COMPUTER IMPLEMENTED METHOD FOR IMPROVING A VELOCITY MODEL FOR SEISMIC IMAGING

Abstract

The present invention is in the field of seismic imaging of underground structures. The invention is a method for solving the uncertainty and instability generated in reservoir geometries due to salt bodies which causes the presence of artifacts in the velocity fields. The method is based in a desalting process and a further specific reconstruction of the sediments located in the domain of the image. Desalting means to remove salt volumes located within the domain wherein said process is followed by the replacement of good sediment velocity values and a careful iterative process avoiding the generation of artifacts.

Claims

1. A computer implemented method for improving a velocity model for seismic imaging, said method comprising a migration module configured to migrate acoustic field data to correct a seismic image iteratively, the seismic image comprising voxels and/or pixels representing a velocity model of a region of a subsurface region, wherein said migration module at least returns a velocity correction (v) of the seismic image by carrying out a predetermined number of iterations; wherein the method comprises the steps: a) recording seismic waves at the earth's surface being acquired as acoustic field data, b) departing from an initial proposed image converting acoustic field data by the migration module, through a predetermined number of iterations, into an estimated seismic image comprising voxels and/or pixels representing the velocity model of the region of the subsurface region; c) identifying in the seismic image at least one salt region D1, at least one artifacts region D2, and at least one region D3 with no salt or artifacts; d) removing the voxels and/or pixels of the at least one salt region D1 and the at least one artifacts region D2 from the seismic image; e) filling the at least one salt region D1 and the at least one artifacts region D2 of the seismic image with voxels and/or pixels with velocity values interpolated from the velocity values of the at least one region D3 with no salt or artifacts; f) generating a velocity correction v for each voxel and/or pixel migrating the acoustic field data with the image obtained in step e) by means of the migration module carrying out a predetermined number of iterations n; g) updating the at least one salt region D1 and the at least one region D3 with no salt or artifacts with the velocity correction v for each voxel and/or pixel of said regions; h) updating the artifacts region D2 with a limited velocity correction v for each voxel and/or pixel of said regions, the limited velocity correction v being: or a bounded velocity correction; that is, the correction v if |v|.sub.max being .sub.max a positive predetermined bound or the correction sign (v).Math..sub.max if |v|.sub.max being sing (v) the sign of v, or a damped velocity correction v, being (0,1) a predetermined value. i) providing the seismic image corrected in the previous step.

2. The method according to claim 1, wherein steps f)-h) are iteratively executed until convergence.

3. The method according to claim 1, wherein the at least one salt region D1, the at least one artifacts region D2, the at least one region D3 with no salt or artifacts, or any combination thereof are re-identified in the seismic image after the updating process according to step h).

4. The method according to claim 1, wherein in step e) the filling process of the at least one salt region D1, the at least one artifacts region D2, or both, comprises: for each plane and/or row of voxels and/or pixels of the image comprising at least one voxel and/or pixel removed, interpolate the removed voxels and/or pixels by using the velocity values of voxels and/or pixels of the same plane and/or row corresponding to the at least one region D3 with no salt or artifacts.

5. The method according to claim 4, wherein it further comprises, after interpolating the removed voxels and/or pixels, a smoothing step involving voxels and/or pixels of the same plane and/or row.

6. The method according to claim 5, wherein the smoothing step is carried out by a Natural Neighbor algorithm.

7. The method according to claim 1, wherein after carrying out step e) and before carrying out step f), a smoothing step over the entire seismic image is applied.

8. The method according to claim 5, wherein the smoothing step over the entire seismic image is carried by: generating a second image with the same number of voxels and/or pixels, each voxel and/or pixel having the value 1/v of the corresponding velocity value v of the voxel and/or pixel of the seismic image; carrying out the smooth step over the second image; providing the seismic image wherein each voxel and/or pixel takes the inverse value of the corresponding voxel and/or pixel of the second image.

9. The method according to claim 7, wherein the smoothing step over the entire image is carried out by a damped least square algorithm.

10. The method according to claim 1, wherein a union of the at least one salt region D1, the at least one artifacts region D2 and the at least one region D3 with no salt or artifacts is the entire image.

11. The method according to claim 1, wherein the artifacts region D2 comprises those voxels and/or pixels located under at least one salt region D1.

12. The method according to claim 1, wherein the migration module uses a ray stopper algorithm when carrying out the migration process in step f) wherein the ray tracing prevents paths crossing the artifacts region D2.

13. The method according to claim 1, wherein the at least one salt region D1 of the velocity model in step c) is identified selecting regions with velocity values within a prespecified range of velocity values measured in salt regions.

14. The method according to claim 1, wherein the selection of artifacts regions D2, the selection of the limited velocity correction v for the artifacts regions D2, or any combination thereof are requested to the user.

