Carbonate fracture-cave zone facies-controlled post-stack geostatistical inversion method

Abstract

The application provides a carbonate fracture-cave zone facies-controlled post-stack geostatistics inversion method. The inversion method comprises the following steps: obtaining reservoir and non-reservoir probability data bodies; obtaining cave-type reservoir probability data bodies and fracture-hole-type reservoir probability data bodies; taking the reservoir probability data bodies as three-dimensional lithofacies probability constraints of the fracture-cave zone and taking the non-reservoir probability data bodies as three-dimensional lithofacies probability constraints of the surrounding rock; taking the cave-type reservoir probability data bodies as three-dimensional lithofacies probability constraints of the cave and taking the fracture-hole-type reservoir probability data bodies as three-dimensional lithofacies probability constraints of the fracture hole; performing fracture-cave zone facies-controlled post-stack geostatistics inversion to obtain an inversion P-wave impedance body; using well logging P-wave impedance and porosity crossplot analysis to obtain a P-wave impedance and porosity regression curve; and converting the inversion P-wave impedance body into an inversion porosity body according to the P-wave impedance and porosity regression curve. The application solves the problem of low prediction accuracy of the existing technology for fault-controlled fracture-cave-type carbonate reservoirs.

Description

Technical Field

[0001] This invention relates to the field of reservoir prediction technology, and more specifically, to an inversion method for facies-controlled post-stack geostatistics of carbonate fracture-cavity zones. Background Technology

[0002] Ordovician fault-controlled fracture-vuggy carbonate reservoirs are mainly formed by fractures and karst alteration, with high-quality reservoirs primarily developing within fracture-vuggy zones surrounding the faults. Reservoirs within these zones are broadly classified into three types: cavernous, porous, and fractured. Cavernous reservoirs, with diameters greater than 100 mm, are mostly formed by fractures and karst processes. Wells encountering caverns often experience significant mud loss, drill string runout, and other engineering anomalies. Porous reservoirs refer to dissolution pores that are generally visible to the naked eye, with diameters ranging from 2 mm to 100 mm, appearing as irregular dark spots on imaging logging images. Fractured reservoirs are an important reservoir structure in carbonate rocks and one of the main seepage channels. Genetically, they are mainly classified into three types: tectonic fractures, dissolution fractures, and diagenetic fractures. Cavern, void, and fracture reservoirs do not exist in isolation. Generally, large-scale reservoirs develop alongside smaller-scale reservoirs. For example, cavern reservoirs are usually surrounded by void and fracture reservoirs. These large, medium, and small-scale caverns, voids, and fractures exhibit a "beaded" reflection pattern in seismic data.

[0003] Due to the amplification effect of seismic data, "beaded" reflections are usually a combined response of three types of reservoirs: caverns, pores, and fractures. Therefore, on the one hand, during drilling, although the well may hit the seismic "beads," it may not hit the cavern type reservoir, but only encounter the nearby pore type reservoir. No engineering anomalies such as venting, leakage, or overflow, which are characteristic of high-quality reservoirs, occur, resulting in low production or failure. On the other hand, when estimating the reserves of favorable targets, the three types of reservoirs—cavities, pores, and fractures—included in the "beaded" seismic reflections are calculated in a general way, resulting in low calculation accuracy and large deviations from actual production data.

[0004] As can be seen from the above, the existing technology has the problem of low prediction accuracy for fault-controlled fracture-vuggy carbonate reservoirs. Summary of the Invention

[0005] The main objective of this invention is to provide an inversion method for post-stack geostatistics of fracture-cavity zones in carbonate rocks, in order to solve the problem of low prediction accuracy for fault-controlled fracture-cavity carbonate reservoirs in the prior art.

