The embodiments relate generally to land and marine seismic exploration and more specifically to systems and methods for implementation of a method of determining and then attenuation true azimuth internal multiples using the three-dimensional (3D) nature of earth's subsurface without apriori knowledge of multiple-generating interfaces.
A widely used technique for searching for oil or gas is the seismic exploration of subsurface geophysical structures. Reflection seismology is a method of geophysical exploration to determine the properties of a portion of a subsurface layer in the earth, which information is especially helpful in the oil and gas industry. Marine-based seismic data acquisition and processing techniques are used to generate a profile (image) of a geophysical structure (subsurface) of the strata underlying the seafloor. This profile does not necessarily provide an accurate location for oil and gas reservoirs, but it may suggest, to those trained in the field, the presence or absence of oil and/or gas reservoirs. Thus, providing an improved image of the subsurface in a shorter period of time is an ongoing process.
The seismic exploration process consists of generating seismic waves (i.e., sound waves) directed toward the subsurface area, gathering data on reflections of the generated seismic waves at interfaces between layers of the subsurface, and analyzing the data to generate a profile (image) of the geophysical structure, i.e., the layers of the investigated subsurface. This type of seismic exploration can be used both on the subsurface of land areas and for exploring the subsurface of the ocean floor.
Marine reflection seismology is based on the use of a controlled source that sends energy waves into the earth, by first generating the energy waves in or on the ocean. By measuring the time it takes for the reflections to come back to one or more receivers (usually very many, perhaps in the order of several dozen, or even hundreds), it is possible to estimate the depth and/or composition of the features causing such reflections. These features may be associated with subterranean hydrocarbon deposits.
For a seismic gathering process, as shown in
Thus, as shown in
The signals recorded by seismic receivers 14 vary in time, having energy peaks that may correspond to reflectors between layers. In reality, since the sea floor and the air/water are highly reflective, some of the peaks correspond to multiple reflections or spurious reflections that should be eliminated before the geophysical structure can be correctly imaged. Primary waves suffer only one reflection from an interface between layers of the subsurface (e.g., first reflected signal 24a). Waves other than primary waves are known as multiples, and more strictly, are events that have undergone more than one reflection. Typically, multiples have a much smaller amplitude than primary reflected waves, because for each reflection, the amplitude decreases proportionally to the product of the reflection coefficients of the different reflectors (usually layers or some sort). As shown in
As illustrated in
As discussed above, the system and method of different aspects of the embodiments are applicable to both marine and land seismic exploration systems.
In operation, source 71 is operated so as to generate a vibro-seismic signal. This signal propagates firstly on the surface of ground 75, in the form of surface waves 74, and secondly in the subsoil, in the form of transmitted ground waves 76 that generate reflected waves 78 when they reach an interface 77 between two geological layers. Each receiver 72 receives both surface wave 74 and reflected wave 78 and converts them into an electrical signal in which are superimposed the component corresponding to reflected wave 78 and the one that corresponds to surface wave 74, the latter of which is undesirable and should be filtered out as much as is practically possible.
As is apparent from
Internal multiple signals 51a and 51b typically arise due to a series of subsurface impedance contrasts. They are commonly observed in seismic data acquired in various places, such as the Santos Basin of Brazil. They are often poorly discriminated from the primaries (i.e., the first, second and third reflected signals, among others), because they have similar movement, dips and frequency bandwidth, thereby making attenuation and/or elimination of internal multiple signals 51a and 51b (as well as surface multiples 50) one of the key issues in providing clear seismic images in interpreting areas of interest. Over time, various methods have been developed to address this difficult problem and most of them rely on the ability to identify the multiple generators.
The acquisition of data in land and marine-based seismic methods usually produces different results in source strength and signature based on differences in near-surface conditions. Further data processing and interpretation of seismic data requires correction of these differences in the early stages of processing. Surface-Related Multiples Elimination (SRME) is a technique commonly used to predict a multiples model from conventional flat streamer data. Attenuating the surface-related multiples is based on predicting a multiples model, adapting the multiples model and subtracting the adapted multiples model from the input streamer data.
