A method of blur zone amplitude compensation and medium

Abstract

The application discloses a fuzzy area amplitude compensation method and a medium, and comprises the following steps: S1, depicting a shallow gas spatial distribution range according to amplitude spatial variation characteristics of a target layer; S2, calculating an absorption attenuation coefficient of the target layer according to the amplitude spatial variation characteristics of the target layer; and S3, obtaining a shallow gas absorption attenuation coefficient according to the shallow gas spatial distribution range and the absorption attenuation coefficient of the target layer, and performing fuzzy area amplitude compensation through the shallow gas absorption attenuation coefficient. The application can better meet actual exploration application, match the requirement for amplitude precision in actual exploration, and realize high matching with geological understanding.

Description

Technical Field

[0001] This invention relates to the field of petroleum exploration and development technology, and in particular to a method and medium for amplitude compensation in fuzzy regions. Background Technology

[0002] When shallow gas clouds, diapirs, or other special anomalous structures exist in the strata, the absorption and attenuation effect significantly impacts the propagation of seismic waves in the subsurface medium. This results in a sharp decrease in waveform intensity and a significant narrowing of bandwidth in seismic data acquired in these anomalous areas, manifesting as weak energy, low dominant frequency, and distortion of wavelet morphology, leading to blurred imaging zones. Currently, to improve imaging accuracy in blurred zones, the industry often employs methods such as inverse Q-filtering and Q-shifting to compensate for amplitude and frequency, thereby enhancing image quality. However, since accurate Q-fields are difficult to obtain in actual data, while these methods provide some improvement, the final results still differ significantly from geological understanding, failing to meet the amplitude accuracy requirements of practical exploration and falling short of practical application needs. Summary of the Invention

[0003] The technical problem to be solved by the present invention is to address at least one defect of the related technologies mentioned in the background: it is difficult to meet the amplitude accuracy requirements in actual exploration and there is a certain difference from meeting the actual application. The present invention provides an amplitude compensation method and medium for fuzzy areas.

[0004] The technical solution adopted by this invention to solve its technical problem is: to construct a method for amplitude compensation in a fuzzy region, which includes the following steps:

[0005] S1: Characterize the spatial distribution range of shallow gas based on the spatial variation characteristics of the target layer amplitude;

[0006] S2: Calculate the absorption attenuation coefficient of the target layer based on the spatial variation characteristics of the target layer amplitude;

[0007] S3: Obtain the shallow gas absorption attenuation coefficient based on the spatial distribution range of shallow gas and the absorption attenuation coefficient of the target layer, and use the shallow gas absorption attenuation coefficient to compensate for the amplitude of the fuzzy region.

[0008] In some embodiments, the method further includes the following steps prior to step S1:

[0009] S101: Perform target layer hierarchical interpretation on the time-domain result data volume;

[0010] S102: Extract the root mean square attribute along the target layer from the time-domain result data volume and analyze the spatial variation characteristics of the target layer amplitude.

[0011] In some embodiments, before step S101, the method further includes: performing time-depth transformation on the superimposed data volume based on the average velocity volume of the time-depth transformation to obtain the time-domain result data volume.

[0012] In some embodiments, the overlay data volume is the overlay data volume of pre-stack depth offset results.

[0013] In some embodiments, step S102 includes: meshing the 10×10 interpretation layer of the target layer into a 1×1 interpretation layer on the time-domain result data volume.

[0014] In some embodiments, step S2 includes: calculating the absorption attenuation coefficient of the target layer based on the spatial variation characteristics of the target layer amplitude and the spatial variation law of the target layer amplitude.

[0015] In some embodiments, the method further includes the following steps prior to step S2:

[0016] S201: Forward modeling was carried out using acoustic data from well logging around the fuzzy zone to analyze the seismic response characteristics at well points around the fuzzy zone;

[0017] S202: Characterize the spatial variation law of the target layer amplitude based on the seismic response characteristics obtained from forward modeling.

