Volcanic rock seismic inversion method based on lithofacies constraint, application, device and medium

Abstract

The invention belongs to the technical field of geophysical interpretation, and discloses a volcanic rock seismic inversion method based on lithofacies constraint, an application, a device and a medium, and the method comprises the steps: obtaining a volcanic rock top and bottom reflection interface, carrying out the multi-attribute volcanic rock lithofacies depiction, and building a lithofacies frame model according with a geological law; meanwhile, the seismic inversion process is jointly constrained on the basis of a rock physical analysis result. The device and the computer readable storage medium according to the method can be applied to obtaining the reservoir thickness plane distribution prediction map, so that the volcanic rock seismic inversion result conforms to lithofacies characteristics, the accuracy of the inversion result is higher, and the method and the device are suitable for inversion of the volcanic rock reservoir and reservoir information analysis.

Description

Technical Field

[0001] This invention belongs to the field of geophysical interpretation technology and relates to a seismic inversion method, specifically a volcanic rock seismic inversion method based on lithofacies constraints, as well as its application, device, and medium. Background Technology

[0002] Volcanic rocks are another important reservoir for oil and gas exploration after clastic and carbonate rocks. As a special type of oil and gas reservoir, volcanic rock reservoirs have high exploration and interpretation value. However, due to different geological origins, the internal structure, lithology, and reservoir distribution of volcanic rocks differ greatly from conventional sedimentary rocks. As a representative of event sedimentation, volcanic rocks also exhibit diverse morphologies, large scales, complex superposition relationships, variable lithology and facies, and strong heterogeneity at various levels of tectonic units. Therefore, while conventional seismic inversion techniques based on layered geological models established under the guidance of traditional sedimentary sequence stratigraphy can meet the inversion needs of most sedimentary reservoirs, they are difficult to adapt to the complex geological characteristics and dramatic lateral variations of volcanic strata, failing to achieve satisfactory results. This is especially true in the Sichuan Basin volcanic rock region, where complex topography superimposed on volcanic structures makes the boundaries of geological anomalies in conventional seismic inversion results blurred and ambiguous, leading to low accuracy in seismic data prediction.

[0003] Therefore, conducting volcanic rock facies identification based on regional geological understanding, and using this as a constraint for volcanic rock seismic inversion, is of great significance to the accuracy of volcanic rock seismic prediction. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention aims to provide a volcanic rock seismic inversion method based on lithofacies constraints. By constructing a lithofacies framework model under lithofacies constraints, and then carrying out seismic inversion, the method aims to improve the accuracy of volcanic rock seismic data prediction.

[0005] Another objective of this invention is to provide applications, apparatus, and computer-readable storage media based on the above-described lithofacies-constrained seismic inversion method for volcanic rocks.

[0006] To achieve the above objectives, the technical solution adopted by the present invention is as follows: A lithofacies-constrained seismic inversion method for volcanic rocks includes the following steps performed sequentially: The top and bottom reflection interfaces of volcanic rocks are obtained through seismic stratigraphic calibration and interpretation; By taking the top and bottom reflection interfaces of volcanic rocks and adjusting the geological features, a multi-attribute volcanic rock facies characterization reflecting the sensitive attributes of volcanic rock facies was completed, and a volcanic rock facies distribution map was compiled. The distribution map of volcanic rock facies was used as the lithofacies strata to establish an initial lithofacies framework model. After arbitrary adjustment of the lithofacies boundaries, a lithofacies framework model that conforms to geological laws was established. By analyzing the sensitive parameters of drilling and logging, rock physical analysis results are obtained and used to determine the reservoir identification threshold for seismic inversion. By taking the lithofacies framework model and the rock physics analysis results, and accumulating the vertical thickness through the reservoir identification threshold, the seismic inversion of volcanic rocks based on lithofacies constraints is completed.

[0007] Preferably, by employing model forward modeling combined with geological feature debugging, a multi-attribute volcanic rock facies characterization reflecting the sensitive attributes of volcanic rock facies is completed, and a volcanic rock facies distribution map is compiled.

[0008] As a limitation of the present invention, the volcanic rock top and bottom reflection interface is obtained by extracting wavelets and creating a synthetic seismic record.

