram illustrating an example of an abnormal trend detection system 400, according to one or more aspects of the present description. The abnormal trend detection system 400 may include one or more information processing systems 402. An information processing system 402 may be coupled to a display 410, a source 406 and a database 408. The display 410 can display information, for example any abnormal trend analysis, to a user. The information processing system 402 can be located near or away from the source 406. The source 406 can be any drilling rig including, but not limited to, a drilling tower such as a drilling tower associated with a hydrocarbon operation such as exploration, recovery or production. Source 406 can be located on an underground or offshore / underwater drilling site. The information processing system 402 can receive drilling data 412 from the source 406. The source 406 can transmit drilling data 412 to the information processing system 402 directly, indirectly, wired or wireless or any
2017-IPM-101598-U1-FR combination of these. In one or more embodiments, the source 406 can transmit drilling data 412 in real time to the information processing system 402. In one or more embodiments, the information processing system 402 can request data drilling 412 from source 406, automatically receiving drilling data 412 from source 406 or any combination thereof. The database 408 can be located locally or remotely from the information processing system 402. In one or more embodiments, the information processing system 402 comprises a database 408. In one or more modes of embodiment, another information processing system 402 comprises a database 408. The database 408 can store any information or any data received by the information processing system 402, for example drilling data 412, storing any information or historical data associated with the source 406 or any other source of information or data, store any current or historical trend analysis performed or determined by the information processing system 402, store any associated historical trend analysis to any drilling site from any source, IT device, storage device, other information collector ns or any combination thereof.
In one or more embodiments, any one or more information processing systems 402 may include a module 404. The module 404 may include hardware, software or any combination thereof to achieve any one or more aspects of this description including, but not limited to, defining any one or more trend indicators, processing 412 drilling data received from source 404, storing 412 drilling data received from source 406, sending, receiving or both, drill data 412 to / from database 408, perform one or more calculations, for example, equations 1 to 5, apply any one or more of the defined trend indicators to determine automatic detection in time abnormal trend real as discussed for Figures 1 to 3, define a threshold, determine if a threshold has been reached, exceeded, not reached, or any combination of these, provide information to a display 410 associated with a trend analysis, for example any one or more illustrations as shown in Figures 1-3, apply one or more smoothing techniques, perform a probability analysis and provide an interface for communicating on various networks, such as Wi-Fi, Bluetooth, RF, wired or wireless communication systems. In one or more embodiments, the information processing system 402 is not coupled to the source 406 and instead detects or determines one or more abnormal trends based, at least in part, on offline data. In one or more embodiments, the information processing system 402 can detect or determine one or more
2017-IPM-101598-U1-FR several anomalous trends based, at least in part, on online data or real-time data, offline data or both.
FIG. 5 is a diagram illustrating an example of an information processing system 500, according to one or more aspects of the present description. The information processing system 402 of Figure 4 can take a form similar to the information processing system 500 or include one or more components of the information processing system 500. Any information processing system and any component discussed which includes a processor may take a form similar to information processing system 500 or include one or more components of information processing system 500. A processor or central processing unit (CPU) 501 of the data processing system information 500 is communicatively coupled to a memory controller hub (MCH) or to a north bridge 502. The processor 501 may include, for example, a microprocessor, a microcontroller, a digital signal processor (DSP), a Application Specific Integrated Circuit (ASIC) or any other digital or analog circuit configured to interpret, execute program instructions, do operating years or any combination thereof. The processor (CPU) 501 can be configured to interpret and execute program instructions or other data retrieved and stored in any memory such as memory 503 or hard drive 507. Program instructions or others data may constitute parts of software or an application allowing the execution of one or more processes described here. The memory 503 can include a read only memory (ROM), a random access memory (RAM), a semiconductor memory or a memory on disc. Each memory module can include any system, device, or apparatus configured to store program instructions, program data, or both for a period of time (for example, computer-readable, non-transient computer media). For example, instructions coming from a software or an application can be extracted and stored in the memory 503, for example a non-transient memory, to be executed by the processor 501.
Modifications, additions or omissions can be made to Figure 5 without departing from the scope of this description. For example, Figure 5 shows a particular configuration of components of the information processing system 500. However, any suitable configuration of components can be used. For example, components of the information processing system 500 can be implemented as physical or logical components. In addition, in some embodiments, functionality associated with components of the information processing system 500 can be implemented in special purpose circuits or components. In other modes of
2017-IPM-101598-U1-EN realization, a functionality associated with components of the information processing system 500 can be implemented in configurable universal circuits or components. For example, components of the information processing system 500 can be implemented by configured computer program instructions.
The memory controller hub (MCH) 502 may include a memory controller for directing information to or from various system memory components in the information processing system 500, such as a memory 503, a storage element 506 and a hard drive 507. The memory controller hub 502 can be coupled to memory 503 and a graphics processing unit (GPU) 504. The memory controller hub 502 can also be coupled to a memory controller hub 'I / O (ICH) or south bridge 505. The I / O controller hub 505 is coupled to storage elements of the information processing system 500, comprising a storage element 506, which may include a flash ROM comprising a basic input / output system (BIOS) of the computer system. The I / O controller hub 505 is also coupled to the hard drive 507 of the information processing system 500. The I / O controller hub 505 can also be coupled to a Super I / O chip 508, it - even coupled to several of the I / O ports of the computer system, including the keyboard 509 and the mouse 510. The mouse 510 can, in one or more embodiments, comprise one or more input elements capable of receiving a classic user input. This conventional input may include, for example, a push button, a touchpad, a touchscreen, a scroll wheel, a joystick, a keyboard, a mouse, a numeric keypad or any other device or element by which a user can enter a command. in the device.
In certain embodiments, the client device 1102 and the server 1106 of FIG. 11 can comprise an information processing system 500 with at least one processor and a memory device coupled to the processor which contains a set of instructions which, when executed, cause certain processor actions to be performed. In one or more embodiments, an information processing system 500 may include at least one processor and a memory device coupled to the processor which contains a set of instructions which, when executed, cause certain processor actions. In any embodiment, the information processing system may include a non-transient computer-readable medium that stores one or more instructions where the instruction (s) when executed, cause certain processor actions to be performed . As used herein, an information processing system can include any instrument or aggregate of instruments that can be used to calculate, classify, process, transmit, receive, retrieve, create, switch, store, display,
2017-IPM-101598-U1-FR manifest, detect, record, reproduce, manipulate or use any form of information, intelligence or data for commercial, scientific, control or other purposes. For example, an information processing system may be a computer terminal, a network storage device or any other suitable device and may vary in size, shape, performance, functionality and price. The information processing system 500 can comprise a random access memory (RAM), one or more processing resources such as a central processing unit (CPU) or a hardware or software control logic, a read only memory (ROM) ) or any other type of non-volatile memory. Additional components of the information processing system may include one or more disk drives, one or more network ports for communication with external devices as well as various I / O devices, such as a keyboard, mouse and video screen. The information processing system 500 can also include one or more buses used to transmit communications between the various hardware components.
FIG. 6 illustrates an example of an abnormal trend analysis system according to one or more aspects of the present invention, including an environment or a drilling site 100 for drilling a well, also called a well bore. As shown, a drilling platform 2 supports a drilling tower 4 comprising a movable block 6 for raising and lowering a drill string 8. A square rod 10 supports the drill string 8 when it is lowered via a rotary table 12. A drill bit 14 is driven by a downhole motor and / or a rotation of the drill string 8. When the drill bit 14 rotates, it creates a wellbore 16 which crosses various formations 18. A pump 20 circulates a drilling fluid through a supply pipe 22 towards the square rod 10, through the interior of the drill string 8, through orifices of the drill bit drilling 14, back to the surface (for example, areas accessible without entering the wellbore), via a ring around the drill string 8 and in a retention pit 24. The drilling fluid transports debris from the wellbore into the pit 24.
Data logging operations can be performed during drilling operations. In one example, drilling can be performed using a string of drill pipes connected together to form the drill string 8 which is lowered through the rotary table 12 into the wellbore. The drill tower 100 at the surface supports the drill string 8, when the drill string 8 is used to drill a wellbore penetrating the underground region. The upper drive rotates the terminal drill bit of the drill string without the use of a square rod and a rotary table. The blowout preventer is one or more valves installed at the well head to prevent
2017-IPM-101598-U1-EN pressure leakage either in the annular space between the casing and the drill pipe, or in an open hole (for example, a hole without a drill pipe) during drilling operations or completion. The mud pump is a large reciprocating piston pump used to circulate mud (drilling fluid) on a drilling tower. Mud pits are a series of open tanks, usually made of steel plates, through which drilling mud is recycled to allow sand and sediment to settle. Additives are mixed with the mud in the pit and the liquid is temporarily stored there before being reintroduced into the well. The mud pit compartments are also called vibrating pits, settling pits and suction pits, depending on their main purpose. In one example, the drill string 8 may include, for example, a square rod, a drill pipe, a bottom hole assembly and / or other components. The bottom hole assembly on the drill string 8 may include drill collars, drill towers, one or more logging tools, and other components. Drilling data logging tools may include pressure sensors, flow measurement sensors, load sensors, mud pump, drill string, mud pit, anti-shutter rash; measurement tools during drilling (MWD); logging tools during drilling (LWD); and others.