[0018] In some embodiments, the method further includes the following after step S202:

[0019] Determine whether the spatial variation law of the target layer amplitude meets the preset law. If yes, proceed to step S2; otherwise, proceed to step S102.

[0020] In some embodiments, step S3 includes:

[0021] S31: Edit the absorption attenuation coefficient of the target layer according to the spatial distribution range of shallow gas to obtain the shallow gas absorption attenuation coefficient;

[0022] S32: The amplitude compensation result of the fuzzy region is obtained by performing fuzzy amplitude compensation on the measured data through the shallow gas absorption attenuation coefficient.

[0023] The present invention also provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the aforementioned fuzzy region amplitude compensation method.

[0024] By implementing this invention, the following beneficial effects are achieved:

[0025] This invention acquires time-domain result data, characterizes the spatial distribution range of shallow gas based on the spatial variation characteristics of the target layer amplitude, calculates the absorption attenuation coefficient of the target layer based on the spatial variation characteristics of the target layer amplitude, and finally obtains the shallow gas absorption attenuation coefficient based on the shallow gas spatial distribution range and the target layer absorption attenuation coefficient. The shallow gas absorption attenuation coefficient is used to compensate for the amplitude in the fuzzy area, so as to better meet the actual exploration application, meet the amplitude accuracy requirements in actual exploration, and achieve a high degree of consistency with geological understanding. Attached Figure Description

[0026] The present invention will be further described below with reference to the accompanying drawings and embodiments. In the accompanying drawings:

[0027] Figure 1 A flowchart of one embodiment of the fuzzy region amplitude compensation method of the present invention is shown;

[0028] Figure 2 This diagram shows the effect of performing fuzzy region amplitude compensation on the shallow gas attenuation coefficient before fuzzy region amplitude compensation in one embodiment of the fuzzy region amplitude compensation method of the present invention.

[0029] Figure 3 The diagram shows the effect of fuzzy region amplitude compensation on the shallow gas attenuation coefficient according to an embodiment of the fuzzy region amplitude compensation method of the present invention. Detailed Implementation

[0030] To provide a clearer understanding of the technical features, objectives, and effects of the present invention, specific embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0031] It should be noted that the flowcharts shown in the accompanying drawings are merely illustrative and do not necessarily include all content and operations / steps, nor do they necessarily have to be performed in the described order. For example, some operations / steps can be broken down, while others can be combined or partially combined; therefore, the actual execution order may change depending on the specific circumstances.

[0032] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities can be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor devices and / or microcontroller devices.

[0033] like Figure 1 As shown, some embodiments of the present invention disclose a method for amplitude compensation in a fuzzy region, the method comprising the following steps:

[0034] S1: Characterize the spatial distribution range of shallow gas based on the spatial variation characteristics of the target layer amplitude;

[0035] S2: Calculate the absorption attenuation coefficient of the target layer based on the spatial variation characteristics of the target layer amplitude;

[0036] S3: Obtain the shallow gas absorption attenuation coefficient based on the spatial distribution range of shallow gas and the absorption attenuation coefficient of the target layer, and use the shallow gas absorption attenuation coefficient to compensate for the amplitude of the fuzzy region.

[0037] This invention uses amplitude compensation in the fuzzy region to better meet the actual exploration application, match the amplitude accuracy requirements in actual exploration, and achieve a high degree of consistency with geological understanding.

[0038] In some embodiments, the method further includes the following steps prior to step S1:

[0039] S101: Perform target layer hierarchical interpretation on the time-domain result data volume;

[0040] S102: Extract the root mean square attribute along the target layer from the time-domain result data volume and analyze the spatial variation characteristics of the target layer amplitude.

[0041] Stratigraphic interpretation is the process of identifying the interface locations, attitudes, and spatial distribution of underground strata by analyzing the reflection phase axes on seismic profiles.

