A method and apparatus for identifying gas-bearing reservoirs

Abstract

The application discloses a method and device for identifying gas-bearing reservoirs, and the method comprises the following steps: establishing a reservoir longitudinal identification criterion according to well logging data and seismic data of a study area; extracting a plurality of seismic attributes from each seismic survey line in two-dimensional seismic data of the study area; determining optimal seismic attributes from the plurality of seismic attributes through comparative analysis; and determining a favorable reservoir distribution area according to the reservoir longitudinal identification criterion and the optimal seismic attributes.

Description

Technical Field

[0001] This article relates to the field of geophysical technology, and in particular to a method and apparatus for identifying gas-bearing reservoirs. Background Technology

[0002] Tight gas reservoirs are characterized by low permeability, low pressure, low abundance, low production, and strong heterogeneity. Identifying the gas-bearing potential of tight reservoirs using 2D seismic methods is not highly accurate, especially for 2D seismic data. The long acquisition time and low accuracy of the data, coupled with poor seismic data quality, significantly increase the difficulty of identifying tight gas reservoirs using 2D seismic methods. Previous reservoir prediction methods have traditionally employed impedance retrieval, geostatistical inversion, and pre-stack elastic parameter inversion. However, for 2D tight gas reservoirs, the accuracy of traditional reservoir prediction is only about 65%, which is low and fails to accurately determine the spatial distribution of gas-bearing reservoirs, severely impacting the success rate of subsequent well placement.

[0003] Therefore, how to develop an effective method for identifying gas-bearing reservoirs within tight reservoirs is an urgent problem to be solved. Summary of the Invention

[0004] This application provides a method and apparatus for identifying gas-bearing reservoirs. This application establishes a vertical identification standard for reservoirs by combining well logging interpretation and reservoir AVO characteristics. At the same time, based on the pre-stack elastic parameter inversion results and the selected seismic two-dimensional attributes, a favorable gas-bearing area is initially delineated. Then, combined with the vertical identification standard, the favorable reservoir area is determined.

[0005] In a first aspect, this application provides a method for identifying gas-bearing reservoirs, the method comprising:

[0006] Based on well logging and seismic data of the study area, a vertical reservoir identification standard was established;

[0007] Multiple seismic attributes were extracted from each seismic line in the two-dimensional seismic data of the study area;

[0008] The optimal seismic attribute is determined from multiple seismic attributes through comparative analysis;

[0009] The favorable reservoir distribution area is determined based on the reservoir vertical identification criteria and the optimal seismic properties.

[0010] Optionally, the establishment of reservoir vertical identification criteria based on well logging and seismic data of the study area includes:

[0011] Lithological interpretation results were obtained based on well logging curves in the study area;

[0012] Well logging and seismic data were used for well-seismic calibration, and the well logging response characteristics of gas-bearing reservoirs were determined by combining lithological interpretation results.

[0013] Establish a vertical identification standard for gas-bearing reservoirs based on the well logging response characteristics of the identified gas-bearing reservoirs.

[0014] Optionally, before extracting multiple seismic attributes from each seismic line in the two-dimensional seismic data of the study area, the method further includes:

[0015] AVO forward modeling analysis was performed on the seismic gather data of the study area;

[0016] AVO characteristics of gas-bearing reservoirs were determined through AVO forward modeling analysis.

[0017] By comparing the corresponding AVO attribute characteristics in the near, middle, and far offsets of the seismic gather data with the well logging response characteristics, the AVO attribute response characteristics of the gas-bearing reservoir are determined.

[0018] Optionally, the process of establishing reservoir vertical identification criteria is as follows:

[0019] The first seismic reflection characteristics of the gas-bearing reservoir were determined based on the pre-stack inversion results.

[0020] Based on the first seismic reflection characteristics, the AVO attribute response characteristics of the gas-bearing reservoir, and the well logging response characteristics, a vertical identification standard for well logging and seismic data is constructed.

[0021] Optionally, multiple seismic attributes are extracted from each seismic survey line in the two-dimensional seismic data of the study area, including:

[0022] Extract the two-dimensional seismic attributes of each seismic line from the two-dimensional seismic data in the study area;

[0023] Based on the two-dimensional seismic attribute data of each study area, the attribute plane distribution corresponding to each seismic attribute is generated;

[0024] The plane distribution of each seismic attribute was extracted by using pre-stack elastic parameter inversion and sedimentary facies constraints.

