法国专利FR3069929A1 PREDICTION IN FRONT OF TREPAN USING VERTICAL SEISMIC PROFILE AND GLOBAL INVERSION

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专利摘要:
Embodiments of the technology of the invention make it possible to predict the seismic impedance. The technology of the invention generates a stack of corridors based on vertical seismic profile (VSP) data of a wellbore in a subterranean formation. The technology of the invention generates an initial estimate of a velocity model for the subsurface formation below the wellbore. The technology of the invention generates a density model for subsurface formation below the wellbore based on information from neighboring wells. The technology of the invention reverses, on the basis of a global inversion algorithm and the initial estimation of the velocity model, the stack of corridors generated to determine a set of velocity models. The technology of the invention generates impedance models in a depth domain based on the generated density model and the set of velocity models. In addition, the technology of the invention stores the generated impedance patterns.
公开号:FR3069929A1
申请号:FR1854948
申请日:2018-06-07
公开日:2019-02-08
发明作者:Amit Padhi；Mark Elliott Willis
申请人:Halliburton Energy Services Inc；
IPC主号:

专利说明:

PREDICTION FORWARD OF THE BIT USING VERTICAL SEISMIC PROFILE AND GLOBAL INVERSION DATA
TECHNICAL AREA
The present description generally relates to the prediction of seismic impedances of underground rock formations.
BACKGROUND
Vertical seismic profile analysis (VSP) is a technique used to perform geophysical studies of underground features. For example, VSP analysis can be used to image the earth's subsoil near a wellbore while drilling or operating a well. In one example, one or more seismic energy sources are located on the surface and one or more seismic detectors are located inside a wellbore. A seismic profile based on information about the subsoil can be determined based on the detection of the reflected seismic energy that comes from the seismic energy sources on the surface.
BRIEF DESCRIPTION OF THE DRAWINGS
FIG. 1 illustrates a flow diagram of an example method for using a vertical seismic profile analysis with zero offset to predict seismic impedances according to certain implementations.
FIG. 2 illustrates a curve of an example of comparison of a stack of terrain corridors with a result of final inversion of the best model synthesis according to certain implementations.
FIG. 3 illustrates a curve of an example of an impedance model in a depth obtained after the global inversion according to certain implementations.
FIG. 4 illustrates a curve of an example of multiple embodiments of a speed model obtained by collecting all the inversion models which have a correlation value greater than a threshold chosen according to certain implementations,
FIG. 5 illustrates an example of a drilling assembly for the implementation of the methods described here according to certain implementations.
FIG. 6 illustrates a wired system suitable for the implementation of the methods described here according to certain implementations.
FIG. 7 illustrates a schematic diagram of a set of general components of an example of a computing device according to certain implementations.
FIG. 8 illustrates a schematic diagram of an example of an environment for the implementation of aspects according to certain implementations.
In one or more implementations, not all of the components shown in each figure are required, and one or more implementations may include additional components not shown in a figure. Variants in the arrangement and type of components can be made without departing from the scope of the description of the invention. Additional components, different components or fewer components can be used in the description of the invention.
DETAILED DESCRIPTION
The detailed description presented below is intended to be a description of various implementations and is not intended to represent the only implementations in which the technology of the invention can be practiced. As will be understood by a person skilled in the art, the described implementations can be modified in different ways, without going beyond the scope of this description. Consequently, the drawings and the description should be considered as illustrative in nature and not restrictive.
Surface seismic data combined with scattered well logging data generally produces a depth map of the subsurface which is only an approximate representation of the ground truth. Accurate prediction of rock formation depths from these types of data depends on the accuracy of the velocity model obtained from the analysis of seismic data and well logging. The analysis of seismic velocity can be fraught with pitfalls due to imperfect assumptions on the subsoil and also use approximations to facilitate calculation with large data sets. In addition, the available surface seismic data may have a sufficiently low resolution so that certain high impedance contrast formations may not be interpretable. In such circumstances, additional tools and techniques may be required for more accurate prediction of rock formations ahead of the drill bit (for example, a tool useful for crushing or cutting rock in a given drilling rig ).
In some cases, zero offset vertical seismic vertical profile (VSP) lane stacks can be inverted to predict impedances ahead of the drill bit in the depth range. Such inversion techniques can use an initial estimate of the smooth bottom velocity model generally obtained from the analysis of the surface seismic migration speed and / or the logs from neighboring wells.
In addition, a density model obtained using geomechanical considerations can be used to generate an initial smooth bottom impedance model. A local inversion based on the gradient is then performed to generate an updated impedance model. After dividing the updated impedance model by the density model, an updated speed model is generated. This updated velocity model is further used to convert the updated impedance model to the depth domain when the actual impedance model is obtained in the time domain. Another way to update an initial background impedance model is to integrate the lane stack, and then add the built-in lane stack to the background impedance model. The final impedance model is again converted to the depth domain using the same techniques as those mentioned above.
Such techniques which use local inversion are however strongly dependent on the initial background model and therefore have a greater probability of providing a prediction with greater imprecision. In addition, such techniques may or may not be capable of providing depth error estimates depending on the formulation of the inversion problem. For example, if the local inversion is a Bayesian formulation, an estimate of the uncertainty can then be provided. However, in the second case described above where an integrated stack of lanes is added to the background model, no uncertainty can be calculated. To overcome such problems, the technology of the invention as described herein provides implementations for prediction based on the overall inversion ahead of the drill bit. A global inversion scheme as described in the implementations is generally significantly less dependent on the initial background model than techniques which use local inversion, thus making the implementations of the invention more insensitive to inaccurate estimates. in the initial background model.
In a zero-shift VSP study, below a depth in which a given well has been drilled, seismic reflections are collected from the receivers in a zero-shift configuration. A stacked plot called a stack of lanes can be produced from these seismic reflections, and the stack of lanes can be reversed to estimate the seismic impedances below the well.
The following description describes in more detail an example of a flow diagram for a method which predicts formations of high or low seismic impedance, and examples of diagrams illustrating a comparison of stacking of field corridors with a final inversion result of the best model synthesis, a depth impedance model obtained after the global inversion and several realizations of the speed model obtained by collecting all the inversion models.
FIG. 1 conceptually illustrates a flow diagram of an exemplary method 100 for the prediction of petrophysical properties and the classification of facies. Although this figure, as well as other process illustrations contained in this description, may describe functional steps in a particular sequence, the processes are not necessarily limited to the particular order or to the illustrated steps. The different steps shown in this figure or in others can be modified, rearranged, executed in parallel or adapted in various ways. In addition, it should be understood that certain steps or sequences of steps can be added to or omitted from the process, without departing from the scope of the various implementations. The method 100 can be implemented by one or more computer devices or systems in certain implementations, such as the processor 538 described in FIG. 5 and / or the computer device 700 described in FIG. 7.