15. A computer system having a processor and a non-transitory computer-readable medium storing computer-executable instructions which, when executed by the processor, cause the processor to carry out the method according to claim 1.

16. A non-transitory computer program product stored on a computer-readable medium and comprising computer-implementable instructions, which, when executed by a computer, cause the computer to carry out the method according to claim 1.

Description

DESCRIPTION OF THE DRAWINGS

[0082] These and other features and advantages of the invention will be seen more clearly from the following detailed description of a preferred embodiment provided only by way of illustrative and non-limiting example in reference to the attached drawings.

[0083] FIG. 1 This figure shows a data processing system for carrying out a method according to the invention.

[0084] FIG. 2 This figure shows schematically an example of a prior art process and a subsequent processing of the image according to the invention.

[0085] FIG. 3 This figure shows a starting velocity model in the form of an image being computed by using a migration algorithm according to the state of art. The velocity field shown in this figure is used as the image to be processed according to an embodiment of the invention.

[0086] FIG. 4 This figure shows some areas of the image turned to black color for identifying at least some salt bodies.

[0087] FIG. 5 This figure shows an intermediate step according to an embodiment of the invention wherein the image has been split in three regions D1, D2 and D3.

[0088] FIG. 6 This figure shows the removal workflow result applied to the image of the same embodiment.

[0089] FIG. 7 This figure shows a filling process in the removed regions by using an interpolation of the surrounding velocity values.

[0090] FIG. 8 This figure shows the corrected image after migrating the image applying a selected correction.

[0091] FIG. 9 This figure shows the Reverse Time Migration (RTM) using the state of art depth velocity model.

[0092] FIG. 10 This figure shows the Reverse Time Migration (RTM) obtained by using a method according to the invention.

DETAILED DESCRIPTION OF THE INVENTION

[0093] As will be appreciated by one skilled in the art, aspects of the present invention may be embodied as a system, a method or a computer program product. Accordingly, aspects of the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment (including firmware, resident software, micro-code, etc.) or an embodiment combining software and hardware aspects that may all generally be referred to herein as a circuit, module or system. Furthermore, aspects of the present invention may take the form of a computer program product embodied in one or more computer readable medium(s) having computer readable program code embodied thereon.

[0094] Any combination of one or more computer readable medium(s) may be utilized. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.

[0095] A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.

[0096] Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

[0097] Computer program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C++ or the like and conventional procedural programming languages, such as the C programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet Service Provider).

[0098] Aspects of the present invention are described below with reference to illustrations and/or diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each illustration can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks.

[0099] These computer program instructions may also be stored in a computer readable medium that can direct a computer, other programmable data processing apparatus, or other devices to function in a particular manner, such that the instructions stored in the computer readable medium produce an article of manufacture including instructions which implement the function/act specified in the flowchart and/or block diagram block or blocks.

[0100] The computer program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of operational steps to be performed on the computer, other programmable apparatus or other devices to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide processes for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks.

[0101] Turning now to the drawings and more particularly, FIG. 1 shows an example of a system 100 improving a velocity model for seismic imaging departing from acoustic field data (AD), according to a preferred embodiment of the present invention.

[0102] The preferred system 100 improves a velocity model in the form of an image (I) in an efficient manner comprising the sequential process of taking first approximation of the numerical model in the form of a migrated image, identifying salt bodies D1, artifacts and regions comprising instabilities or inaccurate structures D2 and the rest of the domain. A further step removes pixels/voxels located within regions D1 and D2, being replaced by values interpolated by using pixels/voxels of region D3.

[0103] These two steps are carried out in the computer system (110) and such a computer system (110) executes an instantiated migration module (M) for determining a velocity correction v of pixels/voxels of D1, D2 and D3. Said computer system (110) is adapted to carry out a selected correction wherein at least D2 is being updated by a limited correction v.

[0104] A preferred computing system 100 includes one or more computers 102, 104, 106 (3 in this example), coupled together, e.g., wired or wirelessly over a network 108. The network 108 may be, for example, a local area network (LAN), the Internet, an intranet or a combination thereof. Typically, the computers 102, 104, 106 include one or more processors, e.g., central processing unit (CPU) 110, memory 112, local storage 114 and some form of input/output device 116 providing a user interface. The local storage 114 may store the acoustic field data being accessible by the plurality of computers 102, 104, 106, processing in parallel a plurality regions of the image in an efficient manner, or processing in parallel a parallel version of the migration module (M), each individual process being processed by each computer 102, 104, 106.

[0105] The present invention provides a method for solving the uncertainty generated in reservoir geometries mainly due to salt bodies.

[0106] Turning now to FIG. 2, according to the prior art, acoustic field data (AD) is used as the main source data for generating by migration the image (I) of the domain to be explored. The image is the representation of a scalar field, the velocity of propagation, where each pixel/voxel represents the velocity at a location at the discrete domain, the location within the domain of the subsurface associated to said pixel/voxel.