[0006] To achieve the above objectives, this invention provides a post-stack geostatistical inversion method for fracture-cavity zones in carbonate rocks, comprising: acquiring reservoir probability data volumes and non-reservoir probability data volumes; acquiring cavernous reservoir probability data volumes and fracture-cavity reservoir probability data volumes; using the reservoir probability data volume as a three-dimensional lithofacies probability constraint for the fracture-cavity zone, and using the non-reservoir probability data volume as a three-dimensional lithofacies probability constraint for the surrounding rock; using the cavernous reservoir probability data volume as a cavernous three-dimensional lithofacies probability constraint, and using the fracture-cavity reservoir probability data volume as a fracture-cavity three-dimensional lithofacies probability constraint; performing post-stack geostatistical inversion of the fracture-cavity zone to obtain an inverted P-wave impedance volume; using cross-plot analysis of P-wave impedance and porosity from drilled well logging to obtain a regression curve of P-wave impedance and porosity; and converting the inverted P-wave impedance volume into an inverted porosity volume based on the regression curve of P-wave impedance and porosity.

[0007] Furthermore, obtaining reservoir probability data volumes and non-reservoir probability data volumes includes: extracting structural tensor attribute data volumes that can characterize the spatial distribution features of carbonate fracture-cavity zones based on time-domain post-stack 3D pure wave seismic data volumes; and statistically analyzing the structural tensor attribute values ​​corresponding to drilled wells that have been emptied or lost in the fracture-cavity zones.

[0008] Furthermore, obtaining the reservoir probability data volume and the non-reservoir probability data volume also includes: finding the minimum value of the structural tensor attribute value as the structural tensor attribute value of the fracture-cavity zone profile.

[0009] Furthermore, obtaining reservoir probability data volume and non-reservoir probability data volume also includes: defining the space within the range of structural tensor attribute values ​​greater than or equal to the fracture-cavity zone outline as the fracture-cavity zone, and defining the space within the range of structural tensor attribute values ​​less than the fracture-cavity zone outline as the surrounding rock.

[0010] Furthermore, obtaining the reservoir probability data volume and the non-reservoir probability data volume also includes: setting the probability value of fracture-vuggy zone reservoir development to 0.9 and the probability value of surrounding rock reservoir development to 0.1 to obtain the reservoir probability data volume; subtracting the reservoir probability data volume from the value 1 to obtain the non-reservoir probability data volume.

[0011] Furthermore, obtaining probabilistic data volumes for cavernous and fracture-cavity reservoirs includes: performing sparse pulse inversion using time-domain post-stack 3D pure wave seismic data to obtain inverted P-wave impedance data; and conducting rock physics analysis using drilled wells to obtain the upper limit value of P-wave impedance for cavernous reservoirs.

[0012] Furthermore, obtaining the probability data volume of cavernous reservoirs and fractured-cavity reservoirs also includes: setting the probability value of the portion of the inverted P-wave impedance data volume that is less than or equal to the upper limit of the P-wave impedance of the cavernous reservoir to 1, and otherwise setting the probability value to 0, thus obtaining the probability data volume of the cavernous reservoir.

[0013] Furthermore, obtaining the probability data volume of cavern-type reservoirs and fracture-pore-type reservoirs also includes: setting the probability value of the part with a probability value of 0 in the cavern-type reservoir probability data volume and the part with a probability value of 0.9 in the reservoir probability data volume to 1, and otherwise setting the probability value to 0, to obtain the probability data volume of fracture-pore-type reservoirs.

[0014] Furthermore, before using the probability data volume of cave-type reservoirs as the probability constraint for cave three-dimensional lithofacies and the probability data volume of fracture-pore-type reservoirs as the probability constraint for fracture-pore three-dimensional lithofacies, and before performing post-stack geostatistical inversion of fracture-cavity zone facies to obtain the inverted P-wave impedance volume, the inversion method also includes: conducting rock physical analysis using drilled wells to obtain the P-wave impedance probability density function of cave-type reservoirs, fracture-pore-type reservoirs and surrounding rocks.

[0015] Furthermore, after using the cave-type reservoir probability data volume as the cave three-dimensional lithofacies probability constraint and the fracture-pore-type reservoir probability data volume as the fracture-pore three-dimensional lithofacies probability constraint, and before performing facies-controlled post-stack geostatistical inversion of the fracture-cavity zone to obtain the inverted P-wave impedance volume, the inversion method also includes: extracting the plane attributes of the target layer to obtain the variation function parameters of the cave-type reservoir, the fracture-pore-type reservoir and the surrounding rock.