As shown in Figure 6, one or more MWD instruments are integrated into a logging tool 26 located near the drill bit 14. When the drill bit 14 extends the wellbore through the formations 18, the logging tool 26 simultaneously collects measurements or data relating to various formation properties, as well as the position of the drill bit and various other drilling conditions, drilling parameters or both. In one or more embodiments, the logging tool 26 may take the form of a drill collar (for example, thick-walled tubing which provides weight and rigidity to facilitate the drilling process) which is placed near the drill bit 14. An auxiliary rangefinder 28 (for example a transceiver) can be coupled to the logging tool 26 to transfer measurements from the logging tool 26 to a surface transceiver 30 , to receive commands from the surface transceiver 30 or both. In addition, in one or more embodiments, sensors or transducers 110 are located at the lower end of the drill string 8. In one or more embodiments, the sensors 110 can be located at any place along the drill string 8, for example, arranged at, on or around the logging tool 26 or a collar 112. While a drilling operation is in progress, one or more sensors 110 can continuously monitor one or more drilling parameters, one or more formation conditions, any other parameter or downhole condition or any combination thereof and transmit
2017-IPM-101598-U1-EN information or data corresponding to a surface detector (for example, the surface transceiver 30, a logging facility 120, an information processing system 130 or any other collection device data) by some form of telemetry. In one or more embodiments, the logging facility 120 may include an information processing system 130. One or more of a logging facility 120 and an information processing system 130 may be located in a communications environment. 100 drilling or remote from it. In one or more embodiments, the logging facility 120, the information processing system 130 or both can be communicatively coupled directly or indirectly to the telemetry device 28, to the logging tool 26, to the sensors 110 or any combination thereof.
One or more abnormal conditions may arise during a hydrocarbon operation, including, but not limited to, a drilling operation, a completion process, or both. Such an abnormal condition can be a training blow ("blow"). A blow may occur when the fluid (for example a liquid or a gas) in a reservoir 118 of a formation 18 prematurely penetrates into a part of a wellbore 16, for example in an annular space of the wellbore 16. Sufficient wellbore pressure must be applied to formation 18 to prevent formation fluids from entering prematurely into wellbore 18. Wellbore pressure represents the pressure exerted by a fluid due to the force of gravity , external pressure, friction, or any combination thereof. If the pressure exerted by the fluid is not sufficient, a blow may occur.
Detecting a blow as early as possible can reduce the risk of blowout, reduce the difficulty of controlling the well, increase productivity time and efficiency of operation in a 100 drilling environment, prevent failure of a equipment caused by high pressure during well control, and improving the safety margin for a hydrocarbon operation. However, one or more hit indicators can be difficult to analyze and may require extensive field experience to accurately detect a hit. One or more blow indicators may include, but are not limited to, an increase in flow (for example, an outflow is greater than an inward flow), an increase in the volume of the pit, a decrease in the pressure of the pump (for example, decrease in pressure in the support pipe), a change in weight of the drill string (for example, a decrease in weight on the drill bit), a drill break (for example, a sudden increase in the rate of penetration) or any combination thereof.
One or more embodiments provide robust and early detection of abnormal conditions, e.g., hit detection, for example using a
2017-IPM-101598-U1-EN drilling parameter, for example an exponent d which is based at least in part on real-time measurement data obtained by surface data logging, MWD techniques, LWD or any combination thereof, one or more hit indicators or any combination thereof. As used herein, "real time" data refers to data that is measured while a drilling operation is taking place simultaneously and measurements of the simultaneous drilling operation are used by the detection algorithm. early and robust blow. A plurality of trend indicators for robust and early hit detection can be determined without the use of additional specialized equipment during a drilling operation.
The following discussion describes, in more detail, examples of flowcharts for an early and robust blow detection method during a drilling operation and a method that detects a drilling operation using at least some drilling data in real time, and sample diagrams illustrating a hit detection based on determined trend indicators.
Figure 7 is a flow diagram for a method of abnormal trend analysis 200 of data according to one or more aspects of the present invention. In particular, the abnormal trend analysis method 200 provides early and robust hit detection using real-time drilling data. Any one or more steps of the method 200 can be implemented by one or more information processing systems, such as a processor 638 described in FIG. 9, an information processing system 500 described in FIG. 5, or any combination thereof.
In one or more embodiments, any one or more steps of FIG. 7 can be carried out jointly (for example after having detected that a drilling operation is in progress) with any one or more of the steps of FIG. 8 to detect a drilling operation in progress. It will be understood, however, that any treatment carried out in the method 200 by any suitable component described here can occur only at the top of the hole, only at the bottom of the hole, or at least part of both (for example, as a distributed method ).
When an active drilling operation is detected, early and robust hit detection can be performed dynamically or adaptively using real time data, substantially real time data or any other appropriate data. If a hit is detected, an alarm event related to the drilling operation is activated or triggered. An alarm event can consist in triggering an alarm, in flashing light sources, in sending one or more notification messages to the personnel concerned, in an information processing system in any combination thereof, in initializing
2017-IPM-101598-U1-FR a stop operation or a deactivation process or at any other stage or any combination thereof. In one or more embodiments, upon receipt or notification of an alarm event, any one or more actions to control the hit and to avoid loss of control of the well, such as temporarily suspending the 'drilling operation, can be carried out.
At block 201, real-time drilling data is received. At block 202, one or more drilling parameters can be extracted from real-time drilling data received from block 201. The drilling parameter (s) may include, but are not limited to, a penetration rate (ROP), a drill bit weight (WOB), a number of revolutions per minute (RPM) of the drill string or any combination thereof. The DPG graph of Figure 3 can be produced based, at least in part, on any one or more drilling parameters. In one or more embodiments, the real-time drilling data, corresponding to the data obtained over a given period of time, is received from a logging tool 26 (for example, installed as part of a downhole assembly or drill string as described above in Figure 6) during a drilling operation. In one or more embodiments, the real-time drilling data can be stored in a memory of an information processing system (for example, the memory 503 of the information processing system 500 of FIG. 5) and accessible from memory for processing. The drilling parameter (s) which are obtained during a drilling operation may relate to a given set of parameters for operating parts of the drilling set (for example, the drill bit 14, the drill string 8 , any other component on a site or any combination thereof). For example, extracting drilling parameters may require obtaining the drilling parameter from a real-time data stream. One or more hit parameters can be calculated for hit detection based, at least in part, on extracted drill parameters or real-time data from the real-time data stream. The drilling parameters can be extracted based, at least in part, on the frequency and noise processing of the data. The real-time data stream may include any one or more measurements or data associated with any one or more drilling operations, including but not limited to, temperature, pressure, fluid flow and any or more than one drilling operation and any one or more operating parameters, including but not limited to, drilling speed, speed of rotation of the drill string, hook load, WOB or any other operating parameter.
In block 204, one or more outliers associated with the drilling parameter (s) or the strike indicator (s) can be removed to produce
2017-IPM-101598-U1-FR 205 early strike detection (EKD) data cleaned (for example, filtered). In one or more embodiments, one or more physical criteria corresponding to a range of expected values for any one or more of the drilling parameter (s) or the strike indicator (s) may be used to suppress an outlier. In one or more embodiments, a wick weight (WOB) parameter worth 20,000 pounds (or about 9,071.85 kilograms) in a given drilling operation may not be a reasonable value given the physical criteria associated with the drilling environment, an underground region, or both, such as rock strength, and can be removed from real-time drilling data 201 as an outlier. The resistance of the rock can correspond to an intrinsic resistance of a given formation which includes rock, which can be based on the composition, the process or both the deposit and the compaction of the formation. A sufficient WOB value is used to overcome the resistance of the rock, as well as a drill bit which is capable of operating under this WOB used. Another physical criterion may include porosity where an ROP value may be higher in a more porous rock formation than in a low porosity rock formation, so that a low ROP value may be considered an outlier for a highly porous formation. In one or more embodiments, an outlier for the ROP drilling parameter may be rejected when a particular value for the ROP drilling parameter indicates a ROP value much greater or less than that expected given a or several other drilling parameters (for example, when the RPM or WOB increases in value, the ROP can increase proportionally in value).
The method 200 determines a value of a blow detection drilling parameter. In one or more embodiments, a real-time blow detection indicator is based, at least in part, on the blow detection drill parameter. In one or more embodiments, the blow detection drill parameter is a drill parameter for a plurality of trend indicators which can be used to identify abnormal pressure formation and to predict abnormal pore pressure. Hits during drilling are caused in many cases by penetration into abnormal pressure zones. Consequently, a plurality of trend indicators can play the role of a good indicator for detecting hits during drilling.
According to one or more embodiments, in block 206, one or more trend indicators can be defined or are determined. While it is easy to visually inspect the trend of the data, quantifying the trend is a non-trivial task. In one or more embodiments, four trend indicators are introduced to