At block 102, a stack of corridors (for example, a stack of field corridors) is generated using zero-shift VSP data for a wellbore in an underground formation. In one example, a seismic source (for example, a device that generates controlled seismic energy and directs this energy into an underground formation) is activated at or near the head of a wellbore of a well and a receiver (or more receivers as described below) record the signal at fixed depths in the wellbore. Multiple planes can be recorded (and stacked) at the same depth interval to determine the zero offset VSP data. Although zero shift VSP data is described herein, the technology of the invention in at least one implementation can also acquire and use other VSP data such as shifted VSP data, VSP data of walkaway type, and the like, which can be transformed and / or pretreated to carry out the other steps of method 100 described below. In at least one implementation, the zero shift VSP uses multiple receivers to collect data. The data collected from these multiple receivers is processed and stacked together to ultimately generate a stack of lanes, which is a single path.
In block 104, a source wavelet is estimated using statistical information. Such statistical information can be provided by an external source (for example, another software application) which can apply statistical techniques to seismic surveys and / or well logs. It is appreciated, however, that any suitable source wavelet can be used depending on the implementations of the technology of the invention.
In block 106, a scale factor is determined for the comparison between the syntheses (described in more detail below) and the stacking of lanes determined. Such a scale factor is obtained from the ratio between the quadratic mean amplitudes (RMS) from the synthesis (calculated using well log data collected in the already drilled section of the well and statistique statistical wavelet ) and the stacking of land corridors for a crest or trough identified on the two tracks. This scale factor can be multiplied by the stacking of field corridors to make the amplitudes comparable to the syntheses produced by the direct modeling methodology which is integrated into the inversion scheme. At block 108, an overburden model to a well bottom depth is generated based on well information. Well information, for example, may include information from well logs for the compression wave speed (V _p ) and / or density. The overburden model velocities and densities can be kept fixed during the execution of the inversion algorithm. In at least one example, these overburden model speeds and densities are used to calculate summary data to compare to the stack of terrain corridors because the overburden model speeds and densities can control the timeline. events (for example, dips and peaks) on the plot of summary data.
In block 110, an initial estimate is determined for a velocity model in the underground formation below the wellbore (for example, at depths less than a depth from the bottom of the wellbore) based on one or more from several sources of information. For example, information from other nearby wells can be used to determine the initial estimate of the velocity model. In addition, the initial velocity model can be based on information from a seismic surface migration velocity analysis.
At block 112, a density model in the underground formation below the wellbore is generated. The density model can be generated based on information from neighboring wells and / or geomechanical considerations. In one implementation, the density can be fixed or updated as a function of speed using the physical relationships of the rock based on, for example, the Gardner equation (for example, an empirical equation relating the speed of the P waves to the density). If the density is kept fixed, an a priori estimate can be made on the basis of geomechanical considerations.
At block 114, the stack of lanes is reversed on the basis of a global inversion algorithm to generate several speed models. The determined scale factor can be applied to the stacking of lanes in at least one implementation in block 114. An example of a global inversion algorithm used in block 114 can be a scalable algorithm. An example of an evolutionary algorithm can be a differential evolution algorithm, which can be used in block 114 since such an algorithm is highly parallelizable on one or more computer devices (for example, resulting in potentially faster processing times), comprising, for example, the processor 538 described in Figure 5 and / or the computing device 700 described in Figure 7. In addition, a scalable algorithm can be implemented more easily (for example, with less complexity) to be run on such computer devices. It is appreciated that any suitable evolutionary algorithm can be used, including any optimization algorithm based on an appropriate population such as a genetic algorithm, an optimization of the particle swarm or an optimization of ant colonies, etc.
In the implementation of the global inversion process, an objective function is maximized or minimized. For example, an objective function may attempt to maximize a cross-correlation between the stack of lanes and the summary data (for example, synthetic seismograms) that are produced by a velocity model. In one example, the global inversion algorithm works with a population of models to converge to models that generate syntheses that correspond substantially to the actual field data (for example, the stack of lanes generated). Since the evolutionary algorithm determines several models that correspond to the stacking of lanes with a high correlation, uncertainty estimates can be made using the series of "good" models obtained.
In one example, syntheses (for example, synthetic seismograms) are produced 1) by multiplying a velocity model (for example, the initial estimate generated from the velocity model) by a fixed density model (for example, the model density generated) to generate an impedance model, 2) by differentiating the impedance model, a series of reflectivity is generated, and 3) the series of reflectivity undergoes a convolution with the estimated source wavelet to generate syntheses. The implementations of the technology of the invention therefore model seismograms with normal incidence in convoy is worth a source wavelet with a series of reflectivity calculated for a stack of layers. The reflectivity can be calculated from impedances which are determined by multiplying the velocities and densities for all the layers. Each layer can have a speed and density assigned to the particular layer. The layers below the well, whose properties are inverted for updating, can be configured using fixed time thicknesses. Consequently, the actual layer thickness can be updated throughout the inversion steps described below by multiplying the speeds at a given generation of a differential evolution algorithm and for a given population element by the thicknesses time. On the other hand, the overburden model thicknesses are kept fixed and there is no need to update them as the reversal pattern continues.
The implementations of the invention technology, as mentioned above, can use a differential evolution algorithm, that is. an evolutionary algorithm based on a population. In one example, the differential evolution algorithm generates an initial random population x of elements (NP size) which evolve to keep superior elements and reject relatively less good elements. Elements of the population are referred to as the solutions to the opposite problem. Each solution is a vector made up of speeds of each layer taken into account for the update. Density can be kept fixed or updated as a function of speed using physical relationships of rock such as the Gardner equation, mentioned above. If the density is kept fixed, an a priori estimate can be made based on geomeanean considerations.
In one or more implementations, a random set of solutions corresponding to the population is generated with a fixed population size. For example, the population size can be 100 and each element of the population is a potential reversal solution. In a first iteration, a randomized population, comprising random numbers, is generated. These random numbers can be generated by a random number generator based on a search window, which may have been defined by a user. The search window can be selected near the initial speed model and a randomly created population called the parent population is then generated.
For example, the initial random population of solutions can be generated by choosing random numbers in a defined model space in the vicinity of an initial model estimate. Such an initial estimate can also be generated using other data sources. Additionally, the random number generator can use any type of distribution, if desired.
The randomly generated parent population undergoes three main steps before proceeding to the next iteration: 1) mutation, 2) crossing and 3) selection, which are described below. Through repeated iterations, a good set of elements of the population can be converged (for example, in which most of the solutions would be close to the right answer).
The differential evolution algorithm applies steps analogous to a genetic algorithm to evolve the population towards superior solutions filling its slices over different generations G, although the differential evolution algorithm uses techniques different from those of a genetic algorithm for these analogous steps. Regarding the mutation step mentioned above, for example, at a given generation (eg, iteration), the parent population can be used to generate a mutant population using equation (1) , which can be designated as follows:
V, = x _rl + F (x _r , -x _r3 ) ................ (1)
In equation (1), for each i in (1, .... NP), a combination of three distinct parent population elements x _r / „x _r 2 and x _r with indices (rl, r2 and r5) are selected to generate a mutant vector v, _: . F is a user-defined step size which can be between 0 and 2 in an example and corresponds to a mutation step.
In order to improve convergence with relatively smaller population sizes, a modified version of equation (1) is provided, which can be designated by equation (2) as follows:
^v ,,, =, n + ( ^Fnev ,,,) (¾ ”) ....... (2)
In equation (2), represents the best element of the population already generated. In this technique, F is made to vary for each model parameter in each mutant vector calculation in each generation, which is implemented using equation (2) above and equation (3 ) below, which may be designated as follows:
After the mutation has been applied to create the same number of mutant solutions as the parent population, the aforementioned crossover step is performed. In particular, after the generation of a mutant population v, an experimental population u is generated using equation (4), which can be designated as follows:
This crossing step represented in equation (4) above is comparable to a crossing in a genetic algorithm and can use a user-defined probability / speed of crossing (CR). In equation (4), rand is a random number (for example, a uniform distribution between 0 and 1) that is generated for each model parameter in the vector. In equation (4), ï represents each element of the population and / represents each segment of each element of the population. When determining an inverse solution for a model, the subsoil below the depth of the well (for example, which corresponds to a region of interest for the application of the inversion) is divided into layers , which can also be called segments. In one example, this part of the basement for inversion can be divided into a predetermined number of layers, such as 70 layers. Each layer will have a speed. As a result, 70 speeds must be reversed, the 70 speeds forming an element of the individual population, and each speed representing a segment (or layer) for this element of the individual population. Thus, / 'represents each individual speed of the 70 speeds and i represents each element of the individual population.
In equation (4), u _ÿ becomes equal to the element segment of the corresponding mutated population if a random number generator (which can be in continuous operation) is below a certain threshold called probability / speed of crossing (“CR”), otherwise u, ÿ becomes equal to the element segment of the corresponding population of the original population, Xÿ. In one example, the crossover rate CR can have a range of values between 0.7 and 0.9.
After the crossing step has been carried out to generate the same number of elements of the population as that included in the original parent population, the aforementioned selection step is then carried out. During the selection step, a comparison of the experimental population and the parent population of this generation is carried out to generate a child population. The comparison can be based on the objective function calculated for each element of the two populations. For each slice of the child population, the elements of the corresponding parent and experimental population are compared and the solution /! Higher element (for example, the lower the objective value, the higher the solution) is retained ( e) in the child population.
After the generation of the first child population, the differential evolution algorithm repeats the above-mentioned mutation, crossing and selection stages until a predefined stopping criterion is satisfied. For example, the termination criterion may be a specified number of generations / iterations (for example, a fixed number of iterations), an acceptable objective value level, other heuristic criteria and / or a combination of at least some of the above stopping criteria.
In an example of determining the final population, all elements of the final mutated population, the final crossover population (for example, experimental) and the original parent population for this iteration are compared (for example, because each of these three populations includes the same number of elements) based on a given objective function. As mentioned earlier, the objective function can be a cross-correlation between the stack of lanes and the summaries. It is appreciated that other types of objective functions can be used, such as an error between a summary and the stacking of lanes.
In the example where the objective function is a cross-correlation between the stack of lanes and the syntheses, a higher cross-correlation value will correspond to a better solution. In the example where the objective function corresponds to an error measure, a lower error value will correspond to a better solution. The element of the respective population of the child population is selected from the final mutated population, the final crossover population or the parent population of origin for this iteration on the basis of which the element of the population corresponds to the best solution. (for example, the highest cross-correlation value or the lowest error value in the examples described above).
Once the stopping criterion is satisfied, the selected final population can be used as the inversion response (for example, the solution or the output of the inversion algorithm representing velocities). Alternatively or in conjunction, each of the respective population elements of each iteration can be compared globally to determine a probabilistic estimate of the inversion response, which can then be used to provide an estimate of the uncertainty over the velocities of individual inversion.
In block 116, the impedance models are determined in a depth domain using the density model and the fixed speed models obtained by inversion of block 114. The impedances are calculated for each element of the population by multiplying the velocities by densities. Once the inversion step is complete and an updated set of "good" speed models is obtained, the speed and density values can be multiplied to obtain the impedances. These impedance models are then converted to the depth domain using the same velocity models after inversion. These depth domain impedance models can be used to identify potential geohazards ahead of the drill bit while also providing an estimate of depth uncertainty.
In block 118, the impedance models are stored (for example, for retrieval and / or subsequent viewing and / or analysis). In addition, in some implementations, stored impedance models can be provided for display to identify geohazards and estimate uncertainty in the depth domain of the well. An example of displaying impedance models is described below in Figure 3 described below.
FIG. 2 illustrates a curve 200 of an example of comparison of the values of the stack of terrain corridors (for example, determined in block 102) with a result of final inversion of the best model synthesis (for example, determined in block 114) according to certain implementations. In curve 200, the y axis represents the time values (ms) and the x axis represents the amplitude values. As shown, the correlation is close to 94% in the example of curve 200 in Figure 2.
FIG. 3 illustrates a curve 300 of an example of a depth impedance model obtained after the global inversion according to certain implementations. In the curve
300, the y axis represents the depth values (m) and the x axis represents the impedance values. Figure 3 shows the curve of the depth impedance model obtained by multiplying the best reverse speed model (for example, as shown on curve 200 in Figure 2) by a fixed density model, then converting the result d inversion of the time domain in depth using the inverted velocity model. This depth-to-impedance model can help identify sharp contrasts in the seismic property of rocks in the underground formation below the wellbore and potential geohazards ahead of the drill bit.
Potential geohazards can be identified using curve 300, for example, as curve 300 shows, at a depth of around 6,250 m, there is a large jump in impedance (for example, relative to above depth) which may indicate, for example, a very strong and / or very rigid rock which may represent a geohazard during drilling, or may indicate that the soil pressure is high at this depth, which may also represent a geohazard. In addition, at a depth of around 6,150 m in curve 300, there may also be a geohazard based on the same type of analysis. At a given depth at which a corresponding impedance is high, this can indicate areas where salt is present, which can be a risk when drilling (for example, the drill bit may get stuck in the salt during drilling) . Sudden changes in impedance on curve 300 can therefore indicate a potential geohazard that can be planned before drilling.