Internal multiple attenuation (IMA) has long been regarded as a challenging problem in seismic data processing. In contrast to surface related multiples that have received closer attention from researchers, primarily because of their relatively stronger effects on seismic migrated images and the ease of identifying their generators, internal multiples (IMs) tend to be regarded as a secondary issue even though it has been shown that complicated IMs do interfere with the interpretation of reservoirs (see, Griffiths, M. et al., “Applications of Inter-Bed Multiple Attenuation,” The Leading Edge, 30, 906-912 [2011]; hereinafter “Griffiths”).
Internal multiple attenuation presents a major problem to both the geologist and the geophysicist. For the geologist the amount of noise can often be such that accurate interpretation of the primary seismic wavefield is impossible, making seismic data unusable. For the geophysicist internal multiples are hard to distinguish from the primaries and more difficult to deal with than surface related multiples. In land seismic exploration environments, internal multiples have a dispersed character that creates a curtain of noise often stronger than primaries and are such that move-out discrimination or de-convolution techniques usually fail to eliminate and/or reduce their influence. In marine applications, however, the strength of internal multiples is usually much weaker than that of the primaries.
Recent developments in SRME such as three dimensional (3D) and true-azimuth applications have advanced the technology further (see, Lin, D. et al., 3D “SRME Practice for Better Imaging,” 67th Conference & Technical Exhibition, EAGE, Extended Abstracts, A030 [2005], and Moore, I. et al., “3D Surface-Related Multiple Prediction (SMP): A Case History,” The Leading Edge, 24, 270-274 [2005]). Since applying the concept of SRME to predict IMs is not a new idea, efforts have been spent in extending IMA to 3D applications. Methods based on kinematic calculations using post-stack data (Reshef, M. et al., “3D Prediction of Surface-Related and Inter-Bed Multiples,” Geophysics, 71(1), V1-V6 [2006]), model-driven wavefield extrapolation (Pica, A. et al., “Wave Equation Based Internal Multiple Modeling in 3D,” 78th Meeting, SEG, Expanded Abstracts, 2476-2480 [2008]), and Jakubowicz's (1998) approach (Jakubowicz, H., “Wave Equation Prediction and Removal of Inter-Bed Multiple,” 68th Meeting, SEG, Extended Abstracts, 1527-1530 [1998]), among others, have been proposed. Nevertheless, most of these methods require apriori information about the subsurface. While apriori knowledge of certain sub-surface marine seismic areas is sometimes available, it is the nature of marine seismic exploration to determine sub-surface knowledge of geographical areas of interest that have not yet been explored, in order to determine the suitability, or not, for hydrocarbon mining.
Progress, however, has been made in addressing the need of identifying the multiple-generating interfaces for IMA. Approaches such as an inverse scattering series (see, Weglein, A. B. et al., “An Inverse-Scattering Series Method for Attenuating Multiples in Seismic Reflection Data,” Geophysics, 62, 1975-1989 [1997]), a layer-based method (see, Verschuur, D. J. et al., “Removal of Internal Multiples with the Common-Focus-Point (CFP) Approach: Part 2—Application Strategies and Data Examples,” Geophysics, 70, V61-V72 [2005]), and window-based method (see, Hung, B. et al., “Internal De-multiple Methodology Without Identifying the Multiple Generators,” 82nd Meeting, SEG, Expanded Abstracts [2012]; and Retailleau, M. G. et al., “Advanced 3D Land Internal Multiple Modeling and Subtraction, a WAZ Oman Case Study,” 73rd Conference & Technical Exhibition, EAGE, Extended Abstracts [2011]) have been suggested for predicting IMs without subsurface information. However, besides the work of Retailleau, most of these approaches are limited to two dimensional (2D) applications only. Therefore, the azimuth aspect of the data has not been explicitly considered. El-Emam's article, “Advances in Inter-Bed Multiples Prediction and Attenuation: Case Study From Onshore Kuwait,” mentioned true-azimuth implementation for IMA but their approach applies to suppressing targeted IMs only.
Accordingly, it would be desirable to provide methods, modes and systems for predicting 3D internal multiple in a true-azimuth manner without the subsurface information to assist with internal multiple attenuation.
An object of the embodiments is to substantially solve at least the problems and/or disadvantages discussed above, and to provide at least one or more of the advantages described below.
It is therefore a general aspect of the embodiments to provide a system and method for predicting internal multiples in marine seismic subsurface exploration that will obviate or minimize problems of the type previously described.