2017-IPM-101598-U1-FR define the trend of real-time data, for example real-time data associated with a hydrocarbon drilling operation. The first indicator is the difference in average displacement of the original data. For example, in one or more embodiments, four trend indicators can be determined which define the trend for the real-time drilling data received from block 201. A first indicator can indicate a difference in the average displacement of the drilling data in real time received from block 201. The first indicator can be determined as indicated in equation 1. The values MA _a , t and ΜΑβ, ί are mean values of displacement at time t with a window length of a and β, respectively.
= MA q.-. - _r (a <β) (Equation 1)
DMA is the mean of differential displacement, t is a discrete time point in a time series, MA is a mean of displacement, a is a first range or a first duration of a data window where a, t defines a first time window and β is a second range or a second duration of a data window where β, ί defines a second time window. In one or more embodiments, the first window and the second window may be based, at least in part, on a sampling rate, a factor or an environmental condition to be measured (for example, a drilling speed where a and β can be relatively large, a throughput where the data is smooth and the data frequency is much higher, which results in a relatively low a and β) of the real-time drilling data received from block 201. A positive value for DMA indicates an upward trend and a negative value of DMA indicates a downward trend.
The second indicator is the slope or indicates the slope of a linear displacement regression, MK _t . The value of MK _t directly represents one or more local trends in the real-time data, positive values representing positive trends and negative values representing a negative trend or rather a positive value for MK _t indicates a positive trend, while a negative value for MK _t represents a negative trend. The value of MK _t directly represents local trends in real-time drilling data received at block 201. Data obtained from a borehole, for example, from a drill tower, can be noisy. Usually the MK _t values can still be very coarse and not applicable to trend analysis. For example, the data associated with a hydrocarbon site, for example, the drilling environment or site 100 in Figure 6, can be so noisy that the value of MK _t does not apply to a trend analysis . A second smoothing step is recommended to eliminate the effect of local noise fluctuations. The smoothing technique can follow an averaging algorithm
2017-IPM-101598-U1-EN weighted displacement or a third indicator described as follows where n represents the length of the displacement window.
A third trend indicator MAK _t represents an average trend on a longer time scale defined by n, the length of the travel time window. Both the sign and the absolute value of MAKt represent the trend of the data. MAKt can be determined as shown in Equation 2, Equation 3 and Equation 4.
(Equation 2) where wi, t represents the weighted displacement average, z is a point in the displacement time window t and n is the length of the window.
ï = t - n + 1, t - n + 2, ......, t (Equation 3)
(Equation 4)
The fourth trend indicator is defined as the difference from the mean of the displacement slope (DMAKi) and can be determined as shown in Equation 5.
DMAK *. - MAK _aZ 3L4 / <p _it ια '-. Β.' (Equation 5)
The MAKa, t and MAKp, are MAKt values with a window length of a and β, respectively. Positive MAKt values represent or indicate an increasing acceleration of the data trend and negative MAKt values represent or indicate a decreasing acceleration of the data trend.
In block 208, one or more thresholds are established based, at least in part, on DMA and DMAK. The threshold (s) indicate an upper or lower limit of a data trend. In one or more embodiments, the threshold may be based, at least in part, on an ability of the drill tower, personnel, or both to handle an abnormal condition including, but not limited to, the type of the drilling tower, the size of the mud pit, the maximum allowable blow volume or any other factor. For example, Figure 1 illustrates a real-time recording of two hit indicators for a gas hit during a rotational drilling operation plotted for a specified time interval or period. A first blow indicator is a flow parameter group (FPG) which incorporates parameters related to the flow, including, but not limited to, the incoming flow, the support pipe pressure and the outgoing flow. A second hit indicator is a group of drilling parameters that incorporates one or more parameters related to drilling, including, but not limited to, ROP, RPM and WOB.
2017-IPM-101598-U1-EN
When a hit occurs, the FPG will exhibit an abnormal upward trend (as indicated by the solid line of the FPG), and the DPG will exhibit an accelerating deceleration tendency (as indicated by the solid line of the DPG).
In block 210, the probability of an abnormal condition is determined. For the detection of an abnormal upward trend, the DMA is calculated in real time on the basis of the FPG data as illustrated in FIG. 2. This upward trend may indicate an abnormal condition. For abnormal downtrend detection as shown in Figure 3, the MK, DMAK and DPG are plotted for a specified time interval or period, for example, about one minute (illustrated by the line MAK 1 min ) and three minutes (illustrated by the MAK line 3 min). To determine a probability of occurrence of an abnormal condition, an alarm threshold can be defined, for example a DMA alarm threshold. The DMA alarm threshold in Figure 2 provides an upper limit so that, when an increasing DMA trend exceeds or reaches the DMA alarm threshold, a hit alarm is triggered and the threshold The alarm in Figure 3 provides a lower limit so that when a downward DMAK trend falls below or reaches a DMAK alarm threshold, a hit alarm is triggered.
In one or more embodiments, a hit risk index (KRI) can be determined as shown in equation 6.
RR] = w _d P _d + WfPf (Equation 6)
Pf and Pd represent the probability of abnormal FPG and DPG conditions, respectively, and Wd and ny are the weighting factors of P / and Pd, respectively. Pf can be calculated by dividing the DMA value (for example, the DMA value shown in Figure 2) by the DMA alarm threshold, Pd can be calculated by dividing the DMAK value (for example, the value of DMAK illustrated in Figure 3) by the DMAK alarm threshold. In one or more embodiments, the DMA alarm threshold and the DMAK alarm threshold may be predetermined thresholds based, at least in part, on historical trends or historical data, user input, or any other appropriate criteria. In block 212, it is determined whether a hit has been detected or responds to a threshold occurrence probability based on the determined probability of an abnormal condition from block 210, for example, based on the KRI. For example, a probability close to zero can mean or indicate a very low chance of a hit, while a probability close to one can mean or indicate a hit that is very likely to happen or is happening.
At block 216, an event is triggered based on block 212. In one or more embodiments, an event may include any one or more
2017-IPM-101598-U1-FR among triggering an alarm, stopping or switching off a pump, adjusting a valve, fluid redirection, activating a pump, stopping the rotation of the drill string or any other step of attenuation or modification or adjustment of a drilling operation which prevents a blow. Any one or more events can be implemented manually or automatically.
At block 214, if the hit is not detected at block 212, method 200 is exited and a next set of drilling data for a next period of time is read. The next time period of the next drilling data set may be in a time proximity close to the time when process 200 is in progress. In one example, operations in method 200 can be repeated for the next set of drilling data. Alternatively or in addition, operations in a method described below in Figure 8 can be performed using this next set of drilling data.
In one or more implementations, a deactivation process can be initiated in response to the activation of the alarm event, such as when the hit is detected with a high probability as determined in block 210 of Figure 7. The The deactivation process may include performing certain actions, such as stopping the drill string, the mud pump and / or other parts of the drilling assembly. The deactivation process, in one example, may not start unless there is no user intervention or input from a human operator to override the deactivation process for a period of time. predetermined time after activation of the alarm event (for example, to give time to a human operator to bypass the deactivation process because stopping the drilling operation can be time consuming, disruptive, costly or any combination thereof). For example, a predetermined period of time is expected to receive user input from the human operator in order to bypass the deactivation process after the activation of the alarm event and after the lapse of time elapsed, the deactivation process is carried out if the user input is not received.
Thus, the invention presents a fast, efficient and simple method for the automatic detection of abnormal tendency of drilling data in real time. In one or more embodiments, any one or more of six types of abnormal trends can be detected using any one or more aspects of this specification, including acceleration, deceleration, acceleration of deceleration, acceleration of acceleration, deceleration of deceleration and deceleration of acceleration. Unlike previous trend analysis of real-time data, for example for hydrocarbon operations, which is mainly based on observations
2017-IPM-101598-U1-EN visual, this description provides one or more algorithms that apply one or more quantified trend indicators to perform automatic detection of abnormal trends in real time.
Figure 8 is a flow diagram which conceptually illustrates an example method 300 for detecting an abnormal trend or determining a trend analysis in a drilling operation using real time data in accordance with one or more aspects of the present invention. In one or more embodiments, the method 300 can be implemented by one or more information processing systems, such as the processor 638 described in FIG. 9 or in FIG. 10, the information processing system 500 described in Figure 5 or both. FIG. 8, in an example, can be carried out jointly (for example before performing the robust and early blow detection algorithm) with the method 200 described in FIG. 7. It will however be understood that any processing carried out in the method 300 by any suitable component described herein can occur only at the top of the hole, only at the bottom of the hole, or at least part of both (eg, distributed processing).
301 real-time drilling data can be provided or received. For example, drilling data 301 can be received from a logging tool (for example, installed as part of a downhole assembly or from a drill string such as the logging tool 26 in Figure 6) during a drilling operation. In another example, the real-time drilling data 301 may be stored in a memory (for example, memory 503 in Figure 5) during the drilling operation and accessible from the memory for processing. In block 302, the received real-time drilling data 301 can be converted by one or more read and format data conversion operations to produce, as output, converted drilling data 304. In one example, the drilling data Real-time drilling received can be filtered to remove outliers related to one or more respective drilling parameters. The method 300 can then perform different types of checks, based on the converted drilling data 304, to determine if a drilling operation is in progress.
In block 306, it is determined whether the converted drilling data 304 indicates drilling activity in connection with an activity check 320. In some examples, the converted drilling data includes data which may indicate drilling activity, such as the measured drilling parameters for penetration rate, bit weight and revolutions per minute, as shown above in Figure 7. If the converted drilling data 304 does not include such drilling parameters, an indication 307 a non-drilling operation can be provided, and the early and robust blow detection method