[0025] Optionally, the step of determining the optimal seismic attribute from multiple seismic attributes through comparative analysis includes:

[0026] The plane distribution of each seismic attribute is compared with the reservoir of the drilled well.

[0027] The attribute with the highest matching rate is determined as the optimal seismic attribute.

[0028] Optionally, the two-dimensional seismic attributes include: instantaneous amplitude attributes, instantaneous frequency attributes, and instantaneous phase attributes.

[0029] Optionally, determining the favorable reservoir distribution area based on the reservoir vertical identification criteria and optimal seismic attributes includes:

[0030] Based on the spatial distribution determined by pre-stack reservoir inversion, a gas-bearing thickness distribution map is determined;

[0031] Based on the planar distribution map of the optimal seismic attributes combined with the gas-bearing thickness distribution map, the preliminary planar distribution area of ​​the reservoir is determined;

[0032] Based on the vertical identification criteria, the favorable areas of the final reservoir are determined in combination with the preliminary reservoir planar distribution area.

[0033] Secondly, this application also provides an apparatus for identifying gas-bearing reservoirs, characterized in that the apparatus includes: a memory and a processor; the memory is used to store a program for identifying gas-bearing reservoirs, and the processor is used to read and execute the program for identifying gas-bearing reservoirs, and to execute the method described in any of the above embodiments.

[0034] Secondly, this application also provides a computer-readable storage medium storing a data processing program, which is executed by a processor to perform the method for identifying gas-bearing reservoirs as described in any of the above embodiments.

[0035] Compared with related technologies, this application provides a method and apparatus for identifying gas-bearing reservoirs. The method includes: establishing a vertical reservoir identification standard based on well logging data and seismic data of the study area; extracting multiple seismic attributes from each seismic line in the two-dimensional seismic data of the study area; determining the optimal seismic attribute from the multiple seismic attributes through comparative analysis; and determining the favorable reservoir distribution area based on the vertical reservoir identification standard and the optimal seismic attribute. This application establishes a vertical reservoir identification standard by combining well logging interpretation and reservoir AVO characteristics; simultaneously, it preliminarily delineates favorable gas-bearing areas based on pre-stack elastic parameter inversion results and the selected two-dimensional seismic attributes, and then further refines the selection of favorable areas by combining the vertical identification standard.

[0036] Other features and advantages of this application will be set forth in the following description, and will be apparent in part from the description, or may be learned by practicing the application. Other advantages of this application can be realized and obtained by means of the solutions described in the description and the accompanying drawings. Attached Figure Description

[0037] The accompanying drawings are used to provide an understanding of the technical solutions of this application and constitute a part of the specification. They are used together with the embodiments of this application to explain the technical solutions of this application and do not constitute a limitation on the technical solutions of this application.

[0038] Figure 1 This is a flowchart of a method for identifying gas-bearing reservoirs according to an embodiment of this application;

[0039] Figure 2This is a schematic diagram of a device for identifying gas-bearing reservoirs according to an embodiment of this application;

[0040] Figure 3 This is a schematic diagram of a method for identifying gas-bearing reservoirs in an exemplary embodiment;

[0041] Figure 4 This is a schematic diagram of the logging interpretation results of well Su10-70-26 in an exemplary embodiment;

[0042] Figure 5 A composite image of a seismic record in an exemplary embodiment;

[0043] Figure 6 An AVO response analysis diagram in an exemplary embodiment;

[0044] Figure 7 This is a forward modeling diagram of a set of methods in an exemplary embodiment;

[0045] Figure 8 This is a three-overlay profile prediction diagram in an exemplary embodiment;

[0046] Figure 9 This is an exemplary embodiment of the inversion profile taken from the western well of the study area.

[0047] Figure 10 This is an exemplary embodiment of the inversion profile two of the wells on the west side of the study area;

[0048] Figure 11 This is an exemplary embodiment of the inversion profile taken from the well on the east side of the study area.

[0049] Figure 12 This is an exemplary embodiment of the inversion profile two of the well on the east side of the study area;

[0050] Figure 13 This is a planar diagram of wave impedance inversion properties in an exemplary embodiment;

[0051] Figure 14 A planar diagram of dessert attributes in an exemplary embodiment;

[0052] Figure 15 A phase attribute plane diagram in an exemplary embodiment;

[0053] Figure 16 This is a preferred plan view of the gas-bearing favorable area in an exemplary embodiment. Detailed Implementation

[0054] This application describes several embodiments, but these descriptions are exemplary and not restrictive, and it will be apparent to those skilled in the art that many more embodiments and implementations are possible within the scope of the embodiments described herein. Although many possible combinations of features are shown in the drawings and discussed in the detailed description, many other combinations of the disclosed features are also possible. Unless specifically limited, any feature or element of any embodiment may be used in combination with, or may replace, any feature or element of any other embodiment.