[0016] The post-stack geostatistical inversion method for fracture-cavity zones in carbonate rocks, applying the technical solution of this invention, includes: acquiring reservoir probability data volumes and non-reservoir probability data volumes; acquiring cavernous reservoir probability data volumes and fracture-cavity reservoir probability data volumes; using the reservoir probability data volume as a three-dimensional lithofacies probability constraint for the fracture-cavity zone, and using the non-reservoir probability data volume as a three-dimensional lithofacies probability constraint for the surrounding rock; using the cavernous reservoir probability data volume as a cavernous three-dimensional lithofacies probability constraint; performing post-stack geostatistical inversion of the fracture-cavity zone to obtain the inverted P-wave impedance volume; and utilizing existing... Cross-plot analysis of P-wave impedance and porosity in drilling logging yields regression curves for P-wave impedance and porosity. Based on these curves, the inverted P-wave impedance volume is transformed into an inverted porosity volume. This approach not only reflects the overall characteristics of the fracture zone but also precisely characterizes each relatively independent fracture-vuggy unit, thereby improving the prediction accuracy of fracture-vuggy carbonate reservoirs. This guides the characterization of fracture-vuggy trap boundaries and the optimization of new well trajectories, increasing reservoir encounter rate and drilling success rate. Simultaneously, it provides fundamental data for precise reserve calculation, solving the problem of low prediction accuracy for fracture-vuggy carbonate reservoirs in existing technologies. Attached Figure Description

[0017] The accompanying drawings, which form part of this application, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an undue limitation of the invention. In the drawings:

[0018] Figure 1 A flowchart illustrating an inversion method for facies-controlled post-stack geostatistics of carbonate fracture-cavity zones according to a specific embodiment of the present invention is shown; and

[0019] Figure 2 A schematic diagram of the probability data of various parts of a carbonate rock mass is shown in a specific embodiment of the present invention;

[0020] Figure 3 Another flowchart of the inversion method for facies-controlled post-stack geostatistics of carbonate rock fracture-cavity zones in a specific embodiment of the present invention is shown;

[0021] Figure 4 A schematic diagram of a reservoir probability data volume is shown in a specific embodiment of the present invention;

[0022] Figure 5 A schematic diagram of a non-reservoir probability data volume is shown in a specific embodiment of the present invention;

[0023] Figure 6 A schematic diagram of a cavernous reservoir probability data volume is shown in a specific embodiment of the present invention;

[0024] Figure 7 A schematic diagram of a fracture-void reservoir probability data volume is shown in a specific embodiment of the present invention;

[0025] Figure 8 A flowchart illustrating the acquisition of probability data for various parts of a carbonate rock mass in a specific embodiment of the present invention is shown.

[0026] Figure 9 A cross-sectional analysis diagram of longitudinal wave impedance and porosity is shown in a specific embodiment of the present invention;

[0027] Figure 10 The diagram illustrates the implementation results of the post-stack geostatistical inversion method for carbonate rock fracture-cavity zones in a specific embodiment of the present invention. Detailed Implementation

[0028] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0029] It should be noted that, unless otherwise specified, all technical and scientific terms used in this application have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains.

[0030] In this invention, unless otherwise stated, directional terms such as "upper," "lower," "top," and "bottom" are generally used in relation to the direction shown in the accompanying drawings, or in relation to the vertical, perpendicular, or gravitational direction of the component itself; similarly, for ease of understanding and description, "inner" and "outer" refer to the inner and outer contours of each component itself, but the above directional terms are not intended to limit this invention.

[0031] Obviously, the embodiments described above are merely some, not all, embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort should fall within the scope of protection of the present invention.

[0032] To address the problem of low prediction accuracy for fault-controlled fracture-vuggy carbonate reservoirs in existing technologies, this invention provides an inversion method based on facies-controlled post-stack geostatistics of carbonate fracture-vuggy zones.

