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    • 专利摘要:
    Multivariate analysis can be used to correlate seismic attributes for underground formation with petrophysical properties of the subterranean formation and / or microseismic data associated with the treatment, creation, and / or extension of a network. fractures of said subterranean formation. For example, a process may involve modeling petrophysical properties of a subterranean formation, microseismic data associated with the processing of a complex fracture network in the subterranean formation, or a corresponding combination with a mathematical model based on measured data, microseismic data, conditioning and processing data, or a combination thereof, for producing a petrophysical property map, a microseismic data map, or a corresponding combination; and correlating a seismic attribute map with the petrophysical property map, the microseismic data map, or the corresponding combination using the mathematical model to produce at least one quantized correlation, wherein the seismic attribute map is a map modeled seismic attributes for the complex fracture network.
    公开号:FR3057963A1
    申请号:FR1758597
    申请日:2017-09-18
    公开日:2018-04-27
    发明作者:Ashwani Dev；Sridharan Vallabhaneni；Raquel Morag Velasco；Jeffrey Marc Yarus
    申请人:Landmark Graphics Corp；
    IPC主号:
    专利说明:

    ® FRENCH REPUBLIC
    NATIONAL INSTITUTE OF INDUSTRIAL PROPERTY
    COURBEVOIE © Publication number:
    (to be used only for reproduction orders)
    ©) National registration number
    057 963
    58597
    ©) Int Cl 8 . G 01 V1 / 34 (2017.01), G 01 V 1/30, 1/24, E 21 B 47/00, G 06 Q 50/02
    A1 PATENT APPLICATION
    ©) Date of filing: 18.09.17. © Applicant (s): LANDMARK GRAPHICS CORPORA- (30) Priority: 04.10.16 IB WOUS2016055285. TION— US. ©) Inventor (s): DEV ASHWANI, VALLABHANENI SRIDHARAN, VELASCO RAQUEL MORAG and YARUS (43) Date of public availability of the JEFFREY MARC. request: 04.27.18 Bulletin 18/17. (56) List of documents cited in the report preliminary research: The latter was not established on the date of publication of the request. (© References to other national documents ©) Holder (s): LANDMARK GRAPHICS CORPORA- related: TION. ©) Extension request (s): ©) Agent (s): GEVERS & ORES Société anonyme.
    MULTIVARIABLE ANALYSIS OF SEISMIC DATA, MICROSISMIC DATA, AND PETROPHYSICAL PROPERTIES IN FRACTURE MODELING.
    FR 3 057 963 - A1 paj A multivariable analysis can be used to correlate seismic attributes for an underground formation with petrophysical properties of the underground formation and / or microseismic data associated with the processing, creation, and / or the extension of a network of fractures in said underground formation. For example, a method may involve modeling petrophysical properties of an underground formation, microseismic data associated with the treatment of a network of complex fractures in the underground formation, or a corresponding combination with a mathematical model based on measured data, microseismic data, conditioning and processing data, or a corresponding combination, to produce a map of petrophysical properties, a map of microseismic data, or a corresponding combination; and correlating a map of seismic attributes with the map of petrophysical properties, the map of microseismic data or the corresponding combination using the mathematical model to produce at least one quantified correlation, in which the map of seismic attributes is a map modeled seismic attributes for the network of
    complex fractures.
    2015-IPM-099545-U1-FR i
    MULTIVARIABLE ANALYSIS OF SEISMIC DATA, MICROSISMIC DATA, AND PETROPHYSICAL PROPERTIES IN FRACTURE MODELING
    BACKGROUND OF THE INVENTION The present application relates to methods and systems for modeling fracture networks of underground formations.
    Oil and gas wells produce oil, gas, and / or derivative products from underground oil tanks. Oil reservoirs, like those containing oil and gas, generally include rock formations with finite, discontinuous, heterogeneous, anisotropic, non-elastic (DIANE) dimensions. These formations, in their natural state (before any fracturing treatment), generally include defects and natural fracture networks. As used here, the term "natural fracture network" refers to a grouping of fractures, connected or disconnected, in an underground formation before any fracturing treatment. Fractures in the natural fracture network can have different sizes, shapes, orientations and lithographic compositions. In addition, natural fractures can be open, closed, partially open, or partially filled. For example, a natural fracture in an underground formation may be partially filled with a different lithographic composition, such as calcite, dolomite, silica or the like, which can be identified in the seismic data.