[0055] This application includes and contemplates combinations of features and elements known to those skilled in the art. The embodiments, features, and elements disclosed in this application may also be combined with any conventional features or elements to form a unique inventive scheme as defined by the claims. Any feature or element of any embodiment may also be combined with features or elements from other inventive schemes to form another unique inventive scheme as defined by the claims. Therefore, it should be understood that any feature shown and / or discussed in this application may be implemented individually or in any suitable combination. Therefore, the embodiments are not limited except by the limitations imposed by the appended claims and their equivalents. Furthermore, various modifications and changes may be made within the scope of the appended claims.

[0056] Furthermore, in describing representative embodiments, the specification may have presented methods and / or processes as a specific sequence of steps. However, the method or process should not be limited to the specific order of steps described herein, to the extent that it does not depend on such a specific order. As will be understood by those skilled in the art, other sequences of steps are also possible. Therefore, the specific order of steps set forth in the specification should not be construed as a limitation of the claims. Moreover, the claims concerning the method and / or process should not be limited to the steps performed in the written order, and those skilled in the art will readily understand that these orders can be varied and still remain within the spirit and scope of the embodiments of this application.

[0057] This invention provides a method for identifying gas-bearing reservoirs, such as... Figure 1 As shown, the method includes steps S100-S130:

[0058] S100: Establish vertical reservoir identification standards based on well logging and seismic data of the study area;

[0059] S110: Extract multiple seismic attributes from each seismic survey line in the two-dimensional seismic data of the study area;

[0060] S120: Optimal seismic properties are selected through comparative analysis;

[0061] S130: Determine favorable reservoir distribution areas based on reservoir vertical identification criteria and optimal seismic properties.

[0062] In one exemplary embodiment, establishing a reservoir vertical identification standard based on well logging data and seismic data of the study area includes:

[0063] The first step is to obtain lithological profile interpretation results based on the well logging curves in the study area;

[0064] The second step is to perform well-seismic calibration using well logging curves and seismic data, and determine the well logging response characteristics of gas-bearing reservoirs by combining the lithological profile interpretation results.

[0065] In this step, well-seismic calibration is performed. The results of the well-seismic calibration are combined with conventional logging curve data to determine the sensitive logging response of the effective reservoir.

[0066] The third step is to establish a vertical identification standard for the reservoir based on the well logging response characteristics of the identified gas-bearing reservoir.

[0067] In one exemplary embodiment, before extracting multiple seismic attributes from each seismic survey line in the two-dimensional seismic data of the study area, the method further includes:

[0068] AVO forward modeling analysis was performed on the seismic data from the collection sites in the study area;

[0069] AVO characteristics of the reservoir were determined through AVO forward modeling analysis;

[0070] The AVO attribute characteristics of gas-bearing reservoirs were determined by comparing the reservoir AVO attribute characteristics of near-offset, medium-offset, and far-offset offset profiles with the gas-bearing response of well logging.

[0071] In one exemplary embodiment, the process of establishing reservoir vertical identification criteria is as follows:

[0072] The first seismic reflection characteristics of the gas-bearing reservoir were determined based on the pre-stack inversion results.

[0073] Based on the first seismic reflection characteristics, the AVO attribute response characteristics of the gas-bearing reservoir, and the well logging response characteristics, a vertical identification standard for well logging and seismic data is constructed.

[0074] In one exemplary embodiment, multiple seismic attributes are extracted from each seismic survey line in the two-dimensional seismic data of the study area, including:

[0075] The first step is to extract the two-dimensional seismic attributes of each seismic line from the two-dimensional seismic data in the study area;

[0076] In this step, the extracted seismic attributes include instantaneous amplitude attributes, instantaneous frequency attributes, instantaneous phase attributes, wave impedance attributes, sweet spot attributes, phase shift attributes, gene inversion attributes, coherence volume, curvature volume, ant volume, etc.

[0077] The second step is to generate the planar attribute distribution corresponding to each seismic attribute based on the two-dimensional seismic attribute data of each study area.

[0078] The third step involves obtaining the constrained seismic attribute planar distribution by inverting pre-stack elastic parameters and sedimentary facies.