[0033] like Figure 1 and Figure 3 As shown, the post-stack geostatistical inversion method for fracture-cavity zones in carbonate rocks includes: acquiring reservoir probability data volumes and non-reservoir probability data volumes; acquiring cavernous reservoir probability data volumes and fracture-cavity reservoir probability data volumes; using the reservoir probability data volume as a three-dimensional lithofacies probability constraint for the fracture-cavity zone, and using the non-reservoir probability data volume as a three-dimensional lithofacies probability constraint for the surrounding rock; using the cavernous reservoir probability data volume as a three-dimensional lithofacies probability constraint for the cave, and using the fracture-cavity reservoir probability data volume as a three-dimensional lithofacies probability constraint for the fracture; performing post-stack geostatistical inversion of the fracture-cavity zone to obtain the inverted P-wave impedance volume; using cross-plot analysis of P-wave impedance and porosity from drilled well logs to obtain the P-wave impedance and porosity regression curves; and converting the inverted P-wave impedance volume into an inverted porosity volume based on the P-wave impedance and porosity regression curves.

[0034] The post-stack geostatistical inversion method for fracture-cavity zones in carbonate rocks includes: obtaining reservoir probability data volumes and non-reservoir probability data volumes; obtaining cavernous reservoir probability data volumes and fracture-void reservoir probability data volumes; using the reservoir probability data volumes as 3D lithofacies probability constraints for the fracture-cavity zone, and the non-reservoir probability data volumes as 3D lithofacies probability constraints for the surrounding rocks; using the cavernous reservoir probability data volumes as cavernous 3D lithofacies probability constraints, and the fracture-void reservoir probability data volumes as fracture-void reservoir 3D lithofacies probability constraints; and performing post-stack geostatistical inversion of the fracture-cavity zone to obtain... Inverting the P-wave impedance volume; using cross-analysis of P-wave impedance and porosity from drilled wells, regression curves of P-wave impedance and porosity are obtained; based on the regression curves of P-wave impedance and porosity, the inverted P-wave impedance volume is transformed into an inverted porosity volume. This not only reflects the overall characteristics of the fracture zone but also finely characterizes each relatively independent fracture-cavity unit, thereby improving the prediction accuracy of fracture-cavity carbonate reservoirs, guiding the characterization of fracture-cavity trap boundaries and the optimization of new well trajectories, improving reservoir encounter rate and drilling success rate, and providing basic data for precise reserve calculation.

[0035] It should be noted that in the field of oil and gas exploration and development, probability data can be simply understood as possibility. The purpose of oil and gas exploration and development is to find places where reservoirs are developed. However, the accuracy of finding reservoirs is not very high, so probability is used to represent the possibility of reservoir development. The larger the probability value, the greater the possibility of reservoir development, and the more likely it is to become a drilling target.

[0036] In this embodiment, the three-dimensional lithofacies probability constraint can be understood as the defined range of the three-dimensional lithofacies probability.

[0037] In this embodiment, obtaining reservoir probability data and non-reservoir probability data includes: extracting structural tensor attribute data that can characterize the spatial distribution of fracture-cavity zones in carbonate rocks based on time-domain post-stack 3D pure-wave seismic data; and statistically analyzing the structural tensor attribute values ​​corresponding to drilled well venting or loss points on the fracture-cavity zone. Specifically, drill string venting and mud loss typically occur when drilling into fracture-cavity reservoir development areas; therefore, the reservoir attributes at drilled well venting and loss points can be used to reflect the reservoir.

[0038] Furthermore, obtaining the reservoir probability data volume and the non-reservoir probability data volume also includes: finding the minimum value of the structural tensor attribute value as the structural tensor attribute value of the fracture-cavity zone profile.

[0039] In this embodiment, obtaining reservoir probability data volume and non-reservoir probability data volume further includes: defining the space within the range of structural tensor attribute values ​​greater than or equal to the fracture-cavity zone outline as the fracture-cavity zone, and defining the space within the range of structural tensor attribute values ​​less than the fracture-cavity zone outline as the surrounding rock. Specifically, as... Figure 2As shown, carbonate rock masses can be divided into fracture-cavity zones and surrounding rocks. Typically, fracture-cavity zones are reservoir development areas, while the surrounding rocks are non-reservoir areas. Furthermore, fracture-cavity zones can be further divided into cavities and fracture pores.