    [0003] During a hydraulic fracturing treatment, fluids are pumped under high pressure into a rock formation through a borehole to cause or form fractures in the formations and increase the permeability and the production of the formation. Fracturing treatments (as well as production and other activities) can cause the development of different models of fractures in training. As used here, the term "complex fracture network" refers to the grouping of two natural fractures, connected or disconnected, in an underground formation. Complex fracture networks can include fractures that extend from drilling, along multiple azimuths, in multiple different planes and directions, along discontinuities in rock, and in multiple regions of a formation.
    2015-IPM-099545-U1-FR
    BRIEF DESCRIPTION OF THE FIGURES The following figures are included to illustrate certain aspects of the embodiments, and should not be considered as exclusive embodiments. The object disclosed admits considerable modifications, transformations, combinations, and equivalents of form and function, as will be understood by a specialist in the field benefiting from this disclosure.
    Figure 1 is a flow diagram of a method which uses a mathematical model to correlate petrophysical properties, seismic attributes and microseismic data according to at least some embodiments of the present disclosure.
    FIG. 2 illustrates a diagram of an example of a wired system which can use the principles of the present disclosure.
    FIG. 3 illustrates a diagram of an example of a system comprising a horizontal well which can use the principles of the present disclosure.
    Figure 4 is a correlation graph of the microseismic amplitude values and the probability of defect values at the location of the microseismic event, where the relationship was established as a first order linear regression with a line regression with a measured correlation coefficient (P, also referred to here as "correlation") covered.
    FIG. 5 is a correlation grid for the probability of defects, the petrophysical properties, and the microseismic data of the underground formation.
    Figure 6 is a correlation grid for the probability of faults from a seismic event, the seismic structural attributes and the petrophysical properties of the underground formation.
    DETAILED DESCRIPTION The present application relates to methods and systems which use a multivariable analysis when modeling fracture networks of underground formations. More specifically, multivariable analysis involves the correlation of seismic attributes (eg, probability of default, curvature attributes, seismic impedance, and the like) for an underground formation with
    2015-IPM-099545-U1-FR of the petrophysical properties of the underground formation and / or of the microseismic data associated with the treatment, creation, and / or extension of a network of fractures of the underground formation. These correlations can improve the differentiation between natural and induced fractures in a network of complex fractures by identifying the origin of microseismic events, which can improve the design of realization and the modeling of the reservoir.
    As used herein, the term "seismic attribute" refers to a chemical or physical property of the underground formation drawn from the seismic data. Examples of seismic attributes may include, but are not limited to, the probability of default, the curvature attributes, the seismic impedance, and the like. As used, the term "probability of faults" refers to a probability that a fault exists at a given location. In some cases, the probability of default can be reported as a volume of probability calculated using the default-oriented semblance algorithm described by Haie (GEOPHYSICS, VOL. 78, N ° 2 (MARCH-APRIL 2013), P. 033-043, Methods to compute fault images, extract fault surfaces, and estimate fault throws from 3D seismic images). In this example, the probability scale varies from 0 (no defect) to 1 (high probability of locating a defect in the volume). Other scales can be used.
    As used herein, the term "petrophysical property" refers to a chemical or physical property of a rock lithology of an underground formation comprising any chemical or physical interaction between the rock and a fluid contained in the interior. Examples of petrophysical properties may include, but are not limited to, sonic and shear impedances, mineralogy, porosity, permeability, relative permeability, capillarity, saturation, brittleness, matrix density, composition, training constraints, and the like, and any corresponding combinations. In some cases, the correlation between seismic attributes and a petrophysical property can be direct when a separate value for the petrophysical property is used in the correlation. As an alternative or in combination with a direct correlation, the correlation between the seismic attributes and a petrophysical property can be indirect when the measured data of the underground formation which relate to the petrophysical property are used in the correlation. For example, gamma ray measurements, nuclear magnetic resonance measurements, and sonic measurements of an underground formation relate to porosity. In direct correlation, one or more of the above measures can be used to calculate porosity, which is then correlated with an attribute
    2015-IPM-099545-U1-FR seismic. In an indirect correlation, one or more of the above measures can be correlated with the probability of default. Unless otherwise specified, the terms "correlation" and their derivatives, in relation to a correlation between seismic attributes and a petrophysical property include direct correlations, indirect correlations and a combination of direct and indirect correlations. In addition, unless otherwise specified, the terms "correlation between seismic attributes and a petrophysical property" and their derivatives include a correlation between seismic attributes and the petrophysical property, a correlation between this seismic attribute and the measured data of the underground formation which relate to the petrophysical property, and any corresponding combination.