2017-IPM-101598-U1-FR (for example, method 200 of Figure 7) is not executed and a next set of real-time drilling data for a later period of time is accessed or received at block 314 .
In block 308, in response to the detection of drilling activity, it is determined whether at least one drilling parameter is active in connection with a mechanical check 330. A particular drilling parameter, included in the drilling data, can be determined to be inactive if a value for the particular drilling parameter does not indicate that a drilling operation is in progress, indicates an incorrect sensor reading, or both. For example, a particular drilling parameter is inactive when a weight parameter on drill bit is insufficient (for example, not important enough to drill through rock in the underground region) or when the value of the revolutions per minute of the drill string drilling is too low (for example, less than 10 rpm), or when the penetration rate is greater than zero but substantially close to zero. If the at least one drilling parameter is not active, an indication 309 of an execution operation (for example, the withdrawal of the drill string from the wellbore or its replacement in the wellbore) , circulation (for example, pumping a fluid through the entire fluid system, including the wellbore and the entire surface reservoir), reconditioning (for example, repairing or stimulating a well of existing production) and / or the bore (for example, the enlargement of the wellbore) can be provided, and the robust and early blow detection method (for example, the method 200 of FIG. 7) does not is not executed and a next set of real-time drilling data for a later period of time is accessed or received at block 314.
At block 310, in response to detecting that at least one drilling parameter is active, it is determined whether at least one pump is active in connection with a hydraulic check 340. One or more hydraulic parameters can be checked to determine whether at least one pump is active, for example a pump flow, a pump displacement and / or a pump pressure. If at least one pump is not active, an indication 311 of an execution and / or connection operation (for example, adding a length of drill pipe to the drill string to continue the drilling) can be provided, and the robust and early blow detection method (e.g. method 200 of Figure 7) is not executed and a next set of real-time drilling data for a later period of time is accessed or received at block 314.
In block 312, in response to detecting that at least one pump is active, it is determined whether the depth of the drill string or part thereof (for example, the drill bit, the pipe drilling) increases in connection with a direction check 350. If the depth does not increase, an indication 313 of execution and / or of repackaging can be provided, and the method of early and robust hit detection (by
2017-IPM-101598-U1-EN example, method 200 of Figure 7) is not executed and a next set of real-time drilling data for a later period of time is accessed or received at block 314.
In block 316, in response to the detection of the increase in depth, a drilling operation is indicated as being in progress. At block 318, in response to the indication that the drilling operation is in progress, an early and robust hit detection method (for example, method 200 of Figure 7) can be performed.
The following discussion in Figures 9 and 10 relate to examples of a drilling assembly and a logging assembly for a given oil or gas well system which can be used to implement blow detection techniques early and robust described above.
Petroleum and gas hydrocarbons can naturally be found in one or more underground formations. An underground formation containing a hydrocarbon or water can be called a reservoir. A tank can be located under ground or offshore. Reservoirs are generally located in a depth range from a few hundred feet (shallow tanks) to a few tens of thousands of feet (ultra-deep tanks). To produce a hydrocarbon, a wellbore is drilled in a reservoir or adjacent to a reservoir. The fluid (a hydrocarbon or water, for example) produced from the wellbore is called a reservoir fluid.
FIG. 9 illustrates an example of a drilling assembly 600 intended to implement one or more embodiments according to the present invention. It should be noted that although Figure 9 generally depicts an onshore drilling rig, those skilled in the art will readily recognize that the principles described herein are also applicable to underwater drilling operations that use platforms and towers floating or marine drilling, without departing from the scope of the description.
In one or more implementations, the method 200, the method 300 or both described above can begin at any one or more of before or while the drilling assembly 600 is drilling a wellbore 616 entering an underground formation 618. It will however be understood that any treatment carried out in method 200, method 300 or both using any suitable component described here can occur only at the top of the hole, only at the bottom of the hole or at least in part of both (for example, distributed processing). As illustrated, the drilling assembly 600 may include a drilling platform 602 which supports a drilling tower 604 having a movable block 606 for raising and lowering a drill string 608. The drill string 608 can include, but not be limited to, drill pipe and coiled tubing, which are generally known to those of skill in the art. A 610 square rod supports the string of
2017-IPM-101598-U1-FR drill 608 when lowered via a rotary table 612. A drill bit 614 is attached to the distal end of the drill string 608 and is driven either by a motor at the bottom of the well and / or by rotation of the drill string 608 from the surface of the well. When the drill bit 614 rotates, it creates the wellbore 616 which enters various underground formations 618.
A pump 620 (for example a mud pump) circulates the drilling mud 622 through a supply pipe 624 and towards the square rod 610, which transports the drilling mud 622 down the hole through the interior of the drill string 608 and through one or more orifices of drill bit 614. Drill mud 622 is then recycled to the surface via a ring 626 defined between drill string 608 and the walls of the wellbore 616. At the surface, the recycled or spent drilling mud 622 leaves the ring 626 and can be transported to one or more fluid treatment units 628 via a line of interconnection flow 630. After passing through the fluid treatment unit (s) 628, a "cleaned" drilling mud 622 is deposited in a neighboring retention pit 632 (ie, a mud pit) . Although illustrated as being disposed at the outlet of the wellbore 616 via the ring 626, those skilled in the art will readily appreciate that the fluid treatment unit (s) 628 can be placed at any other location in the drilling assembly 600 to facilitate its own function, without departing from the scope of the description.
Chemicals, fluids, additives and the like can be added to drilling mud 622 via a mixing hopper 634 coupled communicatively or otherwise in fluid communication with the retention pit 632. The mixing hopper Mixing 634 can include, but is not limited to, mixers and related mixing equipment known to those of skill in the art. In other implementations, however, chemicals, fluids, additives and the like can be added to the drilling mud 622 at any other location in the drilling assembly 600. In at least one implementation, for example, there may be more than one 632 retention pit, such as multiple 632 retention pits in series. In addition, the retention pit 632 may be representative of one or more fluid storage facilities, units or both where chemicals, fluids, additives and the like can be stored, reconditioned and / or regulated up to that they be added to drilling mud 622.
The processor 638 can be a part or a component of the hardware used to implement the various blocks, modules, elements, components, methods and illustrative algorithms described here. Processor 638 can be configured to execute one or more sequences of instructions, programming positions, or stored code
2017-IPM-101598-U1-FR on a non-transient computer-readable medium. The processor 638 can comprise, for example, an information processing system 500 of FIG. 5.
The executable sequences described here can be implemented with one or more code sequences contained in a memory. In one or more embodiments, such code can be read from memory from another machine-readable medium. The execution of the sequences of instructions contained in the memory can cause a processor 638 to execute the operating steps described here. One or more processors 638 in a multiprocessing arrangement can also be used to execute sequences of instructions in memory. In addition, wired circuits can be used in place of, or in combination with software instructions to implement various implementations described here. Thus, these implementations are not limited to any specific combination of hardware, software, or both.
As used herein, machine readable media will refer to any media that directly or indirectly provides instructions to processor 638 for execution. Machine-readable media can take many forms, including, for example, non-volatile media, volatile media, and transmission media. Non-volatile media may include, for example, optical and magnetic discs. Volatile media can include, for example, dynamic memory. Transmission media can include, for example, coaxial cables, wires, optical fibers, and wires that form a bus. Common forms of machine-readable media may include, for example, floppy disks, floppy disks, hard disks, magnetic tapes, other similar magnetic media, CD-ROMs, DVDs, other optical media analogs, punch cards, paper tapes, and similar physical media with patterned holes, RAM, ROM, PROM, EPROM, and flash EPROM.
The drill assembly 600 may further include a downhole assembly (BHA) coupled to the drill string 608 near the drill bit 614. The BHA may include various downhole measurement tools such as, but not limited to, during drilling (MWD) and during drilling (LWD) logging tools, which can be configured to perform downhole and / or tophole measurements of formations surrounding underground 618. Along drill string 608, drilling while drilling (LWD) or measurement during drilling (MWD) equipment 636 is included. In one or more implementations, the drilling assembly 600 involves the drilling of the wellbore 616 while the logging measurements are carried out with the LWD / MWD equipment 636. More generally, the methods described here involve the introduction a wellbore logging tool that is capable of determining wellbore parameters, including
2017-IPM-101598-U1-FR including the mechanical properties of the formation. The logging tool can be an LWD logging tool, an MWD logging tool, a wired logging tool, a smooth cable logging tool, and the like. In addition, it is understood that any processing carried out by the logging tool can only occur at the top of the hole, only at the bottom of the hole, or at least in part of the two (i.e., distributed processing).
According to the present description, the LWD / MWD 636 equipment can comprise a stationary acoustic sensor and a mobile acoustic sensor used to detect the flow of fluid flowing in and / or adjacent to the wellbore 616. In an example , the stationary acoustic sensor can be arranged around the longitudinal axis of the LWD / MWD equipment 636, and thus of the wellbore 616 at a predetermined fixed location inside the wellbore 616. The acoustic sensor mobile can be arranged around the longitudinal axis of the LWD / MWD 636 equipment and, thus, of the wellbore 616, and is designed to move along the longitudinal axis of the wellbore 616. However, the The arrangement of the stationary acoustic sensor and the mobile acoustic sensor is not limited thereto and the acoustic sensors can be arranged in any configuration as required by the application and design.