[0009] As a further limitation of the present invention, the volcanic rock facies sensitive attributes include volcanic rock eruption facies characteristic attributes, amplitude attributes, frequency attributes, spectrum attributes, and geometric attributes.

[0010] The amplitude-related attributes include root mean square amplitude, absolute amplitude, amplitude kurtosis, total amplitude energy, and instantaneous amplitude. The frequency-related attributes include sweet spot, instantaneous frequency, instantaneous phase, and average quality factor; The spectral attributes include spectral absorption factor, dominant frequency, frequency attenuation, and bandwidth energy. The geometric attributes include coherence, similarity, curvature, and texture attributes.

[0011] As a further definition, the volcanic rock facies sensitive attributes include discontinuous detection attributes in geometric attributes, average energy attributes or root mean square amplitude attributes in amplitude attributes, and volcanic rock seismic facies attributes in seismic facies attributes.

[0012] As a further limitation of the present invention, the arbitrary adjustment of lithofacies boundaries involves extracting arbitrary data that passes through different lithofacies boundaries, determining whether the initial lithofacies framework model conforms to geological laws, and adjusting the initial lithofacies framework model until a lithofacies framework model conforms to geological laws is obtained if it does not conform to geological laws.

[0013] As another limitation of the present invention, after the initial model of the lithofacies framework is arbitrarily adjusted to the lithofacies boundary, it is determined whether it matches the extracted drilling and logging data. If it does not match, the model is adjusted to match, and the lithofacies framework model is obtained.

[0014] The present invention also provides an application of the lithofacies-constrained seismic inversion method for volcanic rocks, which is to use the above-mentioned lithofacies-constrained seismic inversion method for seismic inversion to obtain a predicted map of reservoir thickness distribution in planar shape.

[0015] The present invention also provides an apparatus, which is an electronic device, including a memory and a processor, wherein the memory stores executable instructions; the processor executes the executable instructions in the memory to implement the above-described lithofacies-constrained seismic inversion method for volcanic rocks.

[0016] Furthermore, the device is a computer device.

[0017] The present invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described lithofacies-constrained seismic inversion method for volcanic rocks.

[0018] By adopting the above-described technical solution, the beneficial effects achieved by this invention compared to the prior art are as follows: (1) The lithofacies-constrained seismic inversion method of the present invention solves the problem of fuzzy boundary characterization and multiple solutions of geological anomalies by establishing a lithofacies framework model that conforms to geological laws and using rock physical analysis results to jointly constrain the seismic inversion process. Among them, the rock physics analysis process determines the reservoir identification threshold by seismic inversion of volcanic rocks. By accumulating the vertical thickness through the defined threshold, a more accurate reservoir thickness planar distribution prediction map can be obtained. The process of establishing the lithofacies framework model is based on the lithofacies distribution map of volcanic rocks as the input of lithofacies strata for modeling. By extracting arbitrary data that crosses the boundaries of different lithofacies, the model is repeatedly debugged until the initial lithofacies framework model conforms to geological laws. The model is then adjusted to match the actual drilling and logging data by extracting drilling and logging data.

[0019] (2) The inversion method of the present invention establishes a lithofacies framework model that conforms to lithofacies characteristics, correctly describes the stratigraphic contact relationship and reservoir spatial structure, solves the problem that conventional models used for the inversion of the layered characteristics of clastic rocks cannot be applied to the structural characteristics of mound-shaped or cone-shaped volcanic rocks, so that the seismic inversion results of volcanic rocks conform to lithofacies characteristics and make the inversion results more accurate. It can not only be used to obtain more accurate seismic inversion profiles of volcanic rocks in wells and stacked seismic profile results, but also to obtain more accurate reservoir thickness planar distribution prediction maps.

[0020] (3) The seismic inversion method of volcanic rocks based on lithofacies constraints of the present invention has been effectively used in the prediction of volcanic reservoirs in southwestern Sichuan. It has been applied to drilling targets such as Tianfu 2, 3, 6 and Zhongjiang 1 wells, and has the effects of clearer delineation of geological anomaly boundaries, high analysis efficiency and accurate reservoir prediction results.