    As used here, "the measured data which relate to the petrophysical property" refers to data directly measured by a sensor and / or data derived or otherwise calculated from data measured by a sensor, in which, whether directly measured or derived / calculated, the data relate to a petrophysical property of the formation. The measured data relating to the petrophysical property may come, for example, from nuclear magnetic resonance measurements, gamma ray measurements, photoelectric measurements, neutron measurements, geochemical measurements, resistivity measurements, acoustic measurements, drilling imagery measurements, mud logs, core measurements, geomechanical measurements, and the like, and any combination thereof, which can be collected with surface tools, measurement tools during drilling (MWD), recording tools during drilling (LWD), wire tools or corresponding combinations. More specifically, examples of measured data may include, but are not limited to, a p-wave sound impedance (which relates to in situ stresses of the formation), a s-wave shear impedance (which relates to in situ stresses of the formation), slowness of formation (taken from sonic measurements, relating to porosity), gamma rays (which relate to mineralogy), a positive or negative sonic curvature (which relates to structural changes relating to potential fracturing), a photoelectric factor (which relates to the properties and density of the rock matrix), the Young's modulus and the Poisson ratio (which relate to the elastic properties of the formation and obtained using sonic speed, shear speed and density; they also concern the training constraint) and the like, and any corresponding combination.
    2015-IPM-099545-U1-FR [0015] Hydraulic fracturing treatments (also called “fracturing treatments”) are generally carried out to create fractures in the underground formation, and thus to improve the productivity of hydrocarbons in the formation underground. The pressures generated by the fracturing treatment can induce seismic events of low amplitude or low energy in the underground formation, also known as microseismic events. Other treatments at a fracture network can cause microseismic events which can be monitored to acquire microseismic data for analysis. For example, stimulation operations such as injections and gravity drainage treatments assisted by steam applied to a network of fractures can cause microseismic events.
    As used herein, the term "microseismic event" refers to a micro-earthquake that occurs following a change in the distribution of stresses in an underground formation, for example, in response to treatments hydraulic fracturing or other treatments to the fracture network. Microseismic events can arise from, for example, rock slides, rock movements, rock fractures or other events in the underground formation.
    The seismic waves produced by microseismic events are detected by sensors, and then the microseismic waveforms detected by the sensors can be processed and analyzed to determine the size and location in time and space. microseismic events and the various attributes associated with microseismic data. Sensors can be placed in a plurality of locations relative to the borehole in which the treatment is carried out, for example, in a well (e.g., an observation well, an injection well, a treatment well or a well production) which is close enough to the fracture network to measure microseismic data, on the earth's surface, buried at a shallow depth (less than about 500 m) and the like and any corresponding combination. Typically, sensors measure microseismic data from one or more of the above locations before, during and after processing.
    Examples of sensors used to detect microseismic events can include, but are not limited to, geophones, accelerometers, acoustic distributed fiber optic (DAS) sensors, and the like, and any corresponding combinations. Usually several sensors
    2015-IPM-099545-U1-FR (for example, two or more of the same type of sensor or a combination of two or more types of sensor) can be used in a row of sensors.
    Examples of microseismic data may include, but are not limited to, the amplitude of microseismic events, the relative time of microseismic events, the location in space and time of microseismic events, the source mechanism of microseismic events , the amplitude ratios p to wave s, the signal-noise ratios, the seismic moment, the amount of shear associated with microseismic events, the tensors of microseismic moments, the confidence value of microseismic events, the density of microseismic events, the geometry of estimated induced fractures of microseismic events, and the like and any corresponding combinations.
    The microseismic data can be collected in association with the processing, creation and / or extension of a network of fractures. The microseismic data can be entered before the start of the treatment, during the treatment, after the end of the treatment or any corresponding combination.
    The systems and methods of the present application correlate seismic attributes for an underground formation with one or more petrophysical properties of the underground formation and / or microseismic data associated with the treatment of a network of complex fractures in a formation underground to identify natural and induced fractures in the complex fracture network.
    FIG. 1 is a flow diagram of a method which uses a mathematical model 100 to determine a correlation 122 between seismic attributes 104 and petrophysical properties 106, 110 of the underground formation and / or maps of microseismic data 118, associated with treatment of a network of complex fractures according to at least some of the embodiments of the present disclosure.
    More specifically, as illustrated, measured data such as logs from well 108 and geochemical and basic data 112 can be processed deterministically (eg, using a Kriging process) or stochastically (by free, using conditional simulations) to produce maps of petrophysical properties 106,110, respectively.