[0107] The migration process is an iterative method providing a sequence of images converging to the numerical approximation of the scalar field corresponding to the velocity of the explored domain. As it has been disclosed in the prior art section, there are well known algorithms allowing an efficient method for migrating the acoustic field data (AD). Even if the convergence properties of the migration module (M) ensures that the image obtained does not depends on the initial values; an approximate image reduces the time processing for reaching the image when convergence criteria is met. Typical convergence criterion is the measurement of the difference between two consecutive images being measured once a certain norm has been predefined.

[0108] Even if the final image is the result of an iterative process repeated until the convergence criterion is met, a certain predefined number of iterations can be carried out. In this particular embodiment, the migration module (M) is a module that can be instantiated within a program wherein the number of iterations is a parameter. When the migration module is called with a number of iterations n, the module only execute n iterations on the image.

[0109] According to this embodiment, this migration module (M) identified in FIG. 2 implementing a method according to the prior art is adapted to iterate on the image by using two steps, a first step determining the correction v and a second step updating the velocity values of the image with the correction v. A particular embodiment of this method according to the prior art, in each iteration the updating process is immediately executed after the first step, that is, after the correction has been determined.

[0110] If artifacts appear in the image during the iteration process from the initial image (10) to the final image (I) by using the acoustic field data (AD), said artifacts cannot be removed by any iterative migration methods known in the prior art.

[0111] A similar migration module (M) is being represented in FIG. 2 in an embodiment of the present invention, shown in the lower part. In this particular case, the migration module (M) is adapted to carry out one or more iterations determining the correction v and, the same migration module (M) is adapted to carry out the updating of the image in a specific manner as it will be disclosed below.

[0112] The explanation of the method represented by the scheme shown in FIG. 2 and according to an embodiment of the present invention will be combined with images shown in FIGS. 3-8.

[0113] In order to build a stable initial velocity model for the sediments and the salt bodies, the starting seismic image (I) is the image obtained by using a migration algorithm using the acoustic field data (AD), for example the final depth interval velocity model provided by any migration algorithm provided by the state of art. The initial image, according to this embodiment is taken as the result of a migration process as shown in FIG. 2.

[0114] FIG. 3 shows an embodiment of initial seismic image (I), this starting seismic image (I) has not the interpreted salt bodies in the right location and is historically plagued with spurious velocities appearing as numerical instabilities being shown as wrinkles surrounding salt bodies or other spurious velocities under salt overhangs. The origin of such anomalous velocities could be related to velocity picking in the time domain, where the presence of salt bodies limits what can be achieved by 1D velocity analysis on semblance panels.

[0115] Seismic image (I) shown in FIG. 3 comprises voxels/pixels representing the velocity of propagation in each location determined by said voxel/pixel. The image uses a color palette for identifying the velocity field. Color palette allows a graphical identification of the velocity of propagation of the rock.

[0116] Salt bodies (SB) are clearly identified as the areas with almost no gradients. Said salt bodies may be identified numerically when the velocity of each pixel/voxel is compared with the propagation velocity stored in a data bases storing rock properties.

[0117] FIGS. 3 to 8 shows an oval highlighting the region located under a salt overhang where the migrated velocities under the overhangs and also the anomalous high velocities observed at the narrow basins in between steeply dipping salt flanks are not accurately determined according to a prior art method. Those high velocity anomalies correspond to unconstrained tomographic velocity updates for geometry.

[0118] A dramatically slowdown is shown in the base of salt for the overhang creating unnaturally high velocities for the deeper part of the section. This harsh slowdown in velocity has no justification and degrades the imaging.

[0119] In order to obtain a good velocity model the initial velocity model is corrected according to an embodiment of the invention.

[0120] Departing from the seismic image (I), salt regions are identified. FIG. 4 is the seismic image (I) showing in black some regions identified as salt bodies (SB). In a preferred embodiment, regions are identified by creating a mask over-imposed over the original image.

[0121] Those pixels-voxels coinciding with the mask are deemed to be comprised within the region defined by the mask.

[0122] FIG. 5 shows a subsequent step wherein the image is separated in three different regions, a first region D1 of salt bodies (SB) already identified in FIG. 4, a second region D2 having artifacts which appears as being the set of pixels/voxels located below region D1. According to another embodiment, the second region D2 having artifacts is expanded including the surroundings of the salt bodies (SB). The rest of pixels/voxels are identified as the third region D3.

[0123] FIG. 5 shows the first region D1 and the second region D2 identified as separated masks, each mask having non-connected regions, and the third region D3 is not represented by an specific mask as it may be identified as the region not being within the mask of D1 or the mask of D2.