[0079] Different seismic attributes reflect different seismic response characteristics, but there is a lack of constraints that reflect well information and constraints that conform to sedimentary characteristics. In order to make the extracted attributes more accurate, the above two types of information are added to the planar extraction constraints when extracting the planar distribution characteristics of attributes.

[0080] In one exemplary embodiment, the optimal seismic properties are selected through comparative analysis, including:

[0081] The first step is to compare the planar attribute distribution corresponding to each seismic attribute with the drilled reservoir section;

[0082] The second step is to determine the attribute with the highest matching rate as the optimal earthquake attribute.

[0083] In one exemplary embodiment, determining a favorable reservoir distribution area based on reservoir vertical identification criteria and optimal seismic properties includes:

[0084] The first step is to determine the gas-bearing thickness distribution map based on the spatial distribution determined by pre-stack reservoir inversion.

[0085] The second step is to determine the planar distribution based on the optimal seismic attribute planar distribution map combined with the gas-bearing thickness distribution map;

[0086] The third step is to determine the favorable areas of the reservoir based on the vertical identification criteria and the planar distribution.

[0087] Secondly, this application also provides a device for identifying gas-bearing reservoirs, such as... Figure 2 As shown, the device includes a memory and a processor; the memory is used to store a program for identifying gas-bearing reservoirs, and the processor is used to read and execute the program for identifying gas-bearing reservoirs, and to execute the method described in any of the above embodiments.

[0088] Thirdly, this application also provides a computer-readable storage medium storing a data processing program, which is executed by a processor using the method for identifying gas-bearing reservoirs described in any of the above embodiments.

[0089] The method implemented in this application has the following technical effects:

[0090] By analyzing the response characteristics of gas-bearing reservoirs to seismic reflection events and combining them with two-dimensional seismic attribute extraction, a seismic gas-bearing response model and identification criteria are constructed to determine the distribution of gas-bearing reservoirs, identify the dominant zones for gas-bearing reservoir development, summarize the planar distribution patterns of gas-bearing reservoirs, and clarify the potential zones in undeveloped areas. This provides a geophysical theoretical basis for the development of two-dimensional seismic tight gas reservoir gas-bearing prediction technology.

[0091] Example 1

[0092] This example focuses on identifying gas-bearing reservoirs in the southern part of the Su-10 block. The implementation process of identifying gas-bearing reservoirs in the southern part of the Su-10 block using the method described in this application is as follows: Figure 3 As shown:

[0093] The first step is to determine the well logging response of the reservoir.

[0094] In this step, well logging interpretation is performed first. The well logging interpretation results are as follows: Figure 4 The diagram shows the logging interpretation results of well Su10-70-26.

[0095] After well logging interpretation, well-seismic calibration is performed. The results of well-seismic calibration are combined with conventional well logging curve data to determine the sensitive logging response of the effective reservoir.

[0096] Finally, by combining production and testing data, quantitative standards for well logging to identify reservoirs are established to accurately and effectively identify them. For example... Figure 5 The image shows the results of the synthetic seismic record. Using well-seismic calibration, it was determined that in the gas-bearing strata section of the well logging interpretation, the seismic response characteristics are mainly the lower segment of the strong wave peak to the zero phase.

[0097] The second step is the seismic response of the reservoir.

[0098] Forward modeling analysis clearly identified the reservoirs in the study area as Type III AVOs, with amplitudes increasing with offset. Figure 6 As shown in the AVO response analysis diagram, the amplitude increases with the increase of the offset distance.

[0099] like Figure 7 As shown in the forward modeling analysis diagram, it can be seen from the gas-bearing well sections that, in the forward modeling data and as... Figure 8 As shown in the three-layer superimposed profile prediction diagram, it can be clearly seen that where the near-offset weak reflection and far-offset strong reflection phenomenon (i.e., Type III AVO) is obvious in the three profiles, there is a corresponding gas-bearing response in the well. The above analysis shows that reservoirs can be identified by using AVO characteristics.

[0100] Step 3: Construct the gas-bearing reservoir-seismic reflection characteristic response relationship

[0101] Based on the pre-stack elastic parameter inversion results, the spatial distribution of gas-bearing reservoirs is determined. At the same time, combined with the two main seismic reflection characteristics on the west and east sides of the identified study area, a well logging-seismic response model is constructed, and a vertical identification standard is established.