    2015-IPM-099545-U1-FR As used here, the term "map" refers to a characteristic and / or a given property (s) represented in the form of a grid matrix in 3 dimensions of the underground formation (also known as a geocellular grid), a 2-dimensional palette representing the properties of the formation on a 2-dimensional plane, a 1-dimensional palette representing the underground formation and the like. In a 1-dimensional palette, the training data points (for example, data points in the geocellular grid) are converted to a mathematical matrix having matrix identification values corresponding to each of the data points in the geocellular grid.
    Maps of petrophysical property 106, 110 may be of a specific petrophysical property for direct correlations with the map of seismic attributes 104 or of measurements / data relating to the petrophysical property for indirect correlations as described above.
    In addition, microseismic data 120 can be processed deterministically or stochastically to produce microseismic data cards 118.
    In some cases, mathematical analyzes and additional manipulations may be performed, before or during modeling, which may include, but are not limited to, the normalization of collected data (for example, log data from well 108 , geochemical and basic data 112, seismic data 102, and microseismic data 120), calibration of the mathematical mode 100 to any data detected remotely (for example, well 108 log data, geochemical and basic 112, seismic data 102, and microseismic data 120), and the like, and any corresponding combination.
    The measured data (for example the log data from well 108 and the geochemical and basic data 112) can come from one or more measurements of the underground formation, for example, nuclear magnetic resonance measurements, measurements by gamma rays, photoelectric measurements, neutron measurements, geochemical measurements, resistivity measurements, acoustic measurements, drilling imagery measurements, mud logs, geomechanical measurements, and the like, and any combination thereof , which can be collected with MWD tools, LWD tools, wire tools or corresponding combinations. In some cases,
    2015-IPM-099545-U1-FR measured data 108,112,116 can be collected in association with the treatment of a network of complex fractures.
    The petrophysical properties maps 106, 110 and the microseismic data maps 118 can be a model of one or more properties or characterizations of the underground formation which relate to the fractures inside it, including those described here relatively to the seismic attributes map 104.
    In addition, the conditioning and processing data 116 (for example, pump rates, flow rates, drilling pressures, and the like) can be collected.
    The mathematical model 100 can then apply a multivariable analysis of the map of seismic attributes 104, maps of petrophysical properties 106,110, conditioning and processing data 116, and maps of microseismic data 118 to quantify the correlation 122 between the seismic attribute map 104 and each of the petrophysical property maps 106,110, conditioning and processing data 116 and microseismic data maps 118. Multivariable analysis can involve simple linear or non-linear regression to determine the coefficient of correlation, coefficient of determination, or any other statistical method of validity of the adjustment.
    In some cases, the correlation scale (P) can vary from 0 (no correlation) to 1 (high correlation). Other scales can be used. In some cases where the correlation 122 is low (e.g. P <0.5), the seismic data 102, the measured data 108,112, the conditioning and processing data 116, and the microseismic data 120 can be reviewed to determine whether potentially false data is present and delete the false data.
    In certain cases where the correlation 122 is good (for example, P> 0.7 or P 2 > 0.5), the petrophysical property maps 106, 110, the conditioning and processing data 116, and the maps of microseismic data 118 having the correct correlation 122 with the seismic attribute map 104 can be used as a basis for further analysis and / or modeling of the underground formation (for example, variogram modeling 126 and reservoir modeling 128).
    For example, with variogram modeling 126, petrophysical property maps 106,110, conditioning data and
    2015-IPM-099545-U1-EN 116, and the seismic data cards 118 having the correct correlation 122 with the seismic attribute map 104 can be used as a basis for identifying natural and induced fractures in the network of complex fractures . By way of a nonlimiting example, by superimposing the microseismic data cards 118 on the seismic attribute map 104, it is possible to identify microseismic events occurring along probable faults such as the reactivation of natural fractures and d '' identify other microseismic events as being along induced fractures. In addition, comparison with petrophysical properties such as brittleness can be used later to identify fractures induced along brittle parts of the formation.
    In another example, with variogram modeling 128, petrophysical property maps 106,110, conditioning and processing data 116, and microseismic data cards 118 having the correct correlation 122 with the map of seismic attributes 104 can be used as a basis for identifying natural and induced fractures in the complex fracture network. For example, the location for drilling a new well can be chosen to cut a highly connected part of the complex fracture network.
    Similarly, the methods described here can be used to assess the effectiveness of the treatment. Then, the conditioning and processing data 116 having the correct correlation 122 with the seismic attribute map 104 can be used for the design of conditioning and future treatments of adjacent wells.