FIG. 4 illustrates a curve of an example of multiple embodiments of a speed model obtained by collecting all the inversion models which have a correlation value greater than a threshold chosen according to certain implementations. Figure 4 shows a series of velocity models obtained after the inversion using the differential evolution algorithm. Velocity models produced summaries that correlated with the stacking of field corridors by 92.5% or more. As a series of velocity models is obtained (for example, from a scheme like the differential evolution algorithm described above) with models which have comparable levels of correlation when the corresponding syntheses are compared with l 'stack of lanes, multiple depths can be predicted for a target layer and a level of uncertainty can be assessed for the depth of the target layer. In addition, the series of models is obtained by inversion using a fairly large search window comprising lower limits 425 and upper limits 450 as illustrated in FIG. 4. The upper and lower limits of the search window may change as a function of depth as shown in Figure 4. In one example, the search window is selected around an initial estimate of velocities from sources such as the analysis of surface seismic data. Advantageously, even if the initial estimate is not the most optimal, the use of a global inversion scheme can still determine the globally optimal solution and depends at least on the choice of the initial model. On the other hand, a local inversion scheme such as a conjugate gradient or a more abrupt descent process can strongly depend on the choice of the initial velocity model and be subject to larger errors in comparison with the differential evolution algorithm. for the same initial model.
FIG. 5 illustrates an example of a drilling assembly 500 for implementing the methods described here. It should be noted that if FIG. 5 generally represents a land drilling assembly, those skilled in the art will readily recognize that the principles described here are also applicable to underwater drilling operations which employ floating equipment and platforms or at sea, without going beyond the scope of the description.
In one or more implementations, the example method 100 described above begins after the drilling assembly 500 has drilled a wellbore 516 penetrating into an underground formation 518. It will be appreciated, however, that any treatment carried out in the method 100 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 in part of both (i.e., distributed processing). As illustrated, the drilling assembly 500 can comprise a drilling platform 502 which supports a derrick 504 having a movable block 506 for raising and lowering a drilling train 508. The drilling train 508 can notably comprise a drilling rod and a coiled tubing, which are generally known to those skilled in the art. A drive rod 510 supports the drill string 508 when it is lowered via a turntable 512. A drill bit 514 is attached to the distal end of the drill string 508 and is supplied by either a downhole motor and / or by rotation of the drill string 508 from the well surface. When the drill bit 514 rotates, it creates the wellbore 516 which penetrates into various underground formations 518.
A pump 520 (for example, a mud pump) circulates the drilling mud 522 through a supply pipe 524 and towards its drive rod 510, which conveys the drilling mud 522 downhole to the inside the drill string 508 and through one or more holes in the drill bit 514. The drill mud 522 is then recycled to the surface via a ring 526 defined between the drill string 508 and the walls from the wellbore 516. At the surface, the recycled or spent drilling mud 522 leaves the ring 526 and can be conveyed to one or more fluid treatment units 528 via a flow line d interconnection 530. After passing through the fluid treatment unit (s) 528, a “cleaned” drilling mud 522 is deposited in a neighboring retention pit 532 (that is to say, a mud pit). Although illustrated as being disposed at the outlet of the wellbore 516 via the ring 526, those skilled in the art will readily appreciate that the fluid treatment unit or units 528 can be placed at any other location in the drilling assembly 500 to facilitate its proper functioning, without departing from the scope of the description.
Chemicals, fluids, additives and the like can be added to the drilling mud 522 via a mixing hopper 534 communicatively coupled or otherwise in fluid communication with the retention pit 532. The drilling hopper Mixing 534 may 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 522 at any other location in the drilling assembly 500. In at least one implementation, for example, there may be more than one retention pit 532, such as several retention tanks 532 in series. In addition, the retention pit 532 can be representative of one or more fluid storage installations and / or units where the chemicals, fluids, additives and the like can be stored, reconditioned and / or regulated up to 'to their addition to drilling mud 522.
The processor 538 can be part of the computer hardware used to implement the various blocks, modules, elements, components, methods and illustrative algorithms described here. The processor 538 can be designed to execute one or more sequences of instructions, programming positions or code stored on a non-transient computer-readable medium. The processor 538 can be, for example, a general-purpose microprocessor, a mierocontroller, a digital signal processor, an application-specific integrated circuit, a user-programmable pre-broadcast network, a programmable logic device, a controller, a state machine, gate-controlled logic, separate hardware components, an artificial neural network, or any similar suitable entity that can perform calculations or other manipulation of data. In some implementations, 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), programmable erasable read only memory (EPROM)), registers, hard disks, removable disks, CD-ROMs, DVDs or any other similar suitable storage device or medium.
The executable sequences described here can be implemented with one or more code sequences contained in a memory. In some implementations, this code can be read into memory from another machine-readable medium. The execution of instruction sequences contained in the memory can cause a processor 538 to execute the processing steps described here. One or more processors 538 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, the present implementations are not limited to any specific combination of hardware and / or software.
As used here, machine readable media will refer to any media that directly or indirectly provides instructions to the 538 processor for execution. Machine-readable media can take many forms, including, for example, non-volatile media, volatile media, and transmission media. Volatile media can include, for example, optical and magnetic disks. Non-volatile media may 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 similar optical media , punch cards, paper tapes, and similar physical media with profiled holes, RAM, ROM, PROM, EPROM, and flash EPROM.
As shown in more detail in FIG. 5, the processor 538 can be connected in a communicating manner to one or more seismic detectors (three seismic detectors 560a, 560b and 560b are shown) and to a seismic source 550. Although a seismic source be shown, it is appreciated that more than one seismic source can be provided.
In one or more implementations, the seismic source 550 (also called “firing”) is a device which generates a controlled seismic energy and directs this energy into an underground formation. The seismic source 550 can generate seismic energy in various ways, for example using an explosive device (for example, dynamite or other explosive charge), an air pistol, a plasma sound source, a “vibrating truck”, a source of electromagnetic pulses, a seismic vibrator or other devices capable of generating seismic energy in a controlled manner. Seismic sources can provide single pulses of seismic energy or continuous scans of seismic energy.
The 560 seismic detector (such as a geophone) is a device used in seismic acquisition that detects the speed of the ground produced by seismic waves and transforms motion into electrical pulses. The seismic detector 560 can detect a movement in various ways, for example using an analog device (for example, a spring-mounted magnetic mass moving inside a coil of wire) or a mieroelectromechanical device (MEMS) (for example, a MEMS device that generates an electrical signal in response to ground movement) via an active feedback circuit).
In one or more implementations, a downhole tool may include one or more seismic sources (for example, seismic source 550) and one or more seismic detectors (for example, seismic detectors 560a, 560b and 560b).
To obtain zero offset VSP data to generate the stack of lanes (for example, in block 102 of method 100), processor 538 communicates with seismic detectors 560a, 560b and 560c and seismic source 550 to send and receive information (eg, output) from the seismic detectors 560a, 560b and 560c and the seismic source 550, and to control the operation of the seismic detectors 560a, 560b and 560c and the seismic source 550.
As shown, the seismic source 550 is positioned along the upper surface of the underground formation 518, the seismic detectors 560a, 560b and 560c are positioned under the upper surface of the underground formation 518 inside the wellbore 516, In one example, the seismic sources 550 and the seismic detectors 560a, 560b and 560c are connected in a communicating manner to the processor 538 via a communication interface (not shown). Examples of a communication interface include wired connectors or wireless transceivers.