The LWD / MWD 636 equipment can transmit the measured data to a 638 processor on the surface wired or wirelessly. Data transmission is generally illustrated on line 640 to demonstrate the transmissible coupling between the processor 638 and the LWD / MWD equipment 636 and does not necessarily indicate the path to which the communication is carried out. The stationary acoustic sensor and the mobile acoustic sensor can be communicatively coupled to the line 640 used to transfer measurements and signals from the BHA to the processor 638 which processes the acoustic measurements and the signals received by acoustic sensors (for example, a stationary acoustic sensor, a mobile acoustic sensor) and / or controls the operation of the BHA. In the technology in question, the LWD / MWD equipment 636 may be able to perform a log analysis of the underground formation 618 near the wellbore 616.
In certain implementations, part of the processing can be carried out by a telemetry module (not shown) in combination with the processor 638. For example, the telemetry module can preprocess the individual sensor signals (for example, by conditioning, filtering and / or removing noise from a signal) and transmitting them to a surface data processing system (for example, processor 638) for further processing. It should be noted that any processing carried out by the telemetry module can occur only at the top of the hole, only at the bottom of the hole, or at least in part of the two (for example, distributed processing).
2017-IPM-101598-U1-EN
In various implementations, the processed acoustic signals are evaluated in conjunction with measurements from other sensors (for example, surface well pressure and temperature measurements) to assess flow conditions and the overall integrity of the well. The telemetry module may include any known downhole communication means including, but not limited to, a pulsed mud telemetry system, an acoustic telemetry system, a wired communication system, a wireless communication system. wire, or any combination thereof. In certain implementations, some or all of the measurements taken by the stationary acoustic sensor and the mobile acoustic sensor can also be stored in a memory associated with the acoustic sensors or with the telemetry module for subsequent recovery at the surface when the train is removed. drill pipe 608.
FIG. 10 illustrates a set of logs 700 having a suitable wire system for implementing the methods described here. As illustrated, a platform 710 can be equipped with a drilling tower 712 which supports a winch 714. Oil and gas well drilling, for example, is commonly carried out using a train of drilling pipes connected between them so as to form a drill string which is lowered via a rotary table 716 into a well bore 718. Here it is assumed that the drill string has been temporarily removed from the well drilling 718 to allow a logging tool 720 (and / or any other suitable wired tool) to be lowered by wire rope 722, smooth cable, coiled tubing, tubing, downhole tractor, log cable and / or any other physical structure or suitable means of transportation extending downhole from the surface into wellbore 718. Typically, the logging tool 720 is lowered to a region of interest and then pulled towards the top at a substantially constant speed. During the upward movement, the instruments included in the logging tool 720 can be used to make measurements on the underground formation 724 adjacent to the wellbore 718 during the passage of the logging tool 720. In addition, it it is understood that any processing carried out by the logging tool 720 can only occur at the top of the hole, only at the bottom of the hole, or at least in part of the two (for example, distributed processing).
The logging tool 720 can include one or more wired instruments which can be suspended in the wellbore 718 by the metal cable 722. The wired instrument (s) can comprise the stationary acoustic sensor and the mobile acoustic sensor, which can be coupled communicatively to the metal cable 722. The metal cable 722 can include conductors for transporting energy to the wired instrument and also facilitating communication between the surface and the wired instrument.
2017-IPM-101598-U1-EN
The logging tool 720 may include a mechanical component for causing movement of the mobile acoustic sensor. In some implementations, the mechanical component may need to be calibrated to provide more precise mechanical movement when the mobile acoustic sensor is repositioned along the longitudinal axis of wellbore 718.
Acoustic sensors (for example, the stationary acoustic sensor, the mobile acoustic sensor) can include electronic sensors, such as hydrophones, piezoelectric sensors, piezoresistive sensors, electromagnetic sensors, accelerometers or the like. In other implementations, the acoustic sensors can comprise fiber optic sensors, such as point sensors (for example Bragg gratings with fibers, etc.) distributed at desired or predetermined locations along the length of a optical fiber. In still other implementations, the acoustic sensors can include distributed acoustic sensors, which can also use optical fibers and allow a distributed measurement of local acoustics at any given point along the fiber. In still other implementations, the acoustic sensors may include optical accelerometers or optical hydrophones which have fiber optic cabling.
In addition or alternatively, in one example (not explicitly illustrated), the acoustic sensors can be attached to or incorporated in the casing train (s) lining the wellbore 718, the wall of the wellbore 718 or both axially spaced predetermined distance.
A logging facility 728, shown in Figure 10 in the form of a truck, can collect measurements from acoustic sensors (e.g., stationary acoustic sensor, mobile acoustic sensor), and can include processor 638 to control , process, store and / or view the measurements collected by the acoustic sensors. The processor 638 can be communicatively coupled to the wired instrument (s) by means of the metallic cable 722. As a variant, the measurements collected by the logging tool 720 can be transmitted (wired or wireless) or physically delivered to off-site calculation where the methods and procedures described here can be implemented.
As described here, different approaches can be implemented in different environments depending on the embodiments described. For example, FIG. 11 illustrates a schematic diagram of an example of an environment 1100 for the implementation of aspects according to various embodiments. As will be understood, although a client-server environment is used for explanatory purposes, different environments can be used, if necessary, to implement various embodiments. The system includes a
2017-IPM-101598-U1-EN 1102 electronic client device, which may include any suitable device which can be used to send and receive requests, messages or information over an appropriate network 1104 and return the information to a user of the device. Examples of such client devices include personal computers, portable telephones, portable messaging devices, portable computers, set-top boxes, personal data assistants, electronic book readers and the like.
Network 1104 can include any suitable network, including an intranet, the Internet, a cellular network, a local network, or any other such network or combination thereof. The network 1104 could be a “push” network, a “pull” network or a combination of these. In a push network, one or more servers push data to the client device. In a pull network, one or more servers send data to the client device on request for data from the client device. The components used for such a system may depend at least in part on the type of network and / or environment selected. The protocols and components for communicating via such a network are well known and will not be described here in detail. Calculation on the 904 network can be activated via wired and wireless connections and combinations thereof. In this example, the network includes the Internet, since the environment includes a server 1106 to receive requests and serve content in response thereto, although for other networks, an alternative device for a similar purpose may be used, such as this would appear obvious to a person skilled in the art.
The client device 1102 can represent the logging tool 720 of FIG. 10 and the server 1106 can represent the processor 638 of FIG. 9 in certain implementations, or the client device 1102 can represent the processor 638 and the server 1106 can represent off-site IT facilities in other implementations.
Server 1106 will typically include an operating system which provides executable program instructions for general administration and operation of that server and will typically include computer readable media storage instructions which, when executed by a processor of the server, allow the server to perform its intended functions. Appropriate implementations for the operating system and the general functionality of the servers are known or commercially available and are easily implemented by a person skilled in the art, in particular in the light of the present description.
The environment in one embodiment is a distributed computing environment using multiple computer systems and components which are
2017-IPM-101598-U1-FR interconnected via computer links, using one or more computer networks or direct connections. However, a person skilled in the art will appreciate that such a system can function equally well in a system having a number of components less or greater than that illustrated in FIG. 11. Thus, the representation of the environment 1100 in FIG. 11 must to be considered as being of an illustrative nature and not limiting the scope of the description.
In one or more embodiments, a method of detecting an abnormal trend in a drilling operation includes receiving real-time drilling data including a plurality of drilling parameters measured during a drilling operation, determining one or more trend indicators based, at least in part, on the received real-time drilling data, wherein determining the trend indicator (s) includes determining a first trend indicator, wherein the first indicator trend includes an average displacement of drilling data in real time, determining a second trend indicator, wherein the second trend indicator includes a linear regression slope of displacement, determining a third indicator trend, wherein the third trend indicator includes an average trend and determining a n fourth trend indicator, in which the fourth trend indicator comprises a difference in mean of the displacement slope and the triggering of an alarm based, at least in part, on a threshold and the trend analysis. In one or more embodiments, the method further includes modifying a drilling operation based, at least in part, on the trend analysis. In one or more embodiments, the determination of the first indicator comprises the determination of: DMAt = MAD, t - ΜΑβ, ί, where α <β), and where MAa, t and ΜΑβ, ί are mean displacement values at time t with a window length of a and β, respectively. In one or more embodiments, the method further includes determining the second indicator comprising determining MKt, where MKt represents one or more local trends of the received drilling data, and wherein positive values represent positive trends and negative values represent negative trends. In one or more embodiments, the method further comprises
MK
MAK _t = ---- ¹ determination of the third indicator including the determination of: ^w i, t ^{Wi, t_} Γ7 Γ. 1-0.5 + n ^ Tj
WHERE 1 + exp [2 ₀ f], _where i = t - Il + 1, t - Il + 2.
, t, t t and where n and defines a time scale. In one or more embodiments, the method further includes determining the fourth trend indicator including determining DMAKt =
2017-IPM-101598-U1-EN
ΜΑΚα, ί - ΜΑΚβ, ί (α <β), where ΜΑΚα, ί and ΜΑΚβ, ί are MAKt at time t with a window length of a and β, respectively. In one or more embodiments, the method further includes determining a hit risk index, wherein determining the hit risk index comprising determining ⁼ d + ^w f F, where Pf and Pd respectively represent the probability of abnormal conditions of a group of flow parameters and group of drilling parameters respectively, and where wd and wf are weighting factors of Pf and Pd, respectively.