[0040] like Figures 4 to 5 As shown, obtaining the reservoir probability data volume and the non-reservoir probability data volume also includes: setting the probability value of reservoir development in the fractured-vuggy zone to 0.9 and the probability value of reservoir development in the surrounding rock to 0.1 to obtain the reservoir probability data volume; subtracting the reservoir probability data volume from the value 1 to obtain the non-reservoir probability data volume. Normally, the fractured-vuggy zone is a reservoir development area, and the probability (likelihood) of a reservoir within this spatial range is 1 (100%). However, since the above steps only distinguished between the fractured-vuggy zone and the surrounding rock based on the drainage and leakage of drilled wells, areas that have not been drilled were not included in the statistics. Therefore, here the probability value of reservoir development in the fractured-vuggy zone is set to 0.9, and correspondingly, the probability value of reservoir development in the surrounding rock is 1 - 0.9 = 0.1.

[0041] Furthermore, obtaining probabilistic data volumes for cavernous and fracture-vuggy reservoirs includes: performing sparse pulse inversion on time-domain post-stack 3D pure-wave seismic data to obtain inverted P-wave impedance data; and conducting rock physical analysis using drilled wells to obtain the upper limit of P-wave impedance for cavernous reservoirs. Specifically, sparse pulse inversion is a common reservoir inversion method, which transforms seismic data to obtain parameters reflecting the elasticity of subsurface rocks; this will not be elaborated upon here.

[0042] like Figure 6 As shown, obtaining the probabilistic data volumes for cavernous and fracture-void reservoirs further includes setting the probability value of the portion of the inverted P-wave impedance data volume that is less than or equal to the upper limit of the P-wave impedance for cavernous reservoirs to 1, and otherwise setting the probability value to 0, thus obtaining the probabilistic data volume for cavernous reservoirs. Specifically, the better the reservoir conditions, the smaller the P-wave impedance value. Generally speaking, cavernous reservoirs have the best conditions, followed by fracture-void reservoirs. Through the above rock physical analysis, an upper limit of the P-wave impedance for cavernous reservoirs is defined. The portion less than or equal to this upper limit of the P-wave impedance is a cavernous development zone, and the probability of it being a cavernous reservoir is 1 (100%); the probability of the portion that is not a cavernous development zone being a cavernous reservoir is 0.

[0043] like Figure 7As shown, obtaining the probability data volumes for cavernous and fracture-void reservoirs further includes: setting the probability value of the portion with a probability value of 0 in the cavernous reservoir probability data volume and the portion with a probability value of 0.9 in the reservoir probability data volume to 1; otherwise, setting the probability value to 0, thus obtaining the probability data volume for fracture-void reservoirs. Specifically, based on the above rock physical analysis, an upper limit value for the P-wave impedance of cavernous reservoirs is defined. The portion with a P-wave impedance less than or equal to this upper limit value is a cavernous reservoir, and the portion of the entire reservoir space that is not a cavernous reservoir is a fracture-void reservoir. The portion with a probability value of 0 in a cavernous reservoir represents a fracture-void reservoir, and a fracture-void reservoir must be within the reservoir space, not within a non-reservoir space.

[0044] Furthermore, after using the probabilistic data volume of cavernous reservoirs as the three-dimensional lithofacies probability constraint for caverns and the probabilistic data volume of fractured-void reservoirs as the three-dimensional lithofacies probability constraint for fractured-void reservoirs, and before performing post-stack geostatistical inversion of the fracture-cavity zone to obtain the inverted P-wave impedance volume, the inversion method also includes: conducting rock physical analysis using drilled wells to obtain the P-wave impedance probability density function for cavernous reservoirs, fractured-void reservoirs, and surrounding rocks. Specifically, the role of the P-wave impedance probability density function is to describe the probability of P-wave impedance appearing at a certain value point, that is, to describe the distribution of P-wave impedance values.