According to an embodiment, a method for substantially eliminating true-azimuth three dimensional (3D) internal multiple reflections includes the steps of: defining M upper windows that include a geographical area of interest, and a pair of lower windows that are below the M upper windows, defining a first set of apertures and a second set of apertures, segmenting seismic data to each of said windows using the first and second sets of apertures; and determining a total internal 3D multiple model based on an iteratively generated internal 3D multiple model using the segmented seismic data.
According to another embodiment, a method for substantially eliminating true-azimuth three dimensional (3D) internal multiple reflections includes the steps of defining a set of M upper windows, Wj(N), that corresponds physically to a space below a plurality of receivers and includes a geographical area of interest, defining a pair of lower windows, Wk and Wl, both of which are lower than the upper window, defining a first aperture location with a first set of X and Y dimensions, and defining a second aperture location with a second set of X and Y dimensions, segmenting seismic data to each of windows Wj(N), Wk, and Wl as Dwj(N), Dwk, and Dwl, respectively using the first and second aperture locations, and determining a total internal 3D multiple model based on an iteratively generated internal 3D multiple model M(xr,yr|xs,ys;f)(N) using said segmented data Dwj(N), Dwk, and Dwl.
According to another embodiment, a seismic system for substantially eliminating true-azimuth three dimensional (3D) internal multiple reflections includes a processor configured to: define M upper windows that includes a geographical area of interest, and a pair of lower windows that are below the M upper windows, define a first set of apertures and a second set of apertures, segment seismic data to each of said windows using the first and second sets of apertures, and determine a total internal 3D multiple model based on an iteratively generated internal 3D multiple model using the segmented seismic data.
The above and other objects and features of the embodiments will become apparent and more readily appreciated from the following description of the embodiments with reference to the following figures, wherein like reference numerals refer to like parts throughout the various figures unless otherwise specified, and wherein:
The embodiments are described more fully hereinafter with reference to the accompanying drawings, in which embodiments of the inventive concept are shown. In the drawings, the size and relative sizes of layers and regions may be exaggerated for clarity. Like numbers refer to like elements throughout. The embodiments may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the inventive concept to those skilled in the art. The scope of the embodiments is therefore defined by the appended claims. The following embodiments are discussed, for simplicity, with regard to the terminology and structure of a marine seismic exploration system. However, the embodiments to be discussed next are not limited to these systems but may be applied to other seismic exploration systems that are affected by internal multiples, such as land seismic systems.
Reference throughout the specification to “one embodiment” or “an embodiment” means that a particular feature, structure, or characteristic described in connection with an embodiment is included in at least one embodiment of the embodiments. Thus, the appearance of the phrases “in one embodiment” on “in an embodiment” in various places throughout the specification is not necessarily referring to the same embodiment. Further, the particular feature, structures, or characteristics may be combined in any suitable manner in one or more embodiments.
Used throughout the specification are several acronyms, the meaning of which are provided as follows: universal serial bus (USB); internal multiples (IMs); internal multiple attenuation (IMA); two dimensional (2D); three dimensional (3D); multiple contribution gathers (MCGs); normal move out (NMO); differential normal move out (DNMO); top of salt (TOS); base of salt (BOS); and geographical area of interest (GAI).
As generally discussed above, the main purpose of seismic exploration is to render the most accurate possible graphic representation of specific portions of the Earth's subsurface geologic structure (also referred to as a GAI). The images produced allow exploration companies to accurately and cost-effectively evaluate a promising target (prospect) for its oil and gas yielding potential (i.e., hydrocarbon deposits 44).
Embodiments discussed herein take into account the 3D nature of the earth's subsurface for predicting IMs without identifying the multiple-generating interfaces. In addition, the system and method discussed herein can predict IMs with true-azimuth geometries. Consequently, substantial improvement in image quality can be obtained by including cross-line aperture in the prediction process and selecting traces with correct azimuth in the convolution and correlation processes.