In one or more embodiments, a non-transient computer-readable medium storing one or more instructions which, when executed by a processor, cause the processor to: receive drilling data in real time, determine one or more indicators trends based, at least in part, on received real-time drilling data, wherein determining the trend indicator (s) includes: determining a first trend indicator, wherein the first trend indicator includes an average displacement of drilling data in real time, determination of a second trend indicator, in which the second trend indicator comprises a linear regression slope of displacement, determination of a third trend indicator, in which the third trend indicator includes an average trend and the determination of a fourth ten indicator dance, in which the fourth trend indicator comprises a difference in mean of the displacement slope and the determination of a trend analysis based, at least in part, on one or more trend indicators and the triggering of an alarm based, at least in part, on a threshold and trend analysis. In one or more embodiments, the computer-readable medium further comprises the determination of the first indicator comprising the determination of DMA _t = MA _a , t - ΜΑβ, ί, where a <β, where MA _a , _t and ΜΑβ, ί are mean displacement values at time t with a window length of a and β, respectively. In one or more embodiments, the computer-readable medium further includes determining the second indicator including determining MKt, where MK _t represents one or more local trends in the received drilling data, and wherein positive values representing positive trends and negative values represent negative trends. In one or more embodiments, the computer-readable medium further includes determining the third
MK
MAK _t = -----! ·
..... 'ii ^w it, t, t indicator including the determination of:
^{W |} * “7 / r _n io.5 + nt, .i + κρ [-2 ---- θ ----.!] _ _{Where i = t} - _{n +} i, t- _{n + 1} , where t and where n defines a
2017-IPM-101598-U1-FR timescale. In one or more embodiments, the computer-readable medium further includes determining the fourth trend indicator including determining DMAKt = MAK _a , t -ΜΑΚβ, ί (α <β), where MAK _a , t and MAKpt represent MAK _t at time t with a window length of a and β, respectively. In one or more embodiments, the computer-readable medium further includes one or more instructions which, when executed by a processor, further cause the processor to determine a hit risk index, in which the determination of the hit risk index includes the determination of = w ^ P ^ + WfPf p ^. _el p _d represent the probability of abnormal conditions of the flow parameter group and the drilling parameter group, respectively, and where w and w / are weighting factors of P / and Pd, respectively.
In one or more embodiments, an information processing system comprising a memory, a processor coupled to the memory, in which the memory includes one or more instructions executable by the processor for: receiving drilling data in real time, determining one or more trend indicators based, at least in part, on the received real-time drilling data, wherein determining the trend indicator (s) includes: determining a first trend indicator, wherein the first trend indicator includes an average displacement of drilling data in real time, determining a second trend indicator, wherein the second trend indicator includes a linear regression slope of displacement, determining a third indicator of trend, in which the third trend indicator includes an average trend and the determinati a fourth trend indicator, in which the fourth trend indicator comprises a difference in mean of the displacement slope, the determination of a trend analysis based, at least in part, on one or more trend indicators and the triggering of an alarm based, at least in part, on a threshold and analysis of trends. In one or more embodiments, the information processing system further comprises the determination of the first indicator comprising the determination: of DMA _t = MA _a , t - ΜΑβ, ί, (α <β), where MA _a , t and ΜΑβ, ί are mean values of displacement at time t with a window length of a and β, respectively. In one or more embodiments, the information processing system further comprises determining the second indicator including determining MK _t , where MK _t represents one or more local trends in the received drilling data, and wherein values positive represent positive trends and negative values represent negative trends. In one or more embodiments, the information processing system further comprises determining the
2017-IPM-101598-U1-EN
third indicator including the determination of: ^w i .t, where
'Π, where i - t ^{- 11} + T t ^- n + 2 ........ t and where n defines a time scale. In one or more embodiments, the information processing system further comprises determining the fourth trend indicator comprising determining DMAKt = MAK _a , t -MAKpt (α <β), where MAK _{a> t} and MAKpt represent MAK _t at time t with a window length of a and β, respectively. In one or more embodiments, the information processing system further includes one or more instructions that can be executed by the processor to determine a hit risk index, wherein determining the hit risk index includes the determination of ^ 81 = w ^ P ^ + WfPf p ^. _el p _d represent the probability of abnormal conditions of the flow parameter group and the drilling parameter group, respectively, and where w and w / are weighting factors of P / and Pd, respectively.
Therefore, the present invention is well suited to achieve the stated objectives and advantages as well as those inherent therein. The particular embodiments described above are given for illustration purposes only, to the extent that the present invention can be modified and practiced in different but equivalent ways which are obvious to those skilled in the art that takes advantage of these lessons. In addition, no limitation relates to the construction or design details presented herein, other than those described in the claims below. It is therefore obvious that the particular illustrative embodiments described above can be altered or modified and all these variations are considered within the scope and spirit of the present invention. In addition, the terms in the claims have their simple and ordinary meaning, unless explicitly stated otherwise and clearly defined by the patent owner.
A number of examples have been described. However, it will be understood that various modifications can be made. Consequently, other implementations fall within the scope of the following claims.
A reference to an element in the singular is not intended to mean one and only one, unless it is specifically indicated, but rather one or more. For example, "a" module can refer to one or more modules. An element preceded by “a”, “an”, “the” or “the said” does not prevent, without other constraints, the existence of additional identical elements.
2017-IPM-101598-U1-EN
Titles and subtitles, if any, are used for convenience only and do not limit the invention. The term example is used to refer to an example or illustration. To the extent that the term includes, a or the like is used, such a term is intended to be inclusive in a manner similar to the term to understand in the same way that to understand is interpreted when used as a transition word in a claim . Relational terms such as first and second and the like can be used to distinguish one entity or action from another without necessarily requiring or implying such a relationship or order between these entities or actions.
Expressions such as an aspect, the aspect, another aspect, certain aspects, one or more aspects, an implementation, the implementation, another implementation, some implementations, one or more implementations work, one embodiment, the embodiment, another embodiment, some embodiments, one or more embodiments, one configuration, the configuration, another configuration, some configurations, one or more configurations, the technology in question, the description, this description, other variations thereof, and the like are for convenience and do not imply that a description regarding this or these expressions is essential to the technology in question or that such a description applies to all configurations of the technology in question. A description relating to this or these expressions may apply to all of the configurations, or to one or more configurations. A description relating to this expression or expressions may provide one or more examples. An expression such as an aspect or certain aspects can refer to one or more aspects and vice versa, and this applies in the same way to other previous expressions.
An expression "at least one of" preceding a series of elements, with the terms "and" or "or" to separate any one of the elements, modifies the list as a whole rather than each member of the list. The expression "at least one of" does not require the selection of at least one element; on the contrary, the expression allows a meaning which includes at least any one of the elements, and / or at least one of any combination of the elements, and / or at least one of each of the elements. By way of example, each of the expressions "at least one of A, B and C" or "at least one of A, B or C" refers to only A, only B, or only C; any combination of A, B and C; and / or at least one of each of A, B and C.
It is understood that the specific order or hierarchy of the steps, operations or procedures described is an illustration of examples of approach. Unless explicitly stated otherwise, it is understood that the specific order or hierarchy of steps, operations or procedures can be executed in a different order. Some of the steps, operations or
2017-IPM-101598-U1-EN processes can be executed simultaneously. The appended process claims, if any, present elements of the different steps, operations or processes in a sample order, and are not intended to be limited to the specific order or hierarchy presented. These can be performed in series, linearly, in parallel or in a different order. It should be understood that the instructions, operations and systems described can generally be integrated together into a single software / hardware product or packaged in several software / hardware products.
The description is provided to enable any person skilled in the art to practice the various aspects described here. In some cases, well-known structures and components are shown in the form of a block diagram to avoid obscuring the concepts of the technology in question. The description provides various examples of the technology in question, and the technology in question is not limited to these examples. Various modifications of these aspects will be readily apparent to those of skill in the art, and the principles described herein can be applied to other aspects.
The title, context, brief description of the drawings, the abstract and the drawings are incorporated herein into the description and are provided as illustrative examples of the invention, and not in the form of restrictive descriptions. These elements are submitted with the understanding that they will not be used to limit the scope or meaning of the claims. In addition, in the detailed description, it can be seen that the description provides illustrative examples and that the various characteristics are grouped together in various implementations in order to simplify the description. The description process is not to be construed as reflecting an intention that the claimed object requires more features than those expressly stated in each claim. On the contrary, as the claims reflect, the inventive object resides in less than all the characteristics of a single configuration or described operation. The claims are incorporated here in the detailed description, each specific claim being considered as a separately claimed object.
The claims are not intended to be limited to the aspects described here, but should be given the full scope compatible with the language claims and encompass all legal equivalents. However, none of the claims is intended to cover an object which does not meet the requirements of applicable patent law, nor should it be interpreted in this sense.