[0045] Furthermore, after using the probabilistic data volume of cavernous reservoirs as the probabilistic constraint for three-dimensional lithofacies of caverns, and the probabilistic data volume of fractured-void reservoirs as the probabilistic constraint for three-dimensional lithofacies of fractured-void reservoirs, and before performing post-stack geostatistical inversion of fracture-cavity zones to obtain the inverted P-wave impedance volume, the inversion method also includes: extracting the planar attributes of the target layer to obtain the variogram parameters of cavernous reservoirs, fractured-void reservoirs, and surrounding rocks. Specifically, the variogram is a mathematical function used by the target volume to describe spatial variations.

[0046] In this embodiment, cross-plot analysis of P-wave impedance and porosity from drilled well logging is used to obtain regression curves for P-wave impedance and porosity, thus establishing a functional relationship between P-wave impedance and porosity. Knowing one parameter of either parameter allows the determination of the other. Since the P-wave impedance has already been inverted, porosity can be calculated from the regression curve. Figure 9 As shown.

[0047] The following is a detailed description of the post-stack geostatistical inversion method for carbonate rock fracture-cavity zones according to a specific embodiment of this application.

[0048] Figure 8 A flowchart illustrating the acquisition of probability data for various parts of a carbonate rock mass in a specific embodiment of this application is shown.

[0049] like Figure 8 a to Figure 8 As shown in b, structural tensor attribute data volumes capable of characterizing the spatial distribution of fracture-cavity zones in carbonate rocks are extracted from the time-domain post-stack 3D pure-wave seismic data volume. The structural tensor attribute values ​​corresponding to drilled wells that have emptied or leaked within the fracture-cavity zone are statistically analyzed. The minimum value of the structural tensor attribute values ​​is taken as the structural tensor attribute value of the fracture-cavity zone outline. The space within the range of structural tensor attribute values ​​greater than or equal to the fracture-cavity zone outline is defined as the fracture-cavity zone, and the space within the range of structural tensor attribute values ​​less than the fracture-cavity zone outline is defined as the surrounding rock. Figure 8 As shown in c. The probability value for fracture-vuggy zone reservoir development is set to 0.9, and the probability value for surrounding rock reservoir development is set to 0.1, resulting in a reservoir probability data volume. Subtracting the reservoir probability data volume from the value 1 yields the non-reservoir probability data volume. Sparse pulse inversion is performed using the time-domain post-stack 3D pure wave seismic data volume to obtain the inverted P-wave impedance data volume, as shown in c. Figure 8 As shown in d. Rock physical analysis was conducted using drilled wells to obtain the upper limit of the P-wave impedance of the cavernous reservoir. The probability values ​​of portions of the inverted P-wave impedance data volume that are less than or equal to the upper limit of the P-wave impedance of the cavernous reservoir were set to 1, and the probability values ​​of the rest were set to 0, resulting in the cavernous reservoir probability data volume, as shown in d. Figure 8 As shown in e, the probability values ​​of the portions with a probability of 0 in the cavernous reservoir probability data volume and the portions with a probability value of 0.9 in the reservoir probability data volume are set to 1; otherwise, the probability values ​​are set to 0, thus obtaining the fractured-vuggy reservoir probability data volume, as shown in e. Figure 8 As shown in f.

[0050] Reservoir probabilistic data volumes were used as 3D lithofacies probabilistic constraints for fracture-vuggy zones, and non-reservoir probabilistic data volumes were used as 3D lithofacies probabilistic constraints for surrounding rocks. Similarly, cavernous reservoir probabilistic data volumes were used as cavernous 3D lithofacies probabilistic constraints, and fracture-void reservoir probabilistic data volumes were used as fracture-void reservoir 3D lithofacies probabilistic constraints. Rock physical analysis was conducted using drilled wells to obtain the P-wave impedance probability density functions for cavernous reservoirs, fracture-void reservoirs, and surrounding rocks. Planar properties of the target layer were extracted to obtain the variogram parameters for cavernous reservoirs, fracture-void reservoirs, and surrounding rocks.

[0051] like Figure 9 As shown, a phase-controlled post-stack geostatistical inversion of the fracture-vuggy zone was performed to obtain the inverted P-wave impedance volume. Regression curves of P-wave impedance and porosity were obtained using cross-plot analysis of P-wave impedance and porosity from drilled well logs.