The drill assembly 500 may further include a downhole assembly (BHA) coupled to the drill string 508 near the drill bit 514, The BHA may include various downhole measurement tools such as, but without s '' limit, measurement during drilling (MWD) and logging during drilling (LWD), which can be designed to perform downhole and / or tophole measurements of surrounding underground formations 518 , Logging during drilling (LWD) or measurement during drilling (MWD) 536 equipment is included along the drill string 508. In one or more implementations, the drilling assembly 500 involves the drilling the wellbore 516 while the logging measurements are carried out with the LWD / MWD 536 equipment. More generally, the methods described here involve the introduction of a logging tool into the wellbore which is capable of determining well settings age, 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 not! occur only at the top of the hole, only at the bottom of the hole, or at least in part of both (i.e., distributed processing).
According to the present description, the LWD / MWD 536 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 516. In an example , the stationary acoustic sensor can be arranged around the longitudinal axis of the LWD / MWD equipment 536 and, thus, of the wellbore 516 at a predetermined fixed location inside the wellbore 516. The mobile acoustic sensor can be arranged around the longitudinal axis of the LWD / MWD 536 equipment and, thus, of the wellbore 516, and is designed to move along the longitudinal axis of the wellbore 516. However, 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 the design.
The LWD / MWD 536 equipment can transmit the measured data to a 538 processor on the wired or wireless surface. Data transmission is generally illustrated on line 540 to demonstrate the communication coupling between the 538 processor and the LWD / equipment. MWD 536 and does not necessarily indicate the path to which the communication is made. The fixed acoustic sensor and the mobile acoustic sensor can be communicatively coupled to the line 540 used to transfer measurements and signals from the BHA to the processor 538 which processes the acoustic measurements and the signals received by acoustic sensors (for example, the stationary acoustic sensor, the mobile acoustic sensor) and / or controls the operation of the BHA. In the technology of the invention, the LWD / MWD 536 equipment may be able to record the analysis of the underground formation 518 near the wellbore 516.
In certain implementations, part of the processing can be carried out by a telemetry module (not shown) in combination with the processor 538. For example, the telemetry module can preprocess the individual sensor signals (for example, by conditioning of signal, filtering and / or noise cancellation) and transmit them to a surface data processing system (e.g., processor 538) 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 (that is to say, distributed processing).
In various implementations, the processed acoustic signals are evaluated in conjunction with measurements from other sensors (for example, surface well temperature and pressure measurements) to assess flow conditions and overall well integrity . The telemetry module may include any known means of known downhole communication including, but not limited to, a mud pulse telemetry system, an acoustic telemetry system, a wired communication system, a communication system wireless or any combination thereof. In some implementations, some or all of the measurements taken by the stationary acoustic sensor and the mobile acoustic sensor can also be stored inside a memory associated with the acoustic sensors or the telemetry module for subsequent retrieval on the surface. during the retraction of the drilling train 508.
FIG. 6 illustrates a set of logs 600 having a wire system suitable for the implementation of the methods described here. As illustrated, a platform 610 can be equipped with a derrick 612 which supports a winch 614. Drilling of oil and gas wells, for example, is commonly carried out using a drill string connected between them so as to form a drill string which is lowered via a turntable 616 into a wellbore 618, Here it is assumed that the drill string has been temporarily removed from the wellbore 618 to allow a logging tool 620 (and / or any other suitable wired tool) to be lowered by a metal cable 622, a smooth cable, coiled tubing, a pipe, a downhole tractor, a logging cable, and / or any other suitable physical structure or means of transport extending downhole from the surface into the wellbore 618. Typically, the logging tool 620 is lowered to a region of interest and then pulled towards high at a substantially constant speed. During the upward triggering, the instruments included in the logging tool 620 can be used to make measurements on the underground formation 624 adjacent to the wellbore 618 during the passage of the logging tool 620. In addition, it it is understood that any processing carried out by the logging tool 620 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., processing distributed).
The logging tool 620 can comprise one or more wire instruments which can be suspended in the wellbore 618 by the metal cable 622. The wire instrument (s) can comprise the stationary acoustic sensor and the mobile acoustic sensor, which can be coupled communicating with the metal cable 622. The metal cable 622 can include conductors for transporting energy to the wired instrument and also facilitating communication between the surface and the instrument. Wired. The 620 logging tool may include a mechanical component to cause 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 618.
Acoustic sensors (for example, stationary acoustic sensor, 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 include fiber optic sensors, such as point sensors (for example, fiber Bragg gratings, etc.) distributed at desired or predetermined locations along the length d 'an 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 wiring to. optical fiber.
In addition or alternatively, in one example (not explicitly illustrated), the acoustic sensors can be fixed or embedded inside the one or more casing columns covering the wellbore 618 and / or the wall of the wellbore 618 at a predetermined distance axially spaced.
A logging installation 628, represented in FIG. 6 in the form of a truck, can collect measurements from the acoustic sensors (for example, the stationary acoustic sensor, the mobile acoustic sensor), and can include the processor 538 for controlling, processing , store and / or view the measurements collected by the acoustic sensors. The processor 538 can be communicatively coupled to the wire instrument (s) using the metal cable 622. As a variant, the measurements collected by the logging tool 620 can be transmitted (by cable or wireless) or physically delivered to installations. off-site IT in which the methods and processes described here can be implemented.
In one example, one or more seismic detectors may be disposed in the logging tool 620, where the metal cable 622 controls the depth of the logging tool 620 in the wellbore 618 and provides a communication channel to the upper surface of the underground formation 624, (for example, at processor 538). One or more seismic sources can be positioned along the upper surface of the underground formation 624. To obtain VSP data with zero offset in order to generate the stacking of lanes (for example, in block 102 of method 100), processor 538 communicates with the seismic detectors and the seismic sources to send and receive information from the seismic detectors and the seismic sources, and to control the operation of the seismic detectors and the seismic source.
FIG. 7 illustrates a schematic diagram of a set of general components of an example computer device 700. In this example, the computer device 700 includes a processor 702 for executing instructions which can be stored in a device or element of memory 704. The computing device 700 can comprise many types of memory, data storage or non-transient storage medium readable by computer, such as a first data storage for program instructions to be executed by the processor 702, separate storage for images or data, removable memory for sharing information with other devices, etc.
The computing device 700 can typically include some type of display element 706, such as a touch screen or a liquid crystal display (LCD). As described, the computing device 700 in many embodiments will include at least one input element 710 capable of receiving conventional input from a user. 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 some embodiments, however, the computing device 700 may have no buttons and can only be controlled by a combination of visual and audio controls, so that a user can control the computing device 700 without having to be in touch with the computing device 700. In certain embodiments, the computing device 700 of FIG. 7 can comprise one or more network interface elements 708 for communicating on various networks, such as WiFi, Bluetooth, RF, wired communication systems. or wireless. The computing device 700 in many embodiments can communicate with a network, such as the Internet, and may be able to communicate with other computing devices of this type.