[0021] The device and computer-readable storage medium of the present invention can realize seismic inversion of volcanic rocks based on lithofacies constraints, and have the advantages of simple operation, high efficiency, high accuracy of inversion results and low ambiguity. Attached Figure Description

[0022] The present invention will now be described in further detail with reference to the accompanying drawings and specific embodiments.

[0023] Figure 1 This is a schematic diagram of the process of the volcanic rock seismic inversion method based on lithofacies constraints in Embodiment 1 of the present invention; Figure 2 This is a planar diagram showing the sensitive properties of four volcanic rock facies in Embodiment 1 of the present invention; Figure 3 This is a diagram showing the lithofacies distribution of volcanic rocks in Example 1 of the present invention; Figure 4 This is a diagram of the lithofacies framework model in Embodiment 1 of the present invention; Figure 5 This is a cross-plot of the longitudinal wave impedance and porosity of the Permian volcanic rock segment in Embodiment 1 of the present invention; Figure 6 This is a diagram showing the results of the seismic inversion profile overlay of volcanic rock wells in Embodiment 1 of the present invention; Figure 7 This is a predicted planar distribution map of the thickness of volcanic rock reservoirs in Embodiment 1 of the present invention. Detailed Implementation

[0024] The present invention will be further described in detail below with reference to specific embodiments and accompanying drawings. It should be understood that the described embodiments are only used to explain the present invention and do not limit the present invention.

[0025] Example 1: A volcanic rock seismic inversion method based on lithofacies constraints and its application This embodiment utilizes a lithofacies-constrained seismic inversion method for volcanic rocks to invert and predict a Permian volcanic rock segment in the Sichuan Basin, thereby obtaining a predicted reservoir thickness distribution map. The method flow is as follows: Figure 1 As shown, the specific steps include: S1. Seismic horizon marking and interpretation By extracting wavelets and creating synthetic seismic records, the top and bottom reflection interfaces of volcanic rocks can be precisely traced, facilitating subsequent multi-attribute volcanic rock facies characterization, establishment of facies framework models, and seismic inversion within the same domain.

[0026] S2. Four-attribute volcanic rock facies depiction Obtain the three-dimensional discontinuous detection attribute plane map, average energy attribute plane map, root mean square amplitude attribute plane map, and seismic facies attribute plane map of volcanic rocks in the YT1 well area, such as... Figure 2 The above four attributes are used as the sensitive attributes of the volcanic rock facies to be characterized; Take the top and bottom reflection interface of the volcanic rock obtained by S1, and use... Figure 2The four attribute planar maps in the model, through forward modeling and geological feature adjustments, completed the multi-attribute volcanic facies characterization reflecting the sensitive attributes of volcanic rock facies, and compiled a three-dimensional Permian volcanic facies distribution map of the YT1 well area, as shown in the figure. Figure 3 .

[0027] S3. Establish a lithofacies framework model The volcanic rock facies distribution map obtained from S2 is used as the input of the lithofacies strata to establish an initial lithofacies framework model. The framework model is established by editing layer by layer from the bottom up, namely the Maodi, the bottom of the volcanic rock, the boundary of the eruptive facies and the bottom of the Upper Permian. The contact method of the eruptive facies boundary is truncated, while the rest are parallel top and bottom. The initial lithofacies framework model was subjected to arbitrary adjustment of lithofacies boundaries, as detailed below: Arbitrary data passing through different lithofacies boundaries were extracted to determine whether the initial lithofacies framework model conformed to geological laws. It was found that there were cases that did not conform to the distribution of volcanic rock lithofacies. Therefore, it did not conform to geological laws. The initial lithofacies framework model was adjusted by adjusting the lithofacies boundaries or stratigraphic contact mode. For the adjusted initial lithofacies framework model, arbitrary data passing through different lithofacies boundaries were extracted again to determine whether it conformed to geological laws. After repeated adjustments and judgments, the model was found to conform to geological laws. Therefore, the adjusted initial lithofacies framework model is a lithofacies framework model that conforms to geological laws. For lithofacies framework models that conform to geological patterns, it is determined whether they match the extracted drilling and logging data for the area. If discrepancies are found, adjustments are made to the lithofacies patterns interpreted from the drilling and logging data. The model is then repeatedly adjusted until it matches the drilling and logging data for the area, resulting in the final lithofacies framework model. Figure 4 The three types of eruptive facies in the figure are characterized by the aforementioned multi-attribute volcanic rock facies. Type I eruptive facies volcanic rocks have a temporal thickness of 90ms-200ms, with a weak to moderately strong reflection at the top boundary exhibiting poor continuity, and internal regions showing uplift and chaotic reflection. Type II eruptive facies volcanic rocks have a temporal thickness of 50ms-90ms, with a poorly continuous top boundary, internal waveforms showing disturbance and regional uplift, and a wedge-shaped variation in lateral thickness. Effluent facies volcanic rocks have a temporal thickness of 30ms-60ms, with a moderate to strong reflection at the top boundary, and internal regions exhibiting continuous strong axial or layered weak reflection.