In the following discussions, reference is specifically made to true azimuth 3D internal multiples attenuation in marine seismic exploration systems; however, as discussed above, and those of skill in the art might be expected to appreciate, embodiments thereto are not limited to the same, and apply equally as well to land seismic exploration systems according to an embodiment. Following the work of Jakubowicz in 1998, Griffiths in 2011 extended their 3D SRME workflow to handle IMs by identifying the multiple-generating horizons by muting the input data. As illustrated in
where Dm and Dm′ are the data muted above and below a horizon (e.g. horizon k) just underneath horizon j, respectively (muting being the process of arbitrarily assigning values of zero to certain traces); D*m′ is the complex conjugate of Dm′ and “⊗” represents convolution operation. Two surface apertures, indicated by the dotted rectangles, are needed in this case to locate the two reflection points, I1 and I2, to predict the multiple model Mj (because of the three dimensional aspect, i.e., azimuth, as shown in
Recently, a methodology has been presented for 2D cases in an article entitled “Internal De-multiple Methodology Without Identifying the Multiple Generators,” 82nd Meeting, SEG, Expanded Abstracts [2012], by Hung, B. et al., to predict IMs without subsurface information by segmenting the data into different time windows and iteratively locating the top multiple-generating horizon. According to an embodiment, the same principle can be applied to model 3D IMs without identifying specific multiple-generating horizons. To fulfill the lower-higher-lower relationship (see, Weglein, A. B. et al., “An Inverse-Scattering Series Method for Attenuating Multiples in Seismic Reflection Data,” Geophysics, 62, 1975-1989 [1997]) that is useful in the modeling of IMs, input data within the apertures is segmented into different windows, as shown in
such that wk, wl>wj, and wherein Dwk represents the segmented data that is muted off outside the time window wk and the condition: wk, wl>wj indicates that Dwk and Dwl are the portions of data that have longer travel time than Dwj. An extra summation term in Equation (2) is to ensure that all the possible multiple-generating horizons are taken into account in the process of predicting the IMs.
The term D*w
It can be appreciated by those of skill in the art that in true-azimuth 3D SRME it is important that appropriate traces need to be selected for constructing the multiple contribution gathers (MCGs). Similarly, in true-azimuth 3D internal multiple modelling, it is important to carefully select and interpolate traces to properly account for the aspects of azimuth, offset and midpoint in realizing Equation (2). This stems from the fact that in any given aperture, available traces whose sources 4 and receivers 14 are not located everywhere, but only at the grid points, and hence one needs to carefully select these available traces to reconstruct the required traces, i.e. receiver at (x2,y2) for Dwl, source at (x1,y1) for Dwk and source at (x1,y1) and receiver at (x2,y2) for Dwj, for generating the MCGs. The increase in complexity in this case (i.e., Equation (2)) stems from the fact that two surface apertures are included within which the required traces are reconstructed for contributing to the MCG. To solve this problem, interpolation using normal move-out (NMO) is implemented, as discussed in greater detail below, and especially in regard to
To assist in illustrating the use of interpolation,
As discussed above, however, the traces that are desired to be processed are seldom present in the regularly collected data, meaning that because the apertures generally define a certain physical area, the location within the aperture of the additional shot points is usually between receivers, as they are located at grid points. Depending on the selection criteria of the apertures that may minimize the difference in azimuth, offset and midpoint, or weighted sum of these three, the nearest available traces are extracted from the input 3D shot and receiver gathers, and differential normal move out (NMO) can then be used according to an embodiment for correcting the discrepancy in offset and the resulting trace is rotated about the desired midpoint. In doing so, a trade-off can be made in determining the relative importance of the three terms.
According to an embodiment, the method selects three traces and these are then segmented according to their respective requirements of minimizing the differences in azimuth, offset and midpoint, in ensuring that the low-high-low relationship is fulfilled. According to an embodiment, for non-zero offset traces, the windowing time is calculated based on a different normal move-out equation. Thus, hyperbolic events are assumed. However, it has been determined according to the embodiments, that with less complicated subsurface areas, and the use of overlapping windows, it is valid to assume that all top generators are included in the process.
Turning now to implementation of the system and method of the embodiments using the synthetic data of
In
Following step 108, in which the M upper windows Wj(N) are defined, method 100 proceeds to step 110 in which a counter N is set equal to 1. Those of skill in the art can appreciate that such devices are necessary data processing tools that can be implemented in several different manners, and that the process of iteratively performing a calculation can therefore be accomplished in different manners than described herein. In step 112, which follows step 110, two lower windows (with respect to Wj) are defined, Wk and Wl. In step 114, the two apertures, A1 and A2, are defined in terms of location and dimensions. According to an embodiment, the first aperture A1 is provided with X dimensions ranging from X1(initial) to X1(final), and Y dimensions ranging from Y1(initial) to Y1(final). According to a further embodiment, the second aperture A2 is provided with X dimensions ranging from X2(initial) to X2(final), and Y dimensions ranging from Y2(initial) to Y2(final).