As described here, different approaches can be implemented in different environments depending on the embodiments described. For example, FIG. 8 illustrates a schematic diagram of an example of an environment 800 for the implementation of aspects according to certain 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 an 802 electronic client device, which can include any suitable device that can be used to send and receive requests, messages or information over an appropriate network 804 and return 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 digital assistants, electronic book readers and the like.
The 804 network can include any suitable network, including an intranet, Internet, cellular network, a local area network, or any other network or combination thereof. The network 804 can be a “push” network, a “pull” network or a combination of these. In a push network, one or more of the servers send data to the client device. In a pull network, one or more of the servers send data to the client device upon request by 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 804 network can be activated via wired or wireless connections and combinations thereof. In this example, the network includes the internet because the environment includes a server 806 for receiving requests and providing content in response thereto, although for other networks, an alternative device for a similar purpose could be used, like this would appear obvious to the skilled person.
The client device 802 can represent the logging tool 620 of FIG. 6 and the server 806 can represent the processor 538 of FIG. 5 in certain implementations, or the client device 802 can represent the processor 538 and the server 806 can represent off-site IT facilities in other implementations.
Server 806 will typically include an operating system which provides executable program instructions for general administration and general operation of that server and will typically include computer readable media storage instructions which, when executed by a server processor, allow the server to perform its intended functions. Appropriate implementations for the operating system and the general functionality of the servers are as or commercially available and are easily implemented by the skilled person, 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 interconnected via computer links, using one or more computer networks, or direct connections. However, those skilled in the art will appreciate that such a system can work equally well in a system having a number of components less or greater than that illustrated in FIG. 8. Thus, the representation of the environment 800 in FIG. 8 must be considered to be illustrative in nature and not to limit the scope of the description.
Storage media and other non-transient computer readable media intended to contain code, or portions of code, may include any suitable storage media used in the prior art, such as, but without limiting, volatile and non-volatile, removable and non-removable media used in any process or any technology for storing information such as computer-readable instructions, data structures, program modules or other data , including RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disc (DVD) or other optical storage, magnetic tapes, magnetic tape, storage on magnetic disc or other magnetic storage devices, or any other medium that can be used to store the desired information and to which a system device can to access. On the basis of the description and of the lessons provided here, the person skilled in the art will appreciate other means and / or methods for implementing the various implementations.
Various examples of aspects of the description are described below as clauses for convenience. They are provided by way of example and do not limit the technology of the invention.
Clause 1, A method comprising: generating a stack of lanes on the vertical seismic profile (VSP) database of a wellbore in an underground formation; generating an initial estimate of a velocity model for the underground formation below the wellbore; generating a density model for the underground formation below the wellbore based on information from neighboring wells; inverting, based on a global inversion algorithm and the initial speed model estimate, the stack of lanes generated to determine a set of speed models; generation of impedance models in a depth domain based on the density model generated and the set of speed models; and storing the generated impedance models.
Clause 2. The method according to clause 1, further comprising: providing, for display, generated impedance models.
Clause 3. The method according to clause 1, wherein the generated impedance models are indicative of an estimate of uncertainty at depth and the VSP data includes zero shift VSP data.
Clause 4. The method according to clause 1, further comprising: estimating a source wavelet; and the generation of a set of synthetic seismograms based on the source wavelet.
Clause 5. The method according to clause 4, in which the generation of the set of synthetic seismograms further comprises: the generation of an impedance model based on the multiplication of the initial estimate generated from the speed model by the density model generated; generating a series of reflectivity based on the differentiation of the impedance model; and the realization of a convolution on the reflectivity series and. Estimée Wavelet source estimated to provide the generated set of synthetic seismograms.
Clause 6. The method according to clause 4, in which the inversion of the stacked lane stack further comprises: determining a scale factor for a comparison between the generated set of synthetic seismograms and the stack of corridors generated.
Clause 7. The method according to clause 4, in which the inversion of the stack of lanes generated further comprises: determining an initial parent population, the initial parent population comprising a certain number of elements of the population, each element of the population representing a solution for reversing the stack of corridors generated; generating a mutation population based on the initial parent population, the mutation population comprising a number of elements of the population equal to the number of elements of the initial parent population; determining an experimental population on the basis of a probability of crossover applied to the mutation population; and the generation of a child population based on a comparison of the experimental population and the initial parent population.
Clause 8. The method according to clause 7, in which the initial parent population is determined on the basis of a random set of numbers.
Clause 9. The method according to clause 7, further comprising: generating a second mutation population based on the child population generated; the determination of a second experimental population on the basis of the probability of crossing crossing applied to the second mutation population; determining that a termination criterion is met; and determining a final population based on a comparison of the generated child population, the second mutation population and the second experimental population, in which the final population comprises the set of velocity models.
Clause 10. The method according to clause 9, in which the global inversion algorithm comprises an evolutionary algorithm, and the termination criterion is based on a certain number of iterations of the evolutionary algorithm or a predetermined level for a objective function.
Clause 11. The method according to clause 9, in which the final population represents an inversion response to reverse the stack of lanes generated.
Clause 12. The process according to clause 1, in which a potential geohazard is indicated at least in part by a degree of change between the respective impedance values in the generated impedance models.
Clause 13. The method according to clause 1, wherein generating the stack of corridors on the VSP database of the wellbore in the underground formation further comprises: generating, using one or more multiple seismic sources, seismic energy in the wellbore in the underground formation; receiving, using one or more seismic detectors, the seismic energy generated; and generating VSP data based on an output from the one or more seismic detectors.
Clause 14. A system comprising: a processor; and a memory device comprising instructions which, when executed by the processor, cause the processor to: generate a stack of lanes on the basis of vertical seismic profile (VSP) database of a wellbore in a formation underground; generate an initial estimate of a velocity model for the underground formation below the wellbore; generating a density model for the underground formation below the wellbore based on information from neighboring wells; invert, based on a global inversion algorithm and the initial speed model estimate, F stack of lanes generated to determine a set of speed models; generating impedance models in a depth domain based on the density model generated and the set of speed models; and store the generated impedance models.
Clause 15. The system according to clause 14, in which the instructions further cause the processor to: supply, for display, the generated impedance models.
