Abstract:
A method, including: storing, in a computer storage device, geophysical seismic data that has been separated into a multiple-free component and a multiple contaminated component; performing, with a processor, a first full wavefield inversion process on the multiple-free component of the seismic data, wherein a first subsurface physical property model is generated; determining, with a processor, an extended target reflectivity, wherein the extended target reflectivity includes a reflectivity for each of a plurality of shots; separately performing, with a processor, a second full wavefield inversion process with the multiple contaminated component of the seismic data for each of the plurality of shots using the reflectivity corresponding to each of the plurality of shots, wherein a second subsurface physical property model is generated; and generating, with a processor, multiple-free final subsurface physical property model by combining the first subsurface physical property model and the second subsurface physical property model.

Description:
CROSS-REFERENCE TO RELATED APPLICATION 
       [0001]    This application claims the benefit of U.S. Provisional Patent Application 62/171,114, filed Jun. 4, 2015, entitled METHOD FOR GENERATING MULTIPLE FREE SEISMIC IMAGES, the entirety of which is incorporated by reference herein. 
     
    
     FIELD OF THE INVENTION 
       [0002]    Exemplary embodiments described herein pertain generally to the field of geophysical prospecting, and more particularly to geophysical data processing. An exemplary embodiment can invert unprocessed data that contains multiple reflections through full wavefield inversion (FWI), and generate multiple artifact free seismic images. 
       BACKGROUND 
       [0003]    This section is intended to introduce various aspects of the art, which may be associated with exemplary embodiments of the present invention. This discussion is believed to assist in providing a framework to facilitate a better understanding of particular aspects of the present invention. Accordingly, it should be understood that this section should be read in this light, and not necessarily as admissions of prior art. 
         [0004]    Seismic inversion is a process of extracting subsurface information from the data measured at the surface of the earth acquired during a seismic survey. In a typical seismic survey, seismic waves are generated by a source positioned at desired locations. As the source generated wave propagates through the subsurface, some of the energy reflects from subsurface interfaces and travels back to the receiver locations where it is recorded. The seismic waves that have been reflected once are called primary reflections. In contrast, multiple reflections are the seismic waves that have been reflected more than once before being recorded by the receivers. Multiples can be characterized as (i) free-surface related multiples, and (ii) internal multiples. The former are those multiples that are reflected from the top surface and will disappear if that surface becomes non-reflecting. 
         [0005]      FIG. 1  provides an example of inter-bed multiples. Source  107  emits two seismic waves  100  and  101 .  FIG. 1  depicts how waves  100  and  101  can reflect from reflectors  102 ,  103 , and  104  as they travel to receiver  106 .  FIG. 1  assumes free surface  105 . 
         [0006]      FIG. 2  provides an example of free surface multiples. Source  207  emits two seismic waves  200  and  201 , which are received by receivers  206 .  FIG. 2  depicts how waves  200  and  201  reflect off of reflectors  202 ,  203 , and  204 , and free surface  205 . 
         [0007]    Most seismic imaging methods uses only primary data and treat multiple data as noise (i.e., unwanted features in the data) that needs to be removed during conventional data processing. There are several methods for multiple suppression methods in industry. For example, suppression methods include surface-related multiple elimination (SRME), shallow water demultiple (SWD), model-based water-layer demultiple (MWD), and predictive deconvolution. Those of ordinary skill in the art are familiar with these suppression methods, and further discussion is not needed. However, all of the methods struggle with multiple elimination if the multiple and primary reflections overlap in the recorded seismic data. Furthermore, inadequate application of multiple suppression methods may result in damage to the primary data, rendering it unusable for inversion. All of these methods suffer as multiples and primaries are difficult to separate, data processing can damage primary data, and image quality can be degraded. 
         [0008]    Full waveform inversion (FWI) is a seismic imaging method which can utilize the full seismic record including events that are treated as “noise” by standard inversion algorithms. FWI creates a model which, when used to drive numerical simulation, optimally matches the measured data. The numerical simulations can generate data with or without free-surface-related multiples depending on the free-surface boundary condition. The free-surface boundary condition generates data with surface-related multiples, while the non-reflecting (absorbing) boundary condition allows for generation of data free from surface-related multiples. Internal multiples are present in both types of surface boundary conditions. 