[0028] S4. Rock Physical Analysis Based on drilling and logging data within the area, porosity and P-wave impedance samples of the target layer were extracted. Cross-analysis of these two parameters was performed to determine the reservoir identification threshold for seismic inversion as a P-wave impedance of 13400Ω. Sample points with P-wave impedance less than this threshold in the vertical direction were identified as volcanic reservoir development sections, yielding the rock physical analysis results, i.e., as shown below. Figure 5 The intersection diagram of longitudinal wave impedance and porosity.

[0029] S5. Seismic inversion under lithofacies constraints Using the lithofacies framework model obtained in S3 and the rock physical analysis results obtained in S4, vertical thickness accumulation is performed through the reservoir identification threshold to complete the seismic inversion of volcanic rocks based on lithofacies constraints. This yields a stacked seismic profile of the volcanic rock well-to-well seismic inversion, as shown in the image. Figure 6 .Depend on Figure 6 It can be seen that the volcanic reservoir thickness predicted by well-connected seismic inversion matches well logging interpretation results well, and the planar prediction results at well points match the reservoir thickness interpreted by well logging. The seismic inversion using the aforementioned lithofacies framework model more clearly delineates the boundaries of geological anomalies, resolving the issue of multiple interpretations between different lithofacies. The final results show that the vertical and horizontal distribution trends conform to macroscopic geological laws, improving the accuracy and efficiency of volcanic rock prediction.

[0030] Based on the above phased-array seismic inversion, time-domain samples with P-wave impedance less than 13400 m / s*g / cc within the time window of the volcanic rock top and bottom boundaries are extracted. The cumulative thickness is obtained by multiplying these samples by the corresponding point velocity, and a plane distribution prediction map of the volcanic rock reservoir thickness is compiled, as shown below. Figure 7 The predicted results are consistent with the trend of the volcanic rock facies diagram. Therefore, the inversion method of this invention provides clearer characterization of the boundaries of volcanic geological anomalies, higher analysis efficiency, and more accurate reservoir prediction results.

[0031] In other embodiments, depending on the actual situation, the sensitive properties of volcanic rock facies are selected from 3-4 types of volcanic rock eruption facies characteristics, amplitude properties, frequency properties, spectrum properties and geometric properties, all of which can yield good inversion results.

[0032] Example 2: An apparatus for a lithofacies-constrained seismic inversion method for volcanic rocks This embodiment is an electronic device for a volcanic rock seismic inversion method based on lithofacies constraints, including a memory and a processor.

[0033] The memory stores executable instructions; the processor runs the executable instructions in the memory to implement the lithofacies-constrained seismic inversion method for volcanic rocks in Example 1.

[0034] This memory is used to store non-transitory computer-readable instructions. Specifically, the memory may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may, for example, include random access memory (RAM) and / or cache memory. The non-volatile memory may, for example, include read-only memory (ROM), hard disk, flash memory, etc.

[0035] The processor may be a central processing unit (CPU) or other form of processing unit with data processing capabilities and / or instruction execution capabilities, and may control other components in the electronic device to perform desired functions. In one embodiment disclosed in this application, the processor is used to execute computer-readable instructions stored in the memory.