Clause 16. The system according to clause 14, wherein the generated impedance models are indicative of an estimate of the uncertainty at depth and the VSP data includes zero shift VSP data.
Clause 17. The system according to clause 14, in which the instructions further cause the processor to: estimate a source wavelet; and generate a set of synthetic seismograms based on the source wavelet.
Clause 18, The system according to clause 17, in which the generation of the set of synthetic seismograms further comprises: the generation of an impedance model based on the multiplication of the initial estimate generated from the velocity model by the density model generated; generating a series of reflectivity based on the differentiation of the impedance model; and performing a convolution on the reflectivity series and the estimated source wavelet to provide the generated set of synthetic seismograms.
Clause 19. The system according to clause 17, in which the inversion of the generated stack of lanes further comprises: the determination of a scale factor for a comparison between the generated set of synthetic seismograms and the stack of corridors generated.
Clause 20. The system according to clause 17, in which the inversion of the stacked lane generated further comprises: determining an initial parent population, the initial parent population comprising a certain number of elements of the population, each element of the population representing a solution for reversing the stack of corridors generated; generating a mutation population based on the initial parent population, the mutation population comprising a number of elements of the population equal to the number of elements of the initial parent population; determining an experimental population on the basis of a probability of crossover applied to the mutation population; and the generation of a child population based on a comparison of the experimental population and the initial parent population.
Clause 21. The system according to clause 20, in which the initial parent population is determined on the basis of a random set of numbers.
Clause 22. The system according to clause 20, wherein the instructions further cause the processor to: generate a second mutation population based on the generated child population; determining a second experimental population on the basis of the probability of crossing probability applied to the second mutation population; determine that a stop criterion is satisfied; and determining a final population based on a comparison of the generated child population, the second mutation population and the second experimental population, in which the final population comprises the set of velocity models.
Clause 23, The system according to clause 22, in which the global inversion algorithm includes an evolutionary algorithm, and the termination criterion is based on a number of iterations of the evolutionary algorithm or a predetermined level for a objective function.
Clause 24. The system according to clause 22, in which the final population represents an inversion response to reverse the stack of lanes generated.
Clause 25. The system according to clause 14, in which a potential geohazard is indicated at least in part by a degree of change between the respective impedance values in the generated impedance models.
Clause 26, The system according to clause 14, wherein the system further comprises a downhole tool, the downhole tool comprises one or more seismic sources and one or more seismic detectors, and the instructions further provide the processor to: generate, using one or more seismic sources, seismic energy in the wellbore in the underground formation; receive, using one or more seismic detectors, the seismic energy generated; and generate the VSP data based on an output from the one or more seismic detectors.
Clause 27. The system according to clause 26, in which the downhole tool is Fun among a logging tool during drilling or a wired tool.
Clause 28, A computer-readable non-transient medium comprising instructions stored therein which, when executed by at least one computing device, cause the at least one computing device to: generate a stack of lanes on the base vertical seismic profile (VSP) data from a wellbore in an underground formation; generate an initial estimate of a velocity model for the underground formation below the wellbore; generating a density model for the underground formation below the wellbore based on information from neighboring wells; reverse, based on a global inversion algorithm and the initial speed model estimate, the stack of lanes generated to determine a set of speed models; generating impedance models in a depth domain based on the density model generated and the set of speed models; and store the generated impedance models.
A reference to an element in the singular is not intended to mean a single element unless it is specifically indicated, but rather one or more elements. For example, "a" module can refer to one or more modules. An element designated by "a", "an", "the" or "said" does not preclude, without other constraints, the existence of additional identical elements.
Titles and subtitles, if any, are used for convenience only and do not limit the invention. The word example is used to denote an example or illustration. To the extent that the term understand, have, or the like is used, this term is intended to be inclusive in a manner similar to the term understand, which being, 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 a real relationship or order between such 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 of the invention, the description, the present description, other variants thereof and the like are used for reasons of convenience and do not imply that a description relating to this or these expressions is essential to the technology. of the invention or that this description applies to all the configurations of the technology of the invention. A description relating to this or these expressions can apply to all 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 one aspect or certain aspects can refer to one or more aspects and vice versa, and this applies in a similar way to other previous expressions.
The 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 part of the listing. 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. For example, each of the expressions "at least one of A, B and C" or "at least one of A, B or C" means 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 processes described is an illustration of examples of approaches. Unless stated otherwise, it is understood that the specific order or hierarchy of steps, operations or processes may be executed in a different order. Certain steps, operations or procedures can be performed simultaneously. The associated process claims, if any, present elements of the various steps, operations or processes in a sampling order, and are not intended to be limited to the specific order or hierarchy presented. These can be implemented 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 in a single software / hardware product or packaged in several software / hardware products.
In one aspect, a coupled or similar term may refer to a direct coupling. In another aspect, a coupled or similar term may refer to an indirect coupling.
Outfits such as top, bottom, front, back, side, horizontal, vertical and the like refer to an arbitrary reference frame, rather than the ordinary gravitational reference frame. Thus, such a term can extend upwards, downwards, diagonally or horizontally in a gravitational reference frame.
The description is provided to enable those 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 of the invention. The description provides various examples of the technology of the invention, and the technology of the invention is not limited to these examples. Various modifications of these aspects will be apparent to those skilled in the art, and the principles described herein can be applied to other aspects.
All structural and functional equivalents of the elements of the various aspects described throughout the description currently or subsequently known to those skilled in the art are expressly incorporated herein by reference and are intended to be encompassed by the claims. Furthermore, nothing described here is intended to be dedicated to the public, whether or not this description is explicitly mentioned in the claims. No claim element may be interpreted under the provisions of Title 35 USC §112, sixth paragraph, unless the element is expressly described using the phrase "pleas for" or, in the case of a process claim, if the item is described using the term "step to".
The title, background, brief description of the drawings, the abstract and the drawings are hereby incorporated into the description and are provided as examples of the description, and not as restrictive descriptions. It goes without saying 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 should not be interpreted 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 object of the invention lies in a number less than all the characteristics of a single configuration or operation described. The claims are hereby incorporated into the detailed description, each claim being treated 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 the applicable patent law, nor should it be interpreted in this way.