         [0009]    The crux of any FWI algorithm can be described as follows: using a starting subsurface physical property model, synthetic seismic data are generated, i.e. modeled or simulated, by solving the wave equation using a numerical scheme (e.g., finite-difference, finite-element etc.). The term velocity model or physical property model as used herein refers to an array of numbers, typically a 3-D array, where each number, which may be called a model parameter, is a value of velocity or another physical property in a cell, where a subsurface region has been conceptually divided into discrete cells for computational purposes. The synthetic seismic data are compared with the field seismic data and using the difference between the two, an error or objective function is calculated. Using the objective function, a modified subsurface model is generated which is used to simulate a new set of synthetic seismic data. This new set of synthetic seismic data is compared with the field data to generate a new objective function. This process is repeated until the objective function is satisfactorily minimized and the final subsurface model is generated. A global or local optimization method is used to minimize the objective function and to update the subsurface model. 
         [0010]    Numerical simulation can generate data with or without free surface multiples depending on the free surface boundary condition imposed on the top of the subsurface model. The free surface boundary condition yields data with surface-related multiples, while the transparent (absorbing) boundary condition allows for generation of multiple-free data. These two modes of numerical modeling lead to two standard approaches in FWI. 
         [0011]    In a first approach, FWI can utilize input seismic data having undergone some kind of multiple suppression procedure and uses an absorbing boundary condition to model the synthetic data. This approach only suppresses free surface multiples and its success hinges on the multiple suppression techniques. In a second FWI approach, the data still contain surface-related multiples which have to be modeled by using a free-surface boundary condition. 
         [0012]    The second approach saves both time and resources required by conventional multiple processing methods. Furthermore, it ensures that integrity of the data is not compromised. The drawback of the second approach is that it requires an accurate modeling of surface-related multiples. This is extremely difficult for several reasons: (i) residuals in the multiple data are very sensitive to the error in the reflectivity of the primary reflector (e.g., the water bottom reflectivity for the surface related multiple) and (ii) field data might include reflections that cannot be modeled by the given synthetic numerical model (such as elastic affects, attenuation and anisotropy). The most crucial impediment is that even a small data mismatch between the measured and simulated multiples can create undesired multiple artifacts in the image. 
         [0013]    U.S. Pat. No. 7,974,824, the entire contents of which are hereby incorporated by reference, describes the seismic inversion of data containing surface-related multiples. Instead of pre-processing seismic data to remove surface-related multiples, a seismic waveform inversion process enables comparison of simulated seismic data containing surface-related multiples with observed seismic data also containing surface-related multiples. Based on this comparing, a model of a subterranean structure can be iteratively updated. 
         [0014]    Zhang and Schuster (2013) describes a method where least squares migration (LSM) is used to image free-surface multiples where the recorded traces are used as the time histories of the virtual sources at the hydrophones and the surface-related multiples are the observed data. Zhang D. and Schuster G., “Least-squares reverse time migration of multiples,” Geophysics, Vol. 79, S11-S21, 2013, the entire contents of which are hereby incorporated by reference. 
       SUMMARY 
       [0015]    A method, including: storing, in a computer storage device, geophysical seismic data that has been separated into a multiple-free component and a multiple contaminated component; performing, with a processor, a first full wavefield inversion process on the multiple-free component of the seismic data, wherein a first subsurface physical property model is generated; determining, with a processor, an extended target reflectivity, wherein the extended target reflectivity includes a reflectivity for each of a plurality of shots; separately performing, with a processor, a second full wavefield inversion process with the multiple contaminated component of the seismic data for each of the plurality of shots using the reflectivity corresponding to each of the plurality of shots, wherein a second subsurface physical property model is generated; and generating, with a processor, multiple-free final subsurface physical property model by combining the first subsurface physical property model and the second subsurface physical property model. 
         [0016]    The method can further include: creating, with a processor, an image of the subsurface region from the multiple-free final subsurface physical property model. 
         [0017]    The method can further include: using the multiple-free final subsurface physical property model in interpreting a subsurface region for hydrocarbon exploration or production. 
         [0018]    In the method, the extended target reflectivity can be used as a starting model in the second full wavefield inversion process in order to minimize reflections from the target reflector. 
         [0019]    In the method, the target reflector can be a water bottom. 
         [0020]    In the method, the target reflector can be a salt body. 
         [0021]    In the method, the determining can include determining the unique reflectivity of the target reflector for each of the plurality of shots from an iterative inversion of the multiple contaminated component of the seismic data, wherein reflectivity is the only inversion variable. 
         [0022]    In the method, the inversion parameter can be muted everywhere in the iterative inversion but at the target reflector in order to obtain the reflectivity of the target reflector for each shot separately. 