[0052] like Figure 10 As shown, based on the regression curve of longitudinal wave impedance and porosity, the inverted longitudinal wave impedance volume is transformed into an inverted porosity volume, providing basic data for reservoir classification and carving, reserve calculation, etc.

[0053] In one specific embodiment, when a well in the block reached the vicinity of the target point, no good gas logging indications or engineering anomalies such as venting, leakage, or overflow were observed. Inversion was performed using the phase-controlled post-stack geostatistical inversion method for carbonate fracture-cavity zones described in this application. The results showed that the trajectory deviated from the center of the cavernous reservoir by 35m. Based on the inversion results, drilling was performed towards the target reservoir. Subsequently, leakage occurred and 99.92% good gas logging indications were observed. The ignition flame height was 2m-10m, confirming that a cavernous reservoir had been encountered. High production was obtained during testing.

[0054] In another specific embodiment, a certain well in the block produced a cumulative oil production of 34,800 tons and a gas production of 16.19 million cubic meters. The porosity volume was sculpted using both the conventional contour method and the post-stack geostatistical inversion method for carbonate fracture-cavity zones described in this application. A comparison revealed that the absolute deviation between the cumulative production data calculated using the porosity volume sculpted by the inversion method and the actual cumulative production data was 3%, while the absolute deviation between the cumulative production data calculated using the contour method and the actual cumulative production data was 8%. This demonstrates that the results obtained by the inversion method of this application are more reliable than those obtained by the conventional method.

[0055] From the above description, it can be seen that the above embodiments of the present invention achieve the following technical effects: the post-stack geostatistical inversion method for carbonate fracture-cavity zones includes: obtaining reservoir probability data volumes and non-reservoir probability data volumes; obtaining cave-type reservoir probability data volumes and fracture-cavity reservoir probability data volumes; using the reservoir probability data volume as a three-dimensional lithofacies probability constraint for the fracture-cavity zone, and using the non-reservoir probability data volume as a three-dimensional lithofacies probability constraint for the surrounding rock; using the cave-type reservoir probability data volume as a three-dimensional lithofacies probability constraint for the cave, and using the fracture-cavity reservoir probability data volume as a three-dimensional lithofacies probability constraint for the fracture; and performing fracture... Geostatistical inversion of the fracture zone using phase-controlled stacking yields the inverted P-wave impedance volume. Cross-plot analysis of P-wave impedance and porosity from drilled wells is used to obtain regression curves for P-wave impedance and porosity. Based on these regression curves, the inverted P-wave impedance volume is transformed into an inverted porosity volume. This approach not only reflects the overall characteristics of the fracture zone but also precisely characterizes each relatively independent fracture-cavity unit, thereby improving the prediction accuracy of fracture-cavity carbonate reservoirs. This guides the characterization of fracture-cavity trap boundaries and the optimization of new well trajectories, increasing reservoir encounter rate and drilling success rate. Simultaneously, it provides fundamental data for precise reserve calculation.

[0056] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the exemplary embodiments according to this application. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Furthermore, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0057] It should be noted that the terms "first," "second," etc., used in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in sequences other than those illustrated or described herein.

[0058] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. 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 present invention.