权利要求:
Claims (15)
[1" id="c-fr-0001]
1. Method for detecting an abnormal trend in a drilling operation comprising:
receiving real-time drilling data comprising a plurality of drilling parameters measured during a drilling operation;
determining one or more trend indicators based, at least in part, on the received real-time drilling data, wherein determining the trend indicator (s) includes:
determining a first trend indicator, wherein the first trend indicator comprises an average of movement of the drilling data in real time;
determining a second trend indicator, wherein the second trend indicator includes a linear regression displacement slope;
determining a third trend indicator, wherein the third trend indicator includes an average trend; and determining a fourth trend indicator, wherein the fourth trend indicator comprises a difference in mean of the displacement slope;
determining a trend analysis based, at least in part, on the trend indicator (s); and triggering an alarm based, at least in part, on a threshold and trend analysis.
[2" id="c-fr-0002]
2. Method according to claim 1, in which the determination of the first indicator comprises the determination:
of DMA _t = MA _a , t - ΜΑβ, ι, (α <β), where MA _a , _t and MAp, _t are mean displacement values at time t with a window length of a and β, respectively.
[3" id="c-fr-0003]
The method of claim 1, wherein determining the second indicator comprises determining MK _t , where MK _t represents one or more local trends of the received drilling data, and wherein positive values represent positive trends and values negative represent negative trends.
[4" id="c-fr-0004]
4. The method of claim 1, wherein determining the
2017-IPM-101598-U1-EN third indicator includes the determination:
MAK _t = Σί ^w i, t, where
i - t - n + Xt - n + Z ........ t, and where n defines a time scale.
[5" id="c-fr-0005]
5. Method according to claim 4, in which the determination of the fourth trend indicator comprises the determination of DMAKt = MAKa, _t -MAKp, _t (a <β), where MAK _a , _t and MAKp, t represent MAK _t at time t with a window length of a and β, respectively.
[6" id="c-fr-0006]
6. Non-transient computer-readable storage medium storing one or more instructions which, when executed by the processor, cause the processor to: receive drilling data in real time;
determining one or more trend indicators based, at least in part, on drilling data received in real time, wherein determining the trend indicator (s) includes:
determining a first trend indicator, wherein the first trend indicator comprises an average of movement of the drilling data in real time;
determining a second trend indicator, wherein the second trend indicator includes a linear regression displacement slope;
determining a third trend indicator, wherein the third trend indicator includes an average trend; and determining a fourth trend indicator, wherein the fourth trend indicator comprises a difference in mean of the displacement slope;
determining a trend analysis based, at least in part, on the trend indicator (s); and triggering an alarm based, at least in part, on a threshold and trend analysis.
[7" id="c-fr-0007]
7. The computer-readable medium according to claim 6, in which the determination of the first indicator comprises the determination:
of DMA _t = MA _a , t - ΜΑβ, ι, (α <β), where MA _a , _t and MAp, _t are values
2017-IPM-101598-U1-FR means of displacement at time t with a window length of a and β, respectively.
[8" id="c-fr-0008]
The computer-readable medium of claim 6, wherein determining the second indicator includes determining MKt, where MKt represents one or more local trends in the received drilling data, and wherein positive values represent positive trends and negative values represent negative trends.
[9" id="c-fr-0009]
9. The computer-readable medium according to claim 6, in which the determination of the third indicator comprises the determination of:
MAK _t = Σί ^w i, t, where
i - t - n + 1, t - n + 2 ........ t, and where n defines a time scale.
[10" id="c-fr-0010]
The computer-readable medium of claim 9, wherein determining the fourth trend indicator includes determining DMAKt = MAKa, _t -ΜΑΚρ, ι (α <β), where MAKa, _t and MAKp, _t represent MAK _t at time t with a window length of a and β, respectively.
[11" id="c-fr-0011]
11. Information processing system comprising:
a memory ;
a processor coupled to the memory, in which the memory comprises one or more instructions executable by the processor for:
receive drilling data in real time;
determining one or more trend indicators based, at least in part, on drilling data received in real time, wherein determining the trend indicator (s) includes:
determining a first trend indicator, wherein the first trend indicator comprises an average of movement of the drilling data in real time;
determining a second trend indicator, wherein the second trend indicator includes a linear regression displacement slope;
determining a third trend indicator, wherein the third trend indicator includes an average trend; and
2017-IPM-101598-U1-FR determining a fourth trend indicator, wherein the fourth trend indicator comprises a difference in the mean of the displacement slope;
determining a trend analysis based, at least in part, on the trend indicator (s); and triggering an alarm based, at least in part, on a threshold and trend analysis.
[12" id="c-fr-0012]
12. Information processing system according to claim 11, in which the determination of the first indicator comprises the determination:
of DMA _t = MA _a , t - ΜΑβ, ι, (α <β), where MA _a , _t and MAp, _t are mean displacement values at time t with a window length of a and β, respectively.
[13" id="c-fr-0013]
The information processing system according to claim 11, wherein determining the second indicator comprises determining MKt, where MK _t represents one or more local trends of the received drilling data, and wherein positive values represent trends positive and negative values represent negative trends.
[14" id="c-fr-0014]
14. An information processing system according to claim 11, in which the determination of the third indicator comprises the determination:
MAK _t = ---- ï-i ^w i, t, WHERE
Wi.t i - t - n + ljt - n-FZ, ....... t, and where n defines a time scale.
[15" id="c-fr-0015]
15. The information processing system as claimed in claim 14, in which the determination of the fourth trend indicator comprises the determination of DMAKt = MAKa, _t -MAKp, _t (α <β), where MAKa, _t and MAKp, _t represent MAKt at time t with a window length of a and β, respectively.