         [0023]    In the method, the extended target reflectivity can be used as a starting model in the second full wavefield inversion process, and the second full wavefield inversion process is applied to the multiple contaminated component of the seismic data. 
         [0024]    In the method, the extended target reflectivity can include a unique reflectivity of the target reflector for each shot. 
     
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         [0025]    While the present disclosure is susceptible to various modifications and alternative forms, specific example embodiments thereof have been shown in the drawings and are herein described in detail. It should be understood, however, that the description herein of specific example embodiments is not intended to limit the disclosure to the particular forms disclosed herein, but on the contrary, this disclosure is to cover all modifications and equivalents as defined by the appended claims. It should also be understood that the drawings are not necessarily to scale, emphasis instead being placed upon clearly illustrating principles of exemplary embodiments of the present invention. Moreover, certain dimensions may be exaggerated to help visually convey such principles. 
           [0026]      FIG. 1  illustrates examples of inter-bed multiples. 
           [0027]      FIG. 2  illustrates examples of free-surface multiples. 
           [0028]      FIG. 3  illustrates an ambiguity in a water-bottom artifact. 
           [0029]      FIG. 4  is an exemplary flow chart of a method embodying the present technological advancement. 
           [0030]      FIG. 5  illustrates data separation into multiple free data and multiple data. 
           [0031]      FIGS. 6A and 6B  compare conventionally processed seismic data to the same seismic data processed according to the present technological advancement. 
           [0032]      FIG. 7  is an image with a water bottom multiple artifact created with a conventional FWI process. 
           [0033]      FIG. 8  is an image with no water bottom multiple artifact created with an embodiment of the present technological advancement. 
       
    
    
     DESCRIPTION OF THE INVENTION 
       [0034]    While the present disclosure is susceptible to various modifications and alternative forms, specific example embodiments thereof have been shown in the drawings and are herein described in detail. It should be understood, however, that the description herein of specific example embodiments is not intended to limit the disclosure to the particular forms disclosed herein, but on the contrary, this disclosure is to cover all modifications and equivalents as defined by the appended claims. It should also be understood that the drawings are not necessarily to scale, emphasis instead being placed upon clearly illustrating principles of exemplary embodiments of the present invention. Moreover, certain dimensions may be exaggerated to help visually convey such principles. 
         [0035]    An exemplary embodiment of the present technological advancement can remove the multiple artifacts caused by given selected reflector(s). In effect, the present technological advancement transforms seismic data into a model of the subsurface with these multiple artifacts removed or suppressed. Embodiments of the present technological advancement do not require a conventional multiple suppression technique. In addition, the present technological advancement can assume that the field data might include constructive noise (such as elastic affects, attenuation affects) that cannot be modeled by the numerical simulation. 
         [0036]    The non-limiting embodiments described below pertain to a workflow for removing artifacts generated by the water bottom multiples. A water bottom multiple is caused by sound waves bouncing twice between the sea surface and the sea bed, wherein the ray paths lie entirely within the water layer. The artifact created in the data by a water bottom multiple is a water bottom multiple artifact. The artifact arises because water has a substantially different acoustic impedance than the earth formations at the bottom of the water (or sea floor). The present technological advancement is not restricted to water bottom multiples and can be extended to other types of multiples caused by any reflector(s). 
         [0037]      FIG. 3  illustrates an ambiguity between the real reflector (water bottom  300 ) and a fake reflector (a reflector that does not exist in the subsurface; water bottom multiple artifact  302 ). The solid line in  FIG. 3  represents that actual path taken by the seismic wave emitted from source  303  and received receiver  304 , which was reflected off of the free surface  305  and the water bottom  300  (the interface of the base of the water and the rock or sediment beneath it). The dashed line represents an ambiguity because the data recorded by the receiver could indicate a presence of fake reflector  302  beneath the water bottom. This ambiguity is the source of an artifact in the data (see, for example,  FIG. 6A ). In  FIG. 3 , only water bottom reflector  300  can create the primary reflection  301 . However, both water bottom  300  and the fake reflector  302  can create the same multiple reflection, thereby creating a dangerous ambiguity that might cause leakage of multiple artifacts into the seismic image. Since the main reflector (water bottom  300 ) cannot create reflections that can match all relevant primary and multiple events, the present technological advancement uses the fake reflector  302  to minimize the residual in the multiples. It is important to note that, even with the help of the fake reflector, the multiple residual is reduced to a minimum; which is not necessarily zero. Once the multiple artifact (the fake reflector) leaks into the inverted model, experience shows that FWI does not remove it completely in the later nonlinear iterations. Thus, it is advantageous that the present technological advancement can remove the multiple artifact. 