Claims

1. A post-stack geostatistical inversion method for fracture-cavity zones in carbonate rocks, characterized in that, include: Acquire reservoir probability data volumes and non-reservoir probability data volumes; Obtain probabilistic data volumes for cavernous reservoirs and fractured-void reservoirs; The reservoir probability data volume is used as a three-dimensional lithofacies probability constraint for the fracture-cavity zone, and the non-reservoir probability data volume is used as a three-dimensional lithofacies probability constraint for the surrounding rock. The cave-type reservoir probability data volume is used as the cave three-dimensional lithofacies probability constraint, and the fracture-pore-type reservoir probability data volume is used as the fracture-pore three-dimensional lithofacies probability constraint. Phase-controlled post-stack geostatistical inversion of the fracture-cavity zone was performed to obtain the inverted P-wave impedance volume; By using the cross-plot analysis of P-wave impedance and porosity from drilled wells, regression curves of P-wave impedance and porosity were obtained. Based on the longitudinal wave impedance and porosity regression curve, the inverted longitudinal wave impedance volume is converted into an inverted porosity volume; The acquisition of reservoir probability data volume and non-reservoir probability data volume includes: Structural tensor attribute data volume capable of characterizing the spatial distribution of carbonate rock fracture-cavity zones was extracted from the time-domain post-stack 3D pure wave seismic data volume. Statistical tensor attribute values ​​corresponding to drilled wells that have been emptied or leaked in the fracture zone; The acquisition of reservoir probability data volume and non-reservoir probability data volume also includes: The minimum value of the structural tensor attribute is taken as the structural tensor attribute value of the slit strip contour; The acquisition of reservoir probability data volume and non-reservoir probability data volume also includes: The space within the range of structural tensor attribute values ​​greater than or equal to the contour of the fracture zone is defined as the fracture zone, and the space within the range of structural tensor attribute values ​​less than the contour of the fracture zone is defined as the surrounding rock.

2. The method for post-stack geostatistical inversion of carbonate rock fracture-cavity zones according to claim 1, characterized in that, The acquisition of reservoir probability data volume and non-reservoir probability data volume also includes: The probability value of fractured-vuggy zone reservoir development was set to 0.9, and the probability value of surrounding rock reservoir development was set to 0.1, thus obtaining the reservoir probability data body; Subtracting the reservoir probability data volume from the value 1 yields the non-reservoir probability data volume.

3. The post-stack geostatistical inversion method for carbonate rock fracture-cavity zones according to claim 2, characterized in that, The acquisition of probabilistic data volumes for cavernous reservoirs and fractured-vuggy reservoirs includes: Sparse pulse inversion was performed using time-domain post-stack 3D pure wave seismic data volume to obtain inverted P-wave impedance data volume; Rock physics analysis was conducted using drilled wells to obtain the upper limit of the longitudinal wave impedance of cavernous reservoirs.

4. The post-stack geostatistical inversion method for carbonate rock fracture-cavity zones according to claim 3, characterized in that, The acquisition of probabilistic data volumes for cavernous reservoirs and fractured-vuggy reservoirs also includes: The probability value of the portion of the inverted P-wave impedance data volume that is less than or equal to the upper limit of the P-wave impedance of the cavernous reservoir is set to 1, and the probability value is set to 0 otherwise, thus obtaining the cavernous reservoir probability data volume.

5. The post-stack geostatistical inversion method for carbonate rock fracture-cavity zones according to claim 4, characterized in that, The acquisition of probabilistic data volumes for cavernous reservoirs and fractured-vuggy reservoirs also includes: The probability values ​​of the portions with a probability value of 0 and the portions with a probability value of 0.9 in the cavity-type reservoir probability data body are set to 1, and the probability values ​​of the other portions are set to 0, thus obtaining the fracture-cavity-type reservoir probability data body.

6. The post-stack geostatistical inversion method for carbonate rock fracture-cavity zones according to claim 1, characterized in that, After using the cave-type reservoir probability data volume as a cave three-dimensional lithofacies probability constraint and the fracture-pore-type reservoir probability data volume as a fracture-pore three-dimensional lithofacies probability constraint, and before performing the fracture-cavity zone facies-controlled post-stack geostatistical inversion to obtain the inverted P-wave impedance volume, the inversion method further includes: Rock physics analysis was conducted using drilled wells to obtain the probability density function of P-wave impedance for cavernous reservoirs, fractured pore reservoirs, and surrounding rocks.

7. The method for post-stack geostatistical inversion of carbonate rock fracture-cavity zones according to claim 6, characterized in that, After using the cave-type reservoir probability data volume as a cave three-dimensional lithofacies probability constraint and the fracture-pore-type reservoir probability data volume as a fracture-pore three-dimensional lithofacies probability constraint, and before performing the fracture-cavity zone facies-controlled post-stack geostatistical inversion to obtain the inverted P-wave impedance volume, the inversion method further includes: Extract the planar properties of the target layer to obtain the variation function parameters of the cavernous reservoir, the fractured-void reservoir, and the surrounding rock.

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