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引用文献:

---

公开号 | 申请日 | 公开日 | 申请人 | 专利标题

---

WO2015126537A2|2014-02-18|2015-08-27|Chevron U.S.A. Inc.|Apparatus, system and methods for alerting of abnormal drilling conditions|

---

US6820702B2|2002-08-27|2004-11-23|Noble Drilling Services Inc.|Automated method and system for recognizing well control events|

---

CA2680942C|2008-09-30|2013-06-25|Precision Energy Services, Inc.|Downhole drilling vibration analysis|

---

US8965701B2|2010-10-20|2015-02-24|Baker Hughes Incorporated|System and method for automatic detection and analysis of borehole breakouts from images and the automatic generation of alerts|

---

US20130341093A1|2012-06-21|2013-12-26|Stuart Inglis Jardine|Drilling risk avoidance|WO2019125494A1|2017-12-22|2019-06-27|Landmark Graphics Corporation|Robust early kick detection using real time drilling data|

---

WO2021053545A1|2019-09-16|2021-03-25|Accucode AI|Machine learning control for automatic kick detection and blowout prevention|

法律状态:
2019-09-20| PLSC| Search report ready|Effective date: 20190920 |

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2019-09-26| PLFP| Fee payment|Year of fee payment: 2 |

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2021-02-26| RX| Complete rejection|Effective date: 20210115 |

优先权:

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申请号 | 申请日 | 专利标题

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US201762584464P| true| 2017-11-10|2017-11-10|

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US62584464|2017-11-10|

---

PCT/US2018/019227|WO2019094059A1|2017-11-10|2018-02-22|Automatic abnormal trend detection of real time drilling data for hazard avoidance|

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