    In addition, the petrophysical property maps 106,110, the conditioning and processing data 116 and the microseismic data cards 118 having the good correlation 122 with the seismic attribute map 104 can be used to (1) improve the modeling or forecasting reservoir production, (2) improving fracture modeling (for example, to model the degree and position of the fracture cluster), and (3) informing drilling decisions during filling in a part of the underground formation of interest.
    The analyzes and methods described here can be implemented by a set of instructions which allow a processor to execute the mathematical model 100. In some cases, the processor and the set of instructions can also be used. for successive analyzes of
    2015-IPM-099545-U1-EN ίο petrophysical property maps 106,110, conditioning and processing data 116, and microseismic data maps 118 having the correct correlation 122 with the seismic attribute map 104.
    The processor can be part of the computer hardware used to implement the various illustrative blocks, elements, components, methods and algorithms described here. The processor can be configured to execute one or more sequences of instructions, programming requests or codes stored on a computer-readable, non-transient medium. The processor can be, for example, a universal microprocessor, a microcontroller, a digital signal processor, an integrated circuit with specific application, a programmable integrated circuit, a programmable logic device, a controller, a state machine, a logic at door, discrete hardware components, an artificial neural network, or any suitable entity of the same type capable of performing calculations or other manipulation of data. In some embodiments, the hardware may further include such things as, for example, memory (e.g., random access memory (RAM), flash memory, read only memory (ROM), programmable read only memory ( PROM), reprogrammable read only memory (EPROM), registers, hard disks, removable disks, CD-ROMs, DVDs, or any other suitable device or storage medium of the same type.
    The executable sequences described in this document can be implemented with one or more code sequences contained in a memory. In some embodiments, such code can be read into memory from another machine-readable medium. The execution of the sequences of instructions contained in the memory can cause a processor to carry out the process steps described in this document. One or more processors in a multiprocessing arrangement can also be used to execute the sequences of instructions in memory. In addition, a wired circuit can be used in place of or in combination with software instructions to implement various embodiments described in this document. Therefore, the present embodiments are not limited to any specific combination of hardware and / or software.
    As used in this document, a machine-readable medium refers to any medium which directly or indirectly provides instructions to the processor for execution purposes. Readable media
    2015-IPM-099545-U1-FR by a machine can take many forms such as, for example a non-volatile support, a volatile support and a transmission support. A non-volatile medium may include, for example, optical and magnetic disks. A volatile medium can include, for example, dynamic memory. A transmission medium can include, for example, coaxial cables, metal wire, optical fiber, and metal wires that form a bus. Typical forms of machine-readable media may include, for example, floppy disks, flexible disks, hard disks, magnetic tapes, other types of magnetic media, CD-ROMs, DVDs, other media similar optical devices, punch cards, paper strips and similar physical media with patterned holes, RAM, ROM, PROM, EPROM, and flash EPROM.
    FIG. 2 illustrates a diagram of an example of a system 200 which can use the principles of the present disclosure, according to one or more embodiments. QAt different times before, during or after one or more treatments of the complex fracture network, seismic data 102, measured data 108,112, and microseismic data 120 in FIG. 1 can be collected for an underground formation 210. In certain cases, the drilling tools extending into a borehole 204 (eg, a working column for perforating the formation 210) can be removed from a borehole 204 to perform measurement / recording operations. As illustrated, the wired system 200 can include one or more wired tools 202 which can be suspended in the borehole 204 by a cable 212. The wired tools 202 can be connected in communication with the cable 212. The cable 212 can include conductors for transport electricity to the wired tools 202 and also facilitate communication between the surface and the wired tools 202. A recording installation 206, indicated in FIG. 2 in the form of a truck, can collect measurements coming from the wired tools 202 and can include calculation systems 208 for controlling, processing, storing and / or viewing the measurements collected by the wired tools 202. The calculation systems 208 can be connected in communication with the wired tools 202 by means of the cable 212. In some cases, the mathematical model 100 of FIG. 1 can be applied using the calculation systems 208. As a variant, the measurements collected s by the wired tools 202 can be transmitted (wired or wireless) or physically delivered to off-site calculation systems when the mathematical model 100 of FIG. 1 can be applied.
    2015-IPM-099545-U1-FR [0043] FIG. 3 illustrates a diagram of an exemplary system 300 which can use the principles of the present disclosure, according to one or more embodiments. In the illustrated system 300, a borehole 302 with a vertical section 304 and a horizontal section 306 is aligned with the formwork 308 cemented therein to support the borehole 302. Alternatively, part of the borehole 302 may have no formwork , what is called an "open survey". For example, the formwork 308 can extend from a surface location, such as the earth's surface, or from an intermediate point between the surface location and the formation 310. In the illustrated system 300, a fiber optic cable 312 extends along the formwork 308.