权利要求:
Claims (15)
[1" id="c-fr-0001]
1. Process comprising:
generating a stack of corridors based on the vertical seismic profile (VSP) database of a wellbore in an underground formation;
generating an initial estimate of a velocity model for the underground formation below the wellbore;
generating a density model for the underground formation below the wellbore based on information from neighboring wells;
inverting, based on a global inversion algorithm and the initial speed model estimate, the stack of lanes generated to determine a set of speed models;
generating impedance models in a depth domain based on the density domain generated and the set of velocity models; and storing the generated impedance models.
[2" id="c-fr-0002]
2. The method of claim 1, further comprising: providing, for display, the generated impedance models.
[3" id="c-fr-0003]
The method of claim 1, wherein the impedance models generated are indicative of an estimate of the uncertainty in depth and the VSP data includes zero shift VSP data.
[4" id="c-fr-0004]
4. The method of claim 1, further comprising: estimating a source wavelet; and generating a set of synthetic seismograms based on the source wavelet, optionally, in which the set of generated synthetic seismograms further comprises:
generating an impedance model based on the multiplication of the initial estimate generated from the speed model by the density model generated;
generating a series of reflectivity based on the differentiation of the impedance model; and performing a convolution on the reflectivity and plump source series estimated to provide the generated set of synthetic seismograms, optionally, in which the inversion of the stacked lane stack further comprises: determining a factor scale for a comparison between the generated set of synthetic seismograms and the stacked lane generated.
[5" id="c-fr-0005]
5. Method according to claim 4, in which the inversion of the stack of lanes generated further comprises:
determining an initial mother population, the initial mother population comprising a certain number of elements of the population, each element of the population representing an inversion solution of the stack of lanes generated;
generating a mutation population based on the initial mother population, the mutation population comprising a number of elements of the population equal to the number of elements of the initial mother population;
determining an experimental population on the basis of a probability of crossover applied to the mutation population; and the generation of a daughter population based on a comparison of the experimental population and the initial mother population.
[6" id="c-fr-0006]
The method of claim 5, wherein the initial mother population is determined based on a random set of numbers.
[7" id="c-fr-0007]
7. The method of claim 5, further comprising:
the generation of a second mutation population based on the daughter population generated;
the determination of a second experimental population on the basis of a probability of crossing crossing applied to the second mutation population;
determining that a termination criterion is satisfied; and determining a final population based on a comparison of the generated daughter population, the second mutation population and the second experimental population, in which the final population includes the set of velocity models.
[8" id="c-fr-0008]
8. Method according to claim 7, in which the global inversion algorithm comprises an evolutionary algorithm and the stopping criterion is based on a number of iterations of the evolutionary algorithm or a predetermined level for an objective function,
5
[9" id="c-fr-0009]
9. The method of claim 7, wherein the final population represents an inversion response to reverse the stack of lanes generated.
[10" id="c-fr-0010]
10. The method of any of claims 1 to 9, wherein a potential geohazard is indicated at least in part by a degree of change between values
10 of respective impedance in the generated impedance models,
[11" id="c-fr-0011]
11. Method according to any one of claims 1 to 10, in which the generation of the stack of lanes on the basis of VSP of the wellbore in the underground formation further comprises:
15 generation, using one or more seismic sources, of seismic energy in the wellbore in the underground formation;
the reception, using one or more seismic detectors, of the seismic energy generated; and generation of VSP data based on output from one or more 20 seismic detectors,
[12" id="c-fr-0012]
12. System comprising: a processor; and a memory device comprising instructions which, when executed by the processor, cause the processor to:
generating a stack of lanes based on the vertical seismic profile (VSP) database of a wellbore in an underground formation;
generating an initial estimate of a velocity model for the underground formation below the wellbore;
Generating a density model for the underground formation below the wellbore based on information from neighboring wells;
reverse, based on a global inversion algorithm and the initial speed model estimate, the stack of lanes generated to determine a set of speed models;
generating impedance models in a depth domain based on the density domain generated and the set of velocity models; and store the generated impedance models.
[13" id="c-fr-0013]
13. The system of claim 12, wherein the instructions further cause the processor to perform the method of any of claims 2 to 11.
[14" id="c-fr-0014]
14. Non-transient computer-readable medium comprising instructions stored therein which, when executed by at least one computer device, cause the at least one computer device to:
generating a stack of lanes based on the vertical seismic profile (VSP) database of a wellbore in an underground formation;
generating an initial estimate of a velocity model for the underground formation below the wellbore;
generating a density model for the underground formation below the wellbore based on information from neighboring wells;
reverse, based on a global inversion algorithm and the initial speed model estimate, the stack of lanes generated to determine a set of speed models;
generating impedance models in a depth domain based on the density model generated and the set of velocity models; and store the generated impedance models.
[15" id="c-fr-0015]
15. The non-transient computer-readable medium of claim 14, wherein the non-transient computer-readable medium comprises additional instructions stored therein which, when executed by the at least one computing device, further provides the at least one computer device for carrying out the method according to any one of claims 2 to 11.

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同族专利:

公开号 | 公开日

US10324212B2|2019-06-18|

US20190049612A1|2019-02-14|

WO2019027449A1|2019-02-07|

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法律状态:
2019-06-19| PLFP| Fee payment|Year of fee payment: 2 |

2020-10-02| PLSC| Publication of the preliminary search report|Effective date: 20201002 |

2021-03-12| ST| Notification of lapse|Effective date: 20210206 |

优先权:

申请号 | 申请日 | 专利标题

IBWOUS2017044966|2017-08-01|

PCT/US2017/044966|WO2019027449A1|2017-08-01|2017-08-01|Prediction ahead of bit using vertical seismic profile data and global inversion|

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