In step 116, the received data is allocated, according to time of arrival, to each of the three windows. According to an embodiment, the two lower windows, Wk and Wl become smaller and smaller with subsequent iterations such that window wj will always be higher than wk and wl. but the upper window will be redefined in time from iteration to iteration of calculation of Equation (2). If, for example, there were 100 windows Wj(N), Wj(1) through Wj(100), then one hundred wavefields would be reconstructed, and enumerated Wj(1) up to Wj(100). As described in greater detail below, in method 100, sets of three segmented sets of data are used in Equation (2)—two that are related to the-always lower windows Wk, Wl, and the upper window Wj (which can and will vary)—to determine a set of 3D internal multiples without subsurface information according to an embodiment. According to a further embodiment, the received data is allocated according to time of receipt, to each of the three windows, such that Dwk is defined as the segmented data that is muted off outside time window Wk; Dwj(N) is defined as the segmented data that is muted off outside time window Wj(N); and Dwl is defined as the segmented data that is muted off outside time window Wl.
Following step 116, method 100 proceeds to step 118, where a determination is made if the segmented trace Dwj(N) exist in the received data. As the apertures are defined to cover certain continuous areas of the ocean surface based, in part of the respective directions of the internal multiples, it is more than likely, if not entirely probable, that an expected location of data does not match the given point of data because there are only so many receivers that are located in known, fixed positions. Therefore, if data is expected at point X1, Y1 in aperture A1, but there is no receiver close enough to that location, extrapolation may have to occur. Therefore, if there is no trace for Dwj(N), then method 100 proceeds from step 118 to step 119 (“No” path from decision step 118) to extrapolate the desired data. Once extrapolation occurs in step 119, method 100 proceeds to step 120. However, in the rare but not entirely impossible situation of the trace being present at the point of receiver 14, that data can be used just as well, such that following “Yes” path from decision step 118, method 100 proceeds from step 118 to step 120 directly.
Step 120 of method 100 performs the iterative calculation of modified Equation (2): the values of each aperture X-Y position value is set to their respective initial values, and for the first iteration, the first set of segmented data, Dwj(N), for the upper window Wj, is used for N=1. Then, as Equation (2) indicates, the summations are calculated for each set of aperture values in turn until a first internal multiple model, M(xr,yr|xs,ys;f)(N), for N=1 is determined. In step 122, the next step in method 100, the newly calculated internal multiple model M(xr,yr|xs,ys;f)(N) is added to the previously determined internal multiple model M(xr,yr|xs,ys;f)(N−1), and kept as total internal multiple model M.
In step 124, N is incremented, then a determination is made to see if all of the muted-off segmented data from the upper window has been used (N=M?) in decision step 126, and if yes, then method 100 proceeds to step 128, wherein the process is complete and a final determination is made of the true data by adding the raw data to the total internal multiple model M. The true data is determined by adding M to the raw data (actually a subtraction, because M(xr,yr|xs,ys;f)(N) is defined as being a negative of the summation), and the result is an actual depiction of the geographical area of interest with multiples reduced and/or substantially eliminated from received raw data. If not all of the muted-off segmented data has been used for the upper window, Wj(N) (“No” path from decision step 126), method 100 returns to step 118 (with N incremented by 1), and again a determination is made, in decision step 118, whether interpolated data is needed for Dwj(N), as discussed above.
In step 120, according to an embodiment, M(xr,yr|xs,ys;f)(N) is calculated according to a modified version of Equation 2, as mentioned above. Equation 2 is modified to remove the left-most summation, so that the calculation of M (wherein M is the total internal multiple model) can be shown in a flow-diagram format; that is, the left-most summation, from Wj(1) to Wj(M) is represented by the iterative loop that computes the other summations for each defined window (discussed above), and the loop indicates that the summations are performed for each defined window according to an embodiment.
According to an embodiment, two criteria must be met in order to use method 100: first, the lower-higher-lower criteria discussed in greater detail above must be presumed to have been met, and second, the window length must be less than the separation between the multiple generators, or sources 4. That is, the window not only has a depth (in time, or meters), but also a distance (again in meters).