[0124] In a further step, pixels/voxels being within the first region D1 and within the second region D2 are removed from the seismic image (I).

[0125] In one embodiment, pixels/voxels being in both regions are disposed freeing the memory. In a preferred embodiment, pixels located within the mask of D1 and D2 are identified by a property value as being removed while said pixels are being kept in memory (112). If this set of pixels/voxels is generated again, the property associated to those pixels/voxels is changed and no additional memory management is needed for disposing and allocating new segments of memory.

[0126] According to an embodiment of the invention, regions being removed are generated by filling pixels/voxels using an interpolation method by using the pixel/voxels values of region D3 ending up with regions D1 and D2 having velocities that do not show high gradients or artifacts that may deteriorate any subsequent iterative migration.

[0127] In a preferred embodiment, interpolation method reproduces a stratigraphic deposition filling region D2 and also region D1 even if said first region D1 comprises salt bodies according to the acoustic field data.

[0128] The seismic image (I) shows rows and columns of pixels if the image is two-dimensional, or vertically stacked planes of voxels if the image is a three-dimensional image. FIG. 6 shows a determined row/plane identified as R/P being extended horizontally.

[0129] This filling process comprises: [0130] for each plane/row of voxels/pixels of the seismic image (I) comprising at least one voxel/pixel removed, interpolate the removed voxels/pixels by using the velocity values of voxels/pixels of the same plane/row corresponding to the at least one region D3 with no salt or artifacts.

[0131] After this process a stratified structure is reproduced with velocities similar to those of the vicinity. In a preferred embodiment, after interpolating the removed pixels/voxels, a smoothing step involving voxels/pixels of the same plane/row is applied, in particular by means of a Natural Neighbor algorithm. This smoothing process damps sharp gradients in the horizontal direction generated in the filling process.

[0132] In a further embodiment, a smoothing step over the entire image (I) is applied. This smoothing process allows a diffusion process wherein the velocity is also propagated vertically reproducing vertical variations even in stratified structures.

[0133] A further embodiment improves the vertical diffusion of the velocity values improving the identification of complex structures not being horizontal. A further smoothing step over the entire seismic image (I) is carried by: [0134] generating a second image with the same number of voxels/pixels, each voxel/pixel having the value 1/v of the corresponding velocity value v of the voxel/pixel of the seismic image (I); [0135] carrying out the smooth step over the second image; [0136] providing the seismic image (I) wherein each voxel/pixel takes the inverse value of the corresponding voxel/pixel of the second image.

[0137] In a preferred embodiment, as defined above, the smoothing step over the entire image is carried out by a damped least square algorithm.

[0138] FIG. 7 shows the final result after filling the removed pixels and after a complete smoothing process. A stratigraphically structure is generated wherein no salt bodies are identified. Such image is not compatible with acoustic field data (AD) as no salt bodies (SB) are located within the image but stratigraphically structure is being reproduced and artifacts have been removed avoiding a deteriorate process for the subsequent steps.

[0139] A further step salt bodies (SB) and regions being susceptible of appearing artifacts are generated in a specific manner by using the migration module (M).

[0140] A velocity correction v is determined by executing one or more iterations of the migration module (M). Migration module (M) computes v but does not update the image as the teachings of the prior art does.

[0141] Only D1 and D3 with no salt or artifacts regions are updated with the velocity correction v and, region D2 is only partially corrected by using a limited velocity correction v. Said limited velocity correction may be expressed as v being (0,1).

[0142] Damping parameter limits the correction applied to region D2 avoiding the appearance of instabilities during the entire iterative process while it allows to converge to the solution according to the acoustic field data (AD).

[0143] FIG. 8 shows the seismic image (I) obtained by carrying out: [0144] the correction generation step and [0145] the updating step with the limited value of the correction iteratively until convergence.

[0146] In a further embodiment the migration module (M) uses a ray stopper algorithm wherein the ray tracing prevents paths crossing the artifacts region D2 when migrating the image for computing the velocity correction. As overhangs provides regions located below that are susceptible of generating artifacts, an specific module (M) using a ray stopper algorithm wherein the ray tracing prevents paths crossing the artifacts region D2 uses acoustic information from the velocity field avoiding information sources causing instabilities.

[0147] The seismic image (I) obtained after convergence provides salt flanks, subsalt sediments, base of salt and pre-salt events continuous and focused.

[0148] According to a further embodiment, as the salt bodies (SB) are focused with a more accurate location, the entire method is repeated correcting the salt bodies (SB) location and their shape.

[0149] FIG. 9 shows an RTM section according to the initial image of FIG. 3. FIG. 10 is the same section migrated according to the method disclosed in this detailed embodiment where the oval encircles the region located below the overhang. The comparison clearly shows the more accurate representation of the velocity field with no instabilities.