[0042] In some embodiments, before step S101, the method further includes: performing time-depth transformation on the superimposed data volume based on the average velocity volume of the time-depth transformation to obtain the time-domain result data volume.

[0043] Mean velocity volumes are typically built based on seismic and well data, including direct measurements based on well data, inversion calculations from seismic data, or velocity modeling methods using geologically constrained layers. These methods allow for the creation of a three-dimensional velocity model that reflects changes in the velocity of the subsurface medium.

[0044] Time-depth conversion is the process of converting seismic data from the time domain (i.e., the vertical scale represents the time corresponding to a two-way trip) to the depth domain (i.e., the depth of the vertical scale). Because the velocity of seismic waves varies with depth when propagating underground, the representation of the same geological body in the time domain and the depth domain are different, thus requiring time-depth conversion.

[0045] In some embodiments, the overlay data volume is the overlay data volume of the pre-stack depth migration result.

[0046] Pre-stack depth migration (PSDM, presagging, shot migration) is a seismic data processing technique primarily used to improve the quality of seismic imaging. The stacked data volume is obtained by adding multiple seismic records from the same geographic location (called common centroid gathers). Its purpose is to enhance the signal and reduce noise, thereby improving the clarity and accuracy of subsurface structure imaging.

[0047] In some embodiments, step S102 includes: meshing the 10×10 interpretation layer of the target layer into a 1×1 interpretation layer on the time-domain result data volume.

[0048] The purpose of gridding is to interpret each seismic trace by corresponding layer. Before gridding, the target layer is 10×10 layers, and there are 9 seismic traces in the middle that do not have corresponding interpretation layers.

[0049] In some embodiments, step S2 includes: calculating the absorption attenuation coefficient of the target layer based on the spatial variation characteristics of the target layer amplitude and the spatial variation law of the target layer amplitude.

[0050] In some embodiments, the method further includes the following steps prior to step S2:

[0051] S201: Forward modeling was carried out using acoustic data from well logging around the fuzzy zone to analyze the seismic response characteristics at well points around the fuzzy zone;

[0052] S202: Characterize the spatial variation law of the target layer amplitude based on the seismic response characteristics obtained from forward modeling.

[0053] Specifically, the spatial variation law of the target layer amplitude is characterized based on geological understanding and seismic response characteristics obtained from forward modeling.

[0054] In some embodiments, step S202 includes: characterizing the spatial variation law of the target layer amplitude based on geological understanding and seismic response characteristics.

[0055] In some embodiments, after step S202, the method further includes: determining whether the spatial variation law of the target layer amplitude meets the preset law; if yes, proceed to step S2; if no, proceed to step S102.

[0056] In some embodiments, step S3 includes:

[0057] S31: Edit the absorption attenuation coefficient of the target layer according to the spatial distribution range of shallow gas to obtain the shallow gas absorption attenuation coefficient;

[0058] S32: The amplitude compensation result of the fuzzy region is obtained by performing fuzzy amplitude compensation on the measured data through the shallow gas absorption attenuation coefficient.

[0059] In some embodiments, before step S3, the method further includes: analyzing the shallow gas thickness on the seismic profile based on the spatial distribution range of shallow gas.

[0060] Step S3 further includes: obtaining the shallow gas absorption attenuation coefficient based on the shallow gas thickness, the shallow gas spatial distribution range, and the target layer absorption attenuation coefficient, and using the shallow gas absorption attenuation coefficient to perform fuzzy region amplitude compensation.

[0061] For example, this embodiment provides a method for amplitude compensation in a fuzzy region. This method is merely an example and is not intended to limit the scope of this application. Other methods may also be used. The specific steps are as follows:

[0062] like Figure 2 As shown, the fuzzy region amplitude compensation method of the present invention is applied to deep-water seismic data. First, pre-stack depth migration results and the average velocity of time-depth conversion are prepared. The depth domain is converted to the time domain. Analysis of the time domain results reveals that due to the influence of shallow air shielding, although the results data have been processed using techniques such as Q-tomography and QPSDM (Q Prestack Depth Migration), fuzzy regions still exist. The energy of these fuzzy regions is weak and they differ significantly from the surrounding strata.