Disclosed within is a system and method that can predict 3D internal multiples in marine or land seismic data without requiring a priori information about the subsurface of the earth. It is intended to be used after suppression of surface-related multiples. The system and method first separates the seismic data into different windows based on the travel time of the wavefield from the source to receivers. Apertures are defined to take into account the three dimensional nature of the path of the multiples, and data can be extrapolated if necessary for determination of the influence of the internal multiples at locations where receivers do not actually exist. One method of extrapolation is the use of differential normal move-out. The internal multiple model is determined for as many different positions within the apertures as may be deemed necessary to determine a model with sufficient resolution, the specifications of which are not to be construed as a limiting feature of the embodiments. For each differently defined upper window Wj(n), the summations of the influence of the different traces based on the data in the several different muted-off segmented data is determined in an iterative basis, and then the entire process is repeated for all the different upper windows Wj(N) that have been defined.
Attention is now directed towards
Described herein is a 3D approach according to embodiments that is based on iteratively locating the multiple-generating horizons, while acknowledging the azimuths of the contributing traces so that internal multiples can be more accurately predicted and/or determined. Method 100 has been applied successfully in suppressing complex internal multiples that are generated by closely packed layered salt structures that exhibit significant 3D effects, as seen in
In addition to the above described components, system 200 also comprises user console 234, which can include keyboard 228, display 226, and mouse 230. All of these components are known to those of ordinary skill in the art, and this description includes all known and future variants of these types of devices. Display 226 can be any type of known display or presentation screen, such as liquid crystal displays (LCDs), light emitting diode displays (LEDs), plasma displays, cathode ray tubes (CRTs), among others. User console 235 can include one or more user interface mechanisms such as a mouse, keyboard, microphone, touch pad, touch screen, voice-recognition system, among other inter-active inter-communicative devices.
User console 235, and its components if separately provided, interface with server 201 via server input/output (I/O) interface 222, which can be an RS232, Ethernet, USB or other type of communications port, or can include all or some of these, and further includes any other type of communications means, presently known or further developed. System 200 can further include communications satellite/global positioning system (GPS) transceiver device 238, to which is electrically connected at least one antenna 240 (according to an embodiment, there would be at least one GPS receive-only antenna, and at least one separate satellite bi-directional communications antenna). System 200 can access internet 242, either through a hard wired connection, via I/O interface 222 directly, or wirelessly via antenna 240, and transceiver 238.
Server 201 can be coupled to other computing devices, such as those that operate or control the equipment of ship 2, via one or more networks. Server 201 may be part of a larger network configuration as in a global area network (GAN) (e.g., internet 242), which ultimately allows connection to various landlines.
According to a further embodiment, system 200, being ostensibly designed for use in seismic exploration, will interface with one or more sources 4a,b and one or more receivers 14. These, as previously described, are attached to streamers 6a,b, to which are also attached birds 13a,b that are useful to maintain positioning. As further previously discussed, sources 4 and receivers 14 can communicate with server 201 either through an electrical cable that is part of streamer 6, or via a wireless system that can communicate via antenna 240 and transceiver 238 (collectively described as communications conduit 246).
According to further embodiments, user console 235 provides a means for personnel to enter commands and configuration into system 200 (e.g., via a keyboard, buttons, switches, touch screen and/or joy stick). Display device 226 can be used to show: streamer 6 position; visual representations of acquired data; source 4 and receiver 14 status information; survey information; and other information important to the seismic data acquisition process. Source and receiver interface unit 202 can receive the hydrophone seismic data from receiver 14 though streamer communication conduit 248 (discussed above) that can be part of streamer 6, as well as streamer 6 position information from birds 13; the link is bi-directional so that commands can also be sent to birds 13 to maintain proper streamer positioning. Source and receiver interface unit 202 can also communicate bi-directionally with sources 4 through the streamer communication conduit 248 that can be part of streamer 6. Excitation signals, control signals, output signals and status information related to source 4 can be exchanged by streamer communication conduit 248 between system 200 and source 4.
Bus 204 allows a data pathway for items such as: the transfer and storage of data that originate from either the source sensors or streamer receivers; for processor 208 to access stored data contained in data storage unit memory 232; for processor 208 to send information for visual display to display 226; or for the user to send commands to system operating programs/software 236 that might reside in either the processor 208 or the source and receiver interface unit 202.