         [0038]    To remedy the above-noted ambiguity, when applying FWI to unprocessed data, one of the following approaches can be used. A first approach is to find an effective water bottom reflectivity that matches the multiples and primaries very accurately. This approach is the most desired, but very difficult to accomplish with field data. To find an effective water bottom reflectivity, one needs to know the structure around the water bottom, which is part of the unknown image. However, the most important impediment to the first approach is the difficulty of finding an effective water bottom reflectivity when there is constructive noise in the data. In the presence of constructive noise, there might be no effective water bottom that matches both the primary and multiple reflections accurately for all the shots and all the reflection angles for all shot-receiver pairs (especially for shallow water applications). For this reason, this first approach can only be pursued when the physics of simulation are consistent with field data. The second approach is to remove the multiple residual with optimization techniques by introducing “extra non-physical degrees of freedoms,” which is hereinafter referred to as “extended water-bottom reflectivity,” removing the multiple residual without damaging the primary reflections (or not touching primary residual with the introduced extra degrees of freedom), and inferring the remaining primary reflections using a conventional FWI workflow. The present technological advancement implements this second approach, as discussed below. 
         [0039]    The extended water bottom is described as having non-physical degrees of freedom because the extended water bottom does not represent the true Earth. Rather, as discussed below, unique water bottoms are assumed for each shot, which do not represent the true Earth, and are used as a tool to minimize or eliminate the multiple artifact. 
         [0040]      FIG. 4  illustrates an exemplary method embodying the present technological advancement. Step  401  includes separating the data  500  into two parts: the multiple free part  501  and multiple contaminated part  502  (See  FIG. 5  as an example). The multiple contaminated part is a combination of primary and multiple reflections. The separating can be accomplished by applying a low-pass filter to the seismic signal recordings. The cut-off frequency of the low-pass filter can be selected to be the highest frequency expected to be contained in the primary reflections. The signals output from the low-pass filter contain the primary reflections (e.g.,  501  in  FIG. 5 ) essentially in their entirety and the low-frequency portion of the multiple reflections (e.g.,  502  in  FIG. 5 ). Alternatively, the data separation can be done by first calculating (approximately) the travel time of the multiple reflections, and then windowing the data to isolate the part containing multiple reflections. However, other separation techniques are known to those of ordinary skill in the art and can be used with the present technological advancement. 
         [0041]    Step  402  includes generating a subsurface physical property model from the multiple free part  501  using conventional FWI. FWI is well-known to those of ordinary skill in the art. FWI can utilize an initial geophysical property model, with a free-surface boundary condition, and synthetic data can be generated from the initial geophysical property model. Generating and/or obtaining synthetic data based on an initial geophysical property model is well known to those of ordinary skill in the art. An objective function can be computed by using observed geophysical data and the corresponding synthetic data. A gradient of the cost function, with respect to the subsurface model parameter(s), can be used to update the initial model in order to generate an intermediate model. This iterative process can be repeated until the cost function reaches a predetermined threshold, at which point a subsurface physical property model is obtained. Further details regarding FWI can be found in U.S. Patent Publication 2011/0194379 to Lee et al., the entire contents of which are hereby incorporated by reference. 
         [0042]    Since part  501  is not contaminated with multiples, the conventional FWI process produces a multiple artifact-free image. This FWI inversion would be final if the multiple contaminated data  502  were not mixed with the primary reflection. 
         [0043]    The present technological advancement can extract information from the primaries of part  502  while avoiding the multiples. To suppress the multiple residual in part  502  of the data, the present technological advancement utilizes the extended water bottom reflectivity. To this end, a unique water bottom reflectivity is assigned to each shot; in other words the water bottom reflectivity is extended in the shot dimension. Consequently, use of the extended water bottom reflectivity suppresses the multiple artifact in the inverted models generated by the FWI process. 
         [0044]    In conventional FWI, all shots share the same model, since the material model (or Earth) is unique. In the extended water reflectivity approach of the present technological advancement, the water bottom is not unique to all shots, but each shot is assigned its own water bottom. The rest of the earth model is unique to all shots. 
         [0045]    In step  403 , the final subsurface physical property model obtained in step  402  is used as a starting point to process the multiple contaminated data  502 . 
         [0046]    In step  404 , the water bottom reflectivity is extended in the shot dimension (i.e., each shot has its own water bottom). Preferably, each shot has its own unique water bottom. However, the present technological advancement can be applied to situations where some shots share a water bottom reflectivity. 