    One or more drilling tools 320, for example, a packaging unit or a perforating gun, can be used to prepare the horizontal section 306 for the successive extraction of hydrocarbons from the surrounding formation 310. For example, a packaging assembly may include a plurality of conditioners which isolate the different production intervals in horizontal section 306. In some cases, a fluid (eg, stimulation fluid, processing fluid, acidifying fluid, compliance fluid or any combination thereof) can be injected into the borehole 302 or the surrounding formation 310 via the drilling tools 320.
    The system 300 also includes an observation well 322 having a plurality of geophones 324 placed inside to measure the seismic and / or microseismic data. In addition, the system 300 includes a plurality of surface geophones 326 for measuring seismic and / or microseismic data.
    The embodiments of the present application include, but are not limited to, embodiment A, embodiment B and embodiment C.
    The embodiment A is a method comprising: the modeling of an element chosen from the group consisting of petrophysical properties of an underground formation, microseismic data associated with the treatment of a network of complex fractures in the underground formation , and a corresponding combination with the mathematical model based on an element selected from the group consisting of measured data, microseismic data, conditioning and processing data and a corresponding combination, to produce an element chosen from the group consisting of a map of petrophysical properties, a map of data
    2015-IPM-099545-U1-FR microseismic, and a corresponding combination; and the correlation of a map of seismic attributes with an element selected from the group consisting of the map of petrophysical properties, the map of microseismic data and the corresponding combination using the mathematical model to produce at least one quantified correlation, in which the seismic attribute map is a seismic attribute map modeled for the network of complex fractures.
    Embodiment B is a system comprising: a drilling tool placed along a borehole extending into an underground formation; a non-transient computer-readable medium coupled to the drilling tool to receive measured data of the underground formation from the drilling tool and coded with instructions which, when executed, cause the system to execute the process of Embodiment A.
    Embodiment C is a computer-readable, non-transient medium, coded with instructions which, when executed, cause a system to implement the method of Embodiment A.
    Embodiments A, B and C may optionally include one or more of the following: Element 1: the method further comprising: modeling the seismic attributes for the network of complex fractures in the underground formation with the mathematical model based on seismic data from the underground formation to produce the map of seismic attributes; Element 2: the method further comprising: determining a location for drilling a borehole in the underground formation so as to cut the network of complex fractures on the basis of said at least one quantified correlation; Element 3: the method further comprising: identifying natural fractures and induced fractures in the complex fracture network; Element 4: in which the measured data of the underground formation are selected from the group consisting of: seismic data, gravity data, magnetic data, magnetotelluric data, and any corresponding combination; Element 5: the method further comprising: updating a production model of the reservoir on the basis of said at least one quantified correlation; Element 6: the method further comprising: updating a fracture model on the basis of said at least one quantified correlation; Element 7: the method further comprising: performing a drilling processing operation with at least one parameter based on said at least one quantified correlation; and Element 8: drilling or extending a borehole
    2015-IPM-099545-U1-FR so that the hole cuts the network of complex fractures based on at least one quantified correlation.
    Examples of combinations may include, but are not limited to, Element 1 combined with one or more of Elements 2-8; Element 7 and / or 8 in combination with one or more of Elements 1-6; Element 3 in combination with Element 2; Element 3 in combination with one or more of Elements 4-8 and possibly in subsequent combination with Element 2; and the like.
    Unless otherwise indicated, it should be understood that all the numbers expressing quantities of ingredients, properties such as molecular weight, reaction conditions, and so on used in the present specification and the associated claims are modified in all cases by the term "approximately". Consequently, unless otherwise indicated, the numerical parameters indicated in the following specification and the appended claims are approximations which may vary depending on the desired properties which it is desired to obtain by the embodiments of the present invention. At the very least, and not as an attempt to limit the application of the doctrine of equivalents to the scope of the claim, each numerical parameter must at least be interpreted according to the number of significant digits indicated and by applying ordinary techniques d 'round.
    One or more illustrative embodiments incorporating the embodiments of the invention disclosed in this document are presented in this document. All the functionalities of a physical implementation are not described or presented in the present request for reasons of clarity. It is understood that during the development of a physical embodiment incorporating the embodiments of the present invention, many specific decisions of an implementation can be taken to achieve the developer's objective, such as compliance with the associated constraints to a system, associated with a company, associated with a government, among others, which vary according to the implementation and from time to time. Although the efforts of a developer may take time, such efforts would nevertheless be a routine undertaking for those skilled in the art and benefiting from this disclosure.