System 200 can be used to implement method 100 for determining a true-azimuth 3D internal multiple model without subsurface information according to an embodiment, and for substantially eliminating the influence of said true-azimuth 3D internal multiple reflections in geographical area of interest without the a priori knowledge of subsurface information according to an embodiment according to an embodiment. Hardware, firmware, software or a combination thereof may be used to perform the various steps and operations described herein. According to an embodiment, software 236 for carrying out the above discussed steps can be stored and distributed on multi-media storage devices such as devices 216, 218, 220, 224, 234, and/or 237 (described above) or other form of media capable of portably storing information (e.g., universal serial bus (USB) flash drive 426). These storage media may be inserted into, and read by, devices such as the CD-ROM drive 414, the disk drive 412, among other types of software storage devices.
The above embodiments were discussed without specifying what type of seismic receivers 14 are used to record the seismic data. In this sense, it is known in the art to use, for a marine seismic survey, streamers 6 that are towed by one or more vessels/ships 2 and the streamers 6 include seismic receivers/detectors 14. The streamers 6 can be horizontal or slanted or having a curved profile as illustrated in
The curved streamer 6 of
Further, the above embodiments may be used with multi-level source 60.
The depths z1 to z4 of the source points of the first sub-array 62 can obey various relationships. In one application, the depths of source points 66 increase from head 64a toward the tail 64b of float 64, i.e., z1<z2<z3<z4. In another application, the depths of source points 66 decrease from head 64a to tail 64b of float 66. In another application, source points 66 are slanted, i.e., provided on an imaginary line 68. In still another application, line 68 is a straight line. In yet another application, line 68 is a curved line, e.g., part of a parabola, circle, hyperbola, etc. In one application, the depth of the first source point 66a for the sub-array 62 is about 5 m and the largest depth of the last source point 66d is about 8 m. In a variation of this embodiment, the depth range is between about 8.5 and about 10.5 m or between about 11 and about 14 m. In another variation of this embodiment, when line 68 is straight, the depths of the source points 66 increase by 0.5 m from a first source point to an adjacent source point. Those skilled in the art would recognize that these ranges are exemplary and these numbers may vary from survey to survey. A common feature of all these embodiments is that source points 66 have variable depths so that a single sub-array 62 exhibits multiple-level source points 66.
It should be noted in the embodiments described herein that these techniques can be applied in either an “offline”, e.g., at a land-based data processing center or an “online” manner, i.e., in near real time while on-board the seismic vessel. For example, true azimuth three-dimensional (3D) internal multiples attenuation without apriori knowledge of multiple-generating interfaces can occur as the seismic data is recorded on-board the seismic vessel. In this case, it is possible for internal multiples free-data to be generated as a measure of the quality of the sampling run.
As also will be appreciated by one skilled in the art, the various functional aspects of the embodiments may be embodied in a wireless communication device, a telecommunication network, as a method or in a computer program product. Accordingly, the embodiments may take the form of an entirely hardware embodiment or an embodiment combining hardware and software aspects. Further, the embodiments may take the form of a computer program product stored on a computer-readable storage medium having computer-readable instructions embodied in the medium. Any suitable computer-readable medium may be utilized, including hard disks, CD-ROMs, digital versatile discs (DVDs), optical storage devices, or magnetic storage devices such a floppy disk or magnetic tape. Other non-limiting examples of computer-readable media include flash-type memories or other known types of memories.
Further, those of ordinary skill in the art in the field of the embodiments can appreciate that such functionality can be designed into various types of circuitry, including, but not limited to field programmable gate array structures (FPGAs), application specific integrated circuitry (ASICs), microprocessor based systems, among other types. A detailed discussion of the various types of physical circuit implementations does not substantively aid in an understanding of the embodiments, and as such has been omitted for the dual purposes of brevity and clarity. However, as well known to those of ordinary skill in the art, the systems and methods discussed herein can be implemented as discussed, and can further include programmable devices.
Such programmable devices and/or other types of circuitry as previously discussed can include a processing unit, a system memory, and a system bus that couples various system components including the system memory to the processing unit. The system bus can be any of several types of bus structures including a memory bus or memory controller, a peripheral bus, and a local bus using any of a variety of bus architectures. Furthermore, various types of computer readable media can be used to store programmable instructions. Computer readable media can be any available media that can be accessed by the processing unit. By way of example, and not limitation, computer readable media can comprise computer storage media and communication media. Computer storage media includes volatile and non-volatile as well as removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CDROM, digital versatile disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can be accessed by the processing unit. Communication media can embody computer readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and can include any suitable information delivery media.