         [0047]    In step  405 , an iterative inversion process is applied to part  502  of the data, wherein the iterative inversion process uses the extended water reflectivity as the only inversion variable. This inversion process is analogous to FWI, but at this stage the gradient of a cost function used in this iterative inversion process is muted everywhere but at the extended water bottom to infer for the water bottom reflectivity for each shot separately. In this setup, the FWI type processes minimizes the multiple residual-residual created by multiple reflections-using the extended water bottom reflectivity as the inversion variable. Step  405  yields an extended reflectivity that includes a reflectivity of the water bottom for each shot. Each shot can be processed separately in order to arrive at that shots corresponding reflectivity. 
         [0048]    Next, in step  406 , using the extended reflectivity as the starting model, the remaining residual from part  502 , that is the primary residual-residual created by primary reflections-included within  502 , is inferred using FWI, wherein each shot uses its own inferred water bottom. This inversion is applied to the full multiple contaminated data (not only to the primary reflection), but since this step starts from the extended target reflectivity, the residual due to the multiples is zero, and in affect process it is applied to the primary reflection. Then, the subsurface physical property model obtained in step  402  and the subsurface physical property model obtained in step  406  can be summed to arrive at a final subsurface physical property model. The final subsurface physical property model can be used in interpreting a subsurface region for hydrocarbon exploration or production (e.g., imaging, see  FIG. 8 ). 
         [0049]      FIG. 6A  shows an example of a V p  (velocity of the pressure wave) update using part  502  in a synthetic data test. In  FIG. 6A , the update is done without minimizing the multiple residual, where the update is contaminated with multiples artifact (i.e., the same standard water bottom is used for all shots). In  FIG. 6B , the update is obtained after the multiple residual is minimized through optimizing the extended water bottom per the present technological advancement; hence the update has no multiple artifacts but only updates from primary residuals. Comparing  FIGS. 6A and 6B , one can appreciate that multiple artifact  601  is not present in  FIG. 6B . 
         [0050]      FIG. 6B  is for a single shot S 1 . The shots S 1  . . . S n  can be summed to arrive at a subsurface physical property model that does not include the multiple artifact. 
         [0051]    The final FWI image obtained with conventional FWI ( FIG. 7 ) is contaminated with a water bottom multiple artifact  701 . The FWI image obtained with the present technological advancement ( FIG. 8 ) has no water bottom multiple artifact. 
         [0052]    While the above embodiment pertains to removal of a water bottom multiple artifact, the present technological advancement can be extended to remove a multiple artifact caused by any given reflector(s). Following the workflow described above, the target reflector is extended in the shot direction and this is used as an extra degree of freedom to remove the multiple residual from the data, and then to infer for the remaining primaries with conventional FWI. 
         [0053]    Another application of the present technological advancement is to remove/suppress the multiples caused by salt body interfaces. 
         [0054]    Another application of the present technological advancement is to use the results to manage hydrocarbon production. The subsurface images generated with the present velocity models can be used in the exploration for hydrocarbons and improve geophysical prospecting. As used herein, hydrocarbon management includes hydrocarbon extraction, hydrocarbon production, hydrocarbon exploration, identifying potential hydrocarbon resources, identifying well locations, determining well injection and/or extraction rates, identifying reservoir connectivity, acquiring, disposing of and/or abandoning hydrocarbon resources, reviewing prior hydrocarbon management decisions, and any other hydrocarbon-related acts or activities. 
         [0055]    In all practical applications, the present technological advancement must be used in conjunction with a computer, programmed in accordance with the disclosures herein. Preferably, in order to efficiently perform FWI, the computer is a high performance computer (HPC), known to those skilled in the art. Such high performance computers typically involve clusters of nodes, each node having multiple CPU&#39;s and computer memory that allow parallel computation. The models may be visualized and edited using any interactive visualization programs and associated hardware, such as monitors and projectors. The architecture of system may vary and may be composed of any number of suitable hardware structures capable of executing logical operations and displaying the output according to the present technological advancement. Those of ordinary skill in the art are aware of suitable supercomputers available from Cray or IBM. 
         [0056]    The present techniques may be susceptible to various modifications and alternative forms, and the examples discussed above have been shown only by way of example. However, the present techniques are not intended to be limited to the particular examples disclosed herein. Indeed, the present techniques include all alternatives, modifications, and equivalents falling within the spirit and scope of the appended claims.