    Although compositions and methods are described in this document in terms of "comprising" various components or
    2015-IPM-099545-U1-EN steps, compositions and methods can also "consist essentially of" or "consist of" the various components and stages.
    In order to better understand the embodiments of the present invention, the following examples of preferred or representative embodiments are given. It should not be construed in any way as the following examples limit or define the scope of the invention.
    EXAMPLES The measured data which were used included well recording data, seismic data (negative sonic curvature and positive sonic curvature) and microseismic data (amplitude of microseismic events) for an underground formation. Using the seismic data, a volume of probability of default was created. A mathematical model produced a 3D grid of probability of training failure. We describe below in more detail some of the data analyzes and correlations performed by the mathematical model.
    The mathematical model produced a 3D grid of each of the types of data measured and then quantified the correlation of each property on the 3D grid with the default probability map by means of a correlation graph. FIG. 4 is a correlation graph of the map of the microseismic amplitude and the probability of default values on the 3D grid where the first order correlation is superimposed, which quantifies the correlation as being 0.27. Figure 5 provides the correlations between the different maps: probability of default: microseismic amplitude 0.270, probability of default: negative curvature 0.371, probability of default: positive curvature: 0.450. Consequently, the microseismic data and / or the associated maps can be revised to identify and erase the false data points.
    In another example, data was measured for an underground formation, including well log data and measured data (p-wave sound impedance, s-wave shear impedance, sonic log (slowness a sound wave in a formation), gamma ray journal, negative curvatures, positive curvatures and photoelectric factor). Similarly, the 3D grid of the probability of default was produced from the seismic data and correlated with 3D grids corresponding to each of the measured data. In addition, the fragility and the simulated fragility (petrophysical properties) were modeled and mapped on the grid in 3D. Figure 6
    2015-IPM-099545-U1-FR shows the correlations between the different grids: probability of default: sound wave impedance p 0.911, probability of default: shear wave impedance s: -0.565, probability of default: fragility 0.326, probability default: simulated fragility 0.474, probability of default: sonic log -0.376, probability of default: gamma ray log -0.455, probability of default: negative bends 0.282, probability of default: positive bends 0.679, and probability of default: photoelectric factor 0.465. In this example, the probability of default presents the best correlation with the sound impedance at p-wave, the shear impedance at s-wave, and the positive sonic curvatures, and there is also a considerable correlation between the probability of default and the brittleness training.
    Therefore, the present invention is well suited to achieve the ends and advantages mentioned as well as those which are inherent here. The particular embodiments disclosed above are illustrative only, since the present invention can be modified and practiced in different but equivalent ways evident to a specialist in the field and who benefits from the present teachings. In addition, there is no limitation to the construction or design details described herein, other than those described in the claims below. It is therefore obvious that the particular illustrative embodiments disclosed above can be altered, combined, or modified and all variations are considered within the scope and spirit of the present invention. The invention disclosed by way of illustration in this document can be practiced appropriately in the absence of any element which is not specifically disclosed in this document and / or any optional element disclosed in this document. Although compositions and methods are described in terms of "comprising", "containing", or "including" various components or steps, the compositions and methods may also "consist essentially of" or "consist of" various components and stages . All of the numbers and ranges disclosed above may vary by a certain amount. Whenever a numeric range with a lower limit and an upper limit is disclosed, any number and any included range falling within the range are specifically disclosed. In particular, each range of values (of the form, "from about a to about b" or, equivalently, "from approximately a to b" or, equivalently, "from approximately ab") disclosed in this document is to be considered as indicating any numbers and ranges included within the widest range of values. In addition, the terms in the claims have their clear and ordinary meaning, unless mentioned
    2015-IPM-099545-U1-FR contrary explicit and clear defined by the patent holder. Furthermore, the indefinite articles "a" or "an", as used in the claims, mean here one or more of the element which is introduced.
    2015-IPM-099545-U1-FR
    权利要求:
    Claims (15)
    [1" id="c-fr-0001]
    1. Process comprising:
    the modeling of an element chosen from the group consisting of petrophysical properties of an underground formation, microseismic data associated with the treatment of a complex network of fractures in the underground formation, and one of their combinations with a mathematical model based on an element chosen from the group consisting of measured data, microseismic data, completion and processing data, and one of their combinations to produce an element chosen from the group consisting of a map of petrophysical properties , a microseismic data card and one of their combinations; and correlating a seismic attribute map with an element selected from the group consisting of the petrophysical properties map, the microseismic data map, and one of their combinations using the mathematical model to produce at least a quantified correlation, in which the seismic attribute map is a modeled seismic attribute for the complex fracture network.