[0102] On the west side of the study area, such as Figure 9 The image shows the inversion profile of the well on the west side of the study area. Figure 10 As shown in the inversion profile 2 of the western well in the study area, it can be seen from these two inversion profiles that the seismic reflection characteristics of the main target layer H8 are two sets of positive phase medium-strong reflection axes with poor continuity. According to the well logging interpretation conclusions and pre-stack inversion results, the gas-bearing reservoirs are mainly distributed between the upper and lower reflection axes, mainly along the near-zero phase distribution, and the development of gas-bearing reservoirs on the lower axis is significantly better than that on the upper axis.

[0103] like Figure 11 As shown in the inversion profile of the well on the east side of the study area, as shown in section one. Figure 12 As shown in the inversion profile 2 on the east side of the study area, it can be seen from these two inversion profiles that the seismic reflection characteristics of the main target layer H8 on the east side of the study area are a set of positive strong phase reflections with good continuity. According to the well logging interpretation conclusions and pre-stack inversion results, the gas-bearing reservoirs are mainly distributed along the zero phase on this reflection axis. The reflection intensity gradually weakens eastward, and the continuity also weakens slightly. The development of gas-bearing reservoirs is significantly reduced or even non-developed.

[0104] Step 4: Determining the relationship between two-dimensional seismic attributes and gas content

[0105] Two-dimensional seismic attributes were extracted line by line for the study area. These attributes were then converted into data patterns, and surface formats were generated for each attribute, resulting in a corresponding attribute planar distribution. The attribute planar distribution for each seismic attribute was compared with the drilled reservoir data; the attribute with the highest matching rate was selected as the optimal seismic attribute. In this study area, the optimal seismic attribute was chosen as the phase attribute. Figure 13 As shown, the wave impedance inversion property planar diagram; Figure 14 As shown, a flat diagram of dessert attributes; as Figure 15 As shown, the phase attribute planar diagram; based on the comparative analysis of the above three diagrams, the optimal seismic attribute is the phase attribute.

[0106] Among the three instantaneous attributes, the instantaneous amplitude mainly highlights the special lithology of the reservoir, while the instantaneous phase is more sensitive to the heterogeneity of the reservoir. Combining the wave impedance inversion attribute that can reflect well information and the pre-stack elastic inversion results, the attribute with the highest consistency rate with well-seismic-sedimentary characteristics is selected, and this attribute is further used to predict the planar distribution characteristics of gas-bearing reservoirs.

[0107] Anomalies in instantaneous amplitude can reflect changes in acoustic impedance difference in the lateral direction, and they are highly correlated with lithology and hydrocarbon accumulation. Changes in instantaneous phase reflect changes in the seismic phase axis, which can be used to identify reservoir heterogeneity. In the Sulige tight gas reservoir, where the heterogeneity is extremely high, this property is more suitable for reflecting the distribution of gas-bearing reservoirs.

[0108] After determining the optimal seismic attributes, the initial reservoir distribution area is determined by using pre-stack elastic parameter inversion and sedimentary facies to extract the constrained attribute plane distribution.

[0109] Fifth, based on the above research, and by combining seismic response characteristics and two-dimensional seismic attributes, the dominant zones for gas-bearing reservoir development are identified and gas-rich areas are selected based on the constructed plan-section identification criteria.

[0110] like Figure 16 As shown, this is a preferred map of gas-bearing favorable areas. Using the established identification criteria, verification was conducted in 10 completed blind wells, achieving an 85% accuracy rate in identifying gas-bearing reservoirs. Using the established tight reservoir gas-bearing evaluation criteria, gas-bearing reservoirs were identified in the southern part of the Su10 block, and reservoir distribution was predicted, with an 82% accuracy rate.

[0111] It will be understood by those skilled in the art that all or some of the steps, systems, or apparatuses disclosed above, and their functional modules / units, can be implemented as software, firmware, hardware, or suitable combinations thereof. In hardware implementations, the division between functional modules / units mentioned above does not necessarily correspond to the division of physical components; for example, a physical component may have multiple functions, or a function or step may be performed collaboratively by several physical components. Some or all components may be implemented as software executed by a processor, such as a digital signal processor or microprocessor, or as hardware, or as an integrated circuit, such as an application-specific integrated circuit (ASIC). Such software may be distributed on a computer-readable medium, which may include computer storage media (or non-transitory media) and communication media (or transient media). As is known to those skilled in the art, the term computer storage media includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, program modules, or other data). Computer storage media include, but are not limited to, RAM, ROM, EEPROM, flash memory or other memory technologies, CD-ROM, digital versatile disc (DVD) or other optical disc storage, magnetic cartridges, magnetic tape, disk storage or other magnetic storage devices, or any other medium that can be used to store desired information and can be accessed by a computer. Furthermore, it is well known to those skilled in the art that communication media typically contain computer-readable instructions, data structures, program modules, or other data in modulated data signals such as carrier waves or other transmission mechanisms, and may include any information delivery medium.