[0036] Those skilled in the art will understand that, in order to solve the technical problem of how to achieve a good user experience, this embodiment may also include well-known structures such as communication buses and interfaces, and these well-known structures should also be included within the protection scope of this disclosure.

[0037] Example 3: A computer-readable storage medium This embodiment provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the lithofacies-constrained seismic inversion method for volcanic rocks in Embodiment 1.

[0038] The computer-readable storage medium stores non-transitory computer-readable instructions thereon. When the non-transitory computer-readable instructions are executed by a processor, all or part of the steps of the methods of the foregoing embodiments are performed.

[0039] The aforementioned computer-readable storage media include, but are not limited to: optical storage media (e.g., CD-ROM and DVD), magneto-optical storage media (e.g., MO), magnetic storage media (e.g., magnetic tape or portable hard drive), media with built-in rewritable non-volatile memory (e.g., memory card), and media with built-in ROM (e.g., ROM cartridge).

[0040] It should be noted that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art can still modify the technical solutions described in the above embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the claims of the present invention.

Claims

1. A lithofacies-constrained volcanic rock seismic inversion method, characterized in that, a volcanic rock top and bottom reflection interface is obtained through seismic horizon calibration and interpretation; the volcanic rock top and bottom reflection interface is taken, and multi-attribute volcanic rock lithofacies delineation reflecting volcanic rock lithofacies sensitive attributes is completed through geological feature adjustment, and a volcanic rock lithofacies distribution map is prepared; the volcanic rock lithofacies distribution map is taken as a lithofacies formation, an initial model of a lithofacies framework is established, and a lithofacies framework model conforming to geological laws is established through arbitrary adjustment of a lithofacies boundary; a petrophysical analysis result is obtained through analysis of drilling and logging sensitive parameters, and is used to determine a reservoir identification threshold for seismic inversion; the lithofacies framework model and the petrophysical analysis result are taken, and vertical thickness accumulation is performed through the reservoir identification threshold, and lithofacies-constrained volcanic rock seismic inversion is completed.

2. The litho-facies constraint-based volcanic inversion method of claim 1, wherein, The volcanic rock top and bottom reflection interface is obtained by extracting a wavelet and making a synthetic seismic record.

3. The litho-facies constrained volcanic inversion method according to claim 1 or 2, characterized in that, The volcanic rock lithofacies sensitive attributes include volcanic rock eruption phase characteristic attributes, amplitude attributes, frequency attributes, spectrum attributes, and geometric attributes.

4. The method of litho-facies constrained volcanic inversion according to claim 3, wherein, The volcanic rock lithofacies sensitive attributes include non-continuity detection attributes in geometric attributes, average energy attributes or root mean square amplitude attributes in amplitude attributes, and volcanic rock seismic facies attributes in seismic facies attributes.

5. The method of litho-facies constrained volcanic inversion according to claim 4, wherein, The arbitrary adjustment of the lithofacies boundary is to extract arbitrary data passing through different lithofacies boundaries, to determine whether the initial model of the lithofacies framework conforms to geological laws, and to adjust the initial model of the lithofacies framework to obtain a lithofacies framework model conforming to geological laws if it does not conform to geological laws.

6. The method of litho-facies constrained volcanic inversion according to claim 1, 2, 4 or 5, wherein, After the initial model of the lithofacies framework is adjusted through the arbitrary adjustment of the lithofacies boundary, it is determined whether it is consistent with the extracted drilling and logging data, and if it is not consistent, the model is adjusted to be consistent to obtain a lithofacies framework model.

7. Use of a lithofacies-constrained volcanic rock seismic inversion method, characterized in that, The lithofacies-constrained volcanic rock seismic inversion method of any one of claims 1-6 is used for seismic inversion to obtain a reservoir thickness plane distribution prediction map.

8. An apparatus, comprising: An electronic device includes a memory and a processor, wherein the memory stores executable instructions; and the processor executes the executable instructions in the memory to implement the lithofacies-constrained volcanic rock seismic inversion method of any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer readable storage medium stores a computer program, which is executed by the processor to implement the lithofacies-constrained volcanic rock seismic inversion method of any one of claims 1-6.

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