[0063] like Figure 3 As shown, the absorption attenuation coefficient of shallow gas is applied to the target layer to obtain the results after amplitude compensation.

[0064] Some embodiments of the present invention disclose a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, it implements the fuzzy region amplitude compensation method as described in any of the above embodiments, which will not be repeated here.

[0065] It is understood that the above embodiments only illustrate some implementation methods of the present invention, and their descriptions are relatively specific and detailed, but they should not be construed as limiting the scope of the present invention. It should be noted that those skilled in the art can freely combine the above embodiments or technical features without departing from the concept of the present invention, and can also make several modifications and improvements, all of which fall within the protection scope of the present invention. That is, the embodiments described "in some embodiments" can be freely combined with any of the preceding and following embodiments. Therefore, all equivalent transformations and modifications made within the scope of the claims of the present invention should be covered by the claims of the present invention.

Claims

1. A method for amplitude compensation in a fuzzy region, characterized in that, The method includes the following steps: S1: Characterize the spatial distribution range of shallow gas based on the spatial variation characteristics of the target layer amplitude; S2: Calculate the absorption attenuation coefficient of the target layer based on the spatial variation characteristics of the target layer amplitude; S3: Obtain the shallow gas absorption attenuation coefficient based on the spatial distribution range of shallow gas and the absorption attenuation coefficient of the target layer, and use the shallow gas absorption attenuation coefficient to compensate for the amplitude of the fuzzy region.

2. The fuzzy region amplitude compensation method according to claim 1, characterized in that, The procedure preceding step S1 also includes: S101: Perform target layer hierarchical interpretation on the time-domain result data volume; S102: Extract the root mean square attribute along the target layer from the time-domain result data volume and analyze the spatial variation characteristics of the target layer amplitude.

3. The fuzzy region amplitude compensation method according to claim 2, characterized in that, Before step S101, the method further includes: performing time-depth transformation on the superimposed data volume based on the average velocity volume of the time-depth transformation to obtain the time-domain result data volume.

4. The fuzzy region amplitude compensation method according to claim 3, characterized in that, The superimposed data volume is the superimposed data volume of the pre-stack depth migration result.

5. The fuzzy region amplitude compensation method according to claim 2, characterized in that, Step S102 includes: gridding the 10×10 interpretation layer of the target layer into a 1×1 interpretation layer on the time domain result data volume.

6. The fuzzy region amplitude compensation method according to claim 2, characterized in that, Step S2 includes: calculating the absorption attenuation coefficient of the target layer based on the spatial variation characteristics and spatial variation law of the target layer amplitude.

7. The fuzzy region amplitude compensation method according to claim 6, characterized in that, The procedure preceding step S2 also includes: S201: Forward modeling was carried out using acoustic data from well logging around the fuzzy zone to analyze the seismic response characteristics at well points around the fuzzy zone; S202: Characterize the spatial variation law of the target layer amplitude based on the seismic response characteristics obtained from forward modeling.

8. The fuzzy region amplitude compensation method according to claim 7, characterized in that, Following step S202, the following is also included: Determine whether the spatial variation law of the target layer amplitude meets the preset law. If yes, proceed to step S2; otherwise, proceed to step S102.

9. The fuzzy region amplitude compensation method according to claim 1, characterized in that, Step S3 includes: S31: Edit the absorption attenuation coefficient of the target layer according to the spatial distribution range of shallow gas to obtain the shallow gas absorption attenuation coefficient; S32: The amplitude compensation result of the fuzzy region is obtained by performing fuzzy amplitude compensation on the measured data through the shallow gas absorption attenuation coefficient.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the fuzzy region amplitude compensation method as described in any one of claims 1-9.

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