Claims

1. A method for identifying gas-bearing reservoirs, characterized in that, The method includes: Based on well logging and seismic data of the study area, a vertical reservoir identification standard was established; Multiple seismic attributes were extracted from each seismic line in the two-dimensional seismic data of the study area; The optimal seismic attribute is determined from multiple seismic attributes through comparative analysis; The favorable reservoir distribution area is determined based on the reservoir vertical identification criteria and the optimal seismic properties.

2. The method for identifying gas-bearing reservoirs according to claim 1, characterized in that, The establishment of reservoir vertical identification criteria based on well logging and seismic data of the study area includes: Lithological interpretation results were obtained based on well logging curves in the study area; Well logging curves and seismic data were used for well-seismic calibration, and the well logging response characteristics of gas-bearing reservoirs were determined in conjunction with the lithological interpretation results. Establish a vertical identification standard for gas-bearing reservoirs based on the well logging response characteristics of the identified gas-bearing reservoirs.

3. The method for identifying gas-bearing reservoirs according to claim 2, characterized in that, Before extracting multiple seismic attributes from each seismic line in the two-dimensional seismic data of the study area, the method further includes: AVO forward modeling analysis was performed on the seismic gather data of the study area; AVO characteristics of gas-bearing reservoirs were determined through AVO forward modeling analysis. By comparing the corresponding AVO attribute characteristics in the near, middle, and far offsets of the seismic gather data with the well logging response characteristics, the AVO attribute response characteristics of the gas-bearing reservoir are determined.

4. The method for identifying gas-bearing reservoirs according to claim 3, characterized in that, The process of establishing reservoir vertical identification standards is as follows: The seismic reflection characteristics of gas-bearing reservoirs were determined based on the pre-stack inversion results. Based on the seismic reflection characteristics, the AVO attribute response characteristics of the gas-bearing reservoir, and the well logging response characteristics, a vertical identification standard for well logging and seismic events is constructed.

5. The method for identifying gas-bearing reservoirs according to claim 1, characterized in that, The method involves extracting multiple seismic attributes from each seismic survey line in the two-dimensional seismic data of the study area, including: Extract the two-dimensional seismic attributes of each seismic line from the two-dimensional seismic data in the study area; Based on the seismic attribute data of each two-dimensional survey line in the study area, the attribute plane distribution corresponding to each seismic attribute is generated; The plane distribution of each seismic attribute was extracted by using pre-stack elastic parameter inversion and sedimentary facies constraints.

6. The method for identifying gas-bearing reservoirs according to claim 5, characterized in that, The process of determining the optimal seismic attribute from multiple seismic attributes through comparative analysis includes: The plane distribution of each seismic attribute is compared with the reservoir of the drilled well. The attribute with the highest matching rate is determined as the optimal seismic attribute.

7. The method for identifying gas-bearing reservoirs according to claim 6, characterized in that, The two-dimensional seismic attributes include: instantaneous amplitude attribute, instantaneous frequency attribute, and instantaneous phase attribute.

8. The method for identifying gas-bearing reservoirs according to claim 1, characterized in that, The step of determining favorable reservoir distribution areas based on the reservoir vertical identification criteria and the optimal seismic attributes includes: Determine the gas-bearing thickness distribution map based on pre-stack reservoir inversion; Based on the optimal seismic attribute planar distribution map and the gas-bearing thickness distribution map, the preliminary reservoir planar distribution area is determined; Based on the vertical identification criteria, the favorable areas of the final reservoir are determined in combination with the preliminary reservoir planar distribution area.

9. A device for identifying gas-bearing reservoirs, characterized in that, The apparatus includes: a memory and a processor; the memory is used to store a program for identifying gas-bearing reservoirs, and the processor is used to read and execute the program for identifying gas-bearing reservoirs, and to execute the method according to any one of claims 1-8.

10. A computer-readable storage medium having a data processing program stored thereon, the data processing program being executed by a processor as the method for identifying gas-bearing reservoirs according to any one of claims 1-8.

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