    [2" id="c-fr-0002]
    2. Method according to claim 1, further comprising:
    modeling of the seismic attribute for the complex fracture network within the underground formation with the mathematical model based on seismic data from the underground formation to produce the map of seismic attributes.
    [3" id="c-fr-0003]
    3. Method according to claim 1, further comprising:
    determining a location to drill a wellbore in the underground formation so as to intercept the complex fracture network based on the at least one quantified correlation.
    [4" id="c-fr-0004]
    The method of claim 1, further comprising: identifying natural fractures and induced fractures within the complex fracture network.
    [5" id="c-fr-0005]
    5. Method according to claim 1, in which the measured data of the underground formation are chosen from the group consisting of:
    2015-IPM-099545-U1-FR seismic data, gravimetric data, magnetic data, magnetotelluric data, and one of their combinations.
    [6" id="c-fr-0006]
    6. Method according to claim 1, further comprising:
    updating at least one of a reservoir production model and a fracture model based on the at least one quantified correlation.
    [7" id="c-fr-0007]
    7. The method according to claim 1, further comprising:
    performing a wellbore processing operation with at least one parameter based on the at least one quantified correlation.
    [8" id="c-fr-0008]
    8. The method of claim 1, further comprising:
    drilling or extending a wellbore so that the wellbore intercepts the complex fracture network based on the at least one quantified correlation.
    [9" id="c-fr-0009]
    9. System comprising:
    a wellbore tool placed along a wellbore and extending into an underground formation;
    a non-transient computer-readable medium coupled to the wellbore tool to receive measured underground formation data from the wellbore tool and encoded with instructions which, when executed, bring the system to perform operations including:
    modeling of an element chosen from the group consisting of petrophysical properties of an underground formation, microseismic data associated with the treatment of a complex network of fractures in the underground formation, and one of their combinations with measured data , microseismic data, completion and processing data, respectively to produce an element selected from the group consisting of a petrophysical properties map, a microseismic data map and one of their combinations, respectively; and the correlation of a seismic attribute map with an element chosen from the group consisting of the petrophysical properties map, the microseismic data map, and one of their combinations using the model
    2015-IPM-099545-U1-FR mathematical to produce at least one quantified correlation, in which the seismic attribute map is a seismic attribute modeled for the complex fracture network.
    [10" id="c-fr-0010]
    10. The system of claim 9, wherein the instructions which, when executed, cause the system to perform operations which further include:
    modeling of the seismic attribute for the complex fracture network within the underground formation with the mathematical model based on seismic data from the underground formation to produce the map of seismic attributes.
    [11" id="c-fr-0011]
    11. The system of claim 9, wherein the instructions which, when executed, cause the system to perform operations which further include:
    determining a location to drill a wellbore in the underground formation so as to intercept the complex fracture network based on the at least one quantified correlation.
    [12" id="c-fr-0012]
    The system of claim 9, wherein the instructions which, when executed, cause the system to perform operations which further include:
    the identification of natural fractures and induced fractures within the complex fracture network.
    [13" id="c-fr-0013]
    13. The system of claim 9, wherein the measured data of the underground formation are selected from the group consisting of: seismic data, gravity data, magnetic data, magnetotelluric data, and one of their combinations.
    [14" id="c-fr-0014]
    14. The system of claim 9, wherein the instructions which, when executed, cause the system to perform operations which further include:
    updating a reservoir production model based on the at least one quantified correlation.
    2015-IPM-099545-U1-FR
    [15" id="c-fr-0015]
    15. The system of claim 9, wherein the instructions which, when executed, cause the system to perform operations which further include:
    updating a fracture model based on the at least 5 quantified correlation.
    2015-IPM-099545-U1-FR
    1/6
    2015-IPM-099545-U1-FR
    2/6
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    US11099289B2|2021-08-24|
    GB2569899A|2019-07-03|
    US20190235106A1|2019-08-01|
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    优先权:
    申请号 | 申请日 | 专利标题
    PCT/US2016/055285|WO2018067119A1|2016-10-04|2016-10-04|Multivariate analysis of seismic data, microseismic data, and petrophysical properties in fracture modeling|
    IBPCT/US2016/055285|2016-10-04|
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