The system memory can include computer storage media in the form of volatile and/or non-volatile memory such as read only memory (ROM) and/or random access memory (RAM). A basic input/output system (BIOS), containing the basic routines that help to transfer information between elements connected to and between the processor, such as during start-up, can be stored in memory. The memory can also contain data and/or program modules that are immediately accessible to and/or presently being operated on by the processing unit. By way of non-limiting example, the memory can also include an operating system, application programs, other program modules, and program data.
The processor can also include other removable/non-removable and volatile/non-volatile computer storage media. For example, the processor can access a hard disk drive that reads from or writes to non-removable, non-volatile magnetic media, a magnetic disk drive that reads from or writes to a removable, non-volatile magnetic disk, and/or an optical disk drive that reads from or writes to a removable, non-volatile optical disk, such as a CD-ROM or other optical media. Other removable/non-removable, volatile/non-volatile computer storage media that can be used in the operating environment include, but are not limited to, magnetic tape cassettes, flash memory cards, digital versatile disks, digital video tape, solid state RAM, solid state ROM and the like. A hard disk drive can be connected to the system bus through a non-removable memory interface such as an interface, and a magnetic disk drive or optical disk drive can be connected to the system bus by a removable memory interface, such as an interface.
The embodiments discussed herein can also be embodied as computer-readable codes on a computer-readable medium. The computer-readable medium can include a computer-readable recording medium and a computer-readable transmission medium. The computer-readable recording medium is any data storage device that can store data which can be thereafter read by a computer system. Examples of the computer-readable recording medium include read-only memory (ROM), random-access memory (RAM), CD-ROMs and generally optical data storage devices, magnetic tapes, flash drives, and floppy disks. The computer-readable recording medium can also be distributed over network coupled computer systems so that the computer-readable code is stored and executed in a distributed fashion. The computer-readable transmission medium can transmit carrier waves or signals (e.g., wired or wireless data transmission through the Internet). Also, functional programs, codes, and code segments to, when implemented in suitable electronic hardware, accomplish or support exercising certain elements of the appended claims can be readily construed by programmers skilled in the art to which the embodiments pertains.
The disclosed embodiments provide a source array, computer software, and a method for true azimuth three-dimensional (3D) internal multiples attenuation without apriori knowledge of multiple-generating interfaces according to embodiments. It should be understood that this description is not intended to limit the embodiments. On the contrary, the embodiments are intended to cover alternatives, modifications, and equivalents, which are included in the spirit and scope of the embodiments as defined by the appended claims. Further, in the detailed description of the embodiments, numerous specific details are set forth to provide a comprehensive understanding of the claimed embodiments. However, one skilled in the art would understand that various embodiments may be practiced without such specific details.
Although the features and elements of the embodiments are described in the embodiments in particular combinations, each feature or element can be used alone, without the other features and elements of the embodiments, or in various combinations with or without other features and elements disclosed herein.
This written description uses examples of the subject matter disclosed to enable any person skilled in the art to practice the same, including making and using any devices or systems and performing any incorporated methods. The patentable scope of the subject matter is defined by the claims, and may include other examples that occur to those skilled in the art. Such other examples are intended to be within the scope of the claims.
The above-described embodiments are intended to be illustrative in all respects, rather than restrictive, of the embodiments. Thus the embodiments are capable of many variations in detailed implementation that can be derived from the description contained herein by a person skilled in the art. No element, act, or instruction used in the description of the present application should be construed as critical or essential to the embodiments unless explicitly described as such. Also, as used herein, the article “a” is intended to include one or more items.
All United States patents and applications, foreign patents, and publications discussed above are hereby incorporated herein by reference in their entireties.
The present application is a Continuation Application of U.S. application Ser. No. 14/151,966 filed Jan. 10, 2014 which claims priority under 35 U.S.C. § 119(e) to U.S. Provisional Patent Application No. 61/752,566, filed Jan. 15, 2013, the entire contents of which are expressly incorporated herein by reference.
Number | Date | Country | |
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61752566 | Jan 2013 | US |
Number | Date | Country | |
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Parent | 14151966 | Jan 2014 | US |
Child | 16791443 | US |