Method and system for constructing spherical karst cave model
By using the probability density function and development probability body of the cave statistical space in the spherical cave model, the spherical cave model was accurately constructed, solving the problem of large model errors in the existing technology, and achieving a geological model construction that conforms to reality.
Patent Information
- Application Number
- CN202311047363.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2023-08-18
- Publication Date
- 2025-02-21
AI Technical Summary
When constructing spherical cave models, it is difficult to accurately control the shape and volume distribution of the caves in the prior art, resulting in large model errors and not constrained by multiple prior geological knowledge, and the prediction results are inaccurate.
By dividing the target area where the cave is located into multiple cave statistical spaces, collecting geological information, probability density functions of structural volume proportion and development density, determining the total volume and total number of caves, determining the cave location based on the development probability body, and calculating the volume distribution Features: Construct the target spherical cave model.
The accurate construction of the spherical cave model is achieved, the "spherical" shape is retained, and the constraints of multiple types of prior geological knowledge are met, which improves the accuracy and reliability of the model.
Smart Images
Figure CN119494930A_ABST
Abstract
Description
Technical Field
[0001] The invention belongs to the field of reservoir geological modeling, and in particular relates to a method and a system for constructing a spherical karst cave model. Background Art
[0002] The storage space of the Ordovician fracture-cave oil reservoirs in the Tahe Oilfield is caves, pores and fractures of different scales, among which caves are the main storage space. The cave reservoir is characterized by continuous strong reflection (underground dark river) and near-circular shape (fault control) in seismic response. Spherical caves are a very important type of cave reservoir. In recent years, with the continuous deepening of research on fracture-cave oil reservoirs, many experts and scholars have conducted many studies on the characteristics of this type of cave reservoir, such as: (1) By studying the reservoir characteristics, genesis and development laws of the "fault-karst body" during the burial period, the main controlling factors and characteristics of cave development are clarified; (2) Based on the strong correlation between seismic attributes and cave development, the seismic attribute threshold is determined, and the seismic attributes such as the root mean square amplitude are directly truncated to obtain the cave geological model; (3) Based on the statistical analysis of well point identification data, the regional theoretical variation function is obtained, and then based on this The variogram function is used to predict underground karst reservoirs; (4) The spatial distribution law of spherical karst reservoirs is obtained by scanning pre-given training images, and then based on this law, multi-point geostatistical algorithms such as Snesim are used to predict the spatial distribution of spherical karst reservoirs; (5) By constructing a knowledge base of fracture-cavity reservoirs, training images are established based on the geometric morphology and distribution law of underground rivers revealed by the knowledge base, and the spatial distribution of underground underground river reservoirs is simulated through multi-point geostatistical methods; (6) Based on the modeling idea of "hierarchical constraints, genetic control, and step-by-step modeling" of fault-karst systems, a large-scale karst model is established using a deterministic method.
[0003] In the process of realizing the present invention, the inventors found that the existing technology mainly uses deterministic methods and random simulations (sequential indication and multi-point geostatistical simulation methods) to characterize the spatial distribution of caves. Among them, the cave model characterized by the deterministic method is very consistent with the seismic attributes, but it is impossible to control the shape of the constructed cave, and when the correlation between the seismic attributes and the cave is not strong, the error of the established cave model is large; the sequential indication method controls the cave reservoir with a variogram, which can make the prediction results consistent with the well point observation data in the spatial distribution law of the geological body to a certain extent, but its shortcomings are very obvious, such as: the prediction process is not controlled by geological factors such as the total volume of the cave, and the prediction results obtained are inaccurate; the multi-point geostatistical method can reproduce the "spherical" shape of the cave to a certain extent, but the prediction process is also not constrained by multiple types of prior geological knowledge, such as: the total volume of the cave, the number of caves, the volume of each cave, etc., and the prediction results obtained are also inaccurate. Summary of the invention
[0004] In order to solve the above problems, an embodiment of the present invention provides a method for constructing a spherical cave model, the method comprising: dividing a target area where the cave is located into a plurality of cave statistical spaces, and collecting geological information of each statistical space, so as to respectively construct a first probability density function for describing the volume proportion of the cave in the statistical space, and a second probability density function for describing the cave development density in the statistical space; configuring the volume proportion and the cave development density for the model used to simulate the target area, and using each probability density function to determine the total volume and the total number of caves required for the current model to be constructed; determining the location of the caves of the model to be constructed based on a cave development probability body representing the existence status of the caves in the target area, thereby obtaining the cave volume distribution characteristics of the model to be constructed according to the positional relationship between the cave location and the fault layer in the target area, and the total volume and the total number of the caves; and constructing a target spherical cave model according to the cave volume distribution characteristics.
[0005] Preferably, the geological information of each statistical space is obtained by analyzing the geological characteristics of oil field outcrops and similar karst areas in the target area including the caves.
[0006] Preferably, the step of determining the total volume of the cave includes: obtaining the total volume using the configured volume percentage and the regional volume of the target area, wherein the total volume is calculated using the following expression:
[0007] V r =V z *prop
[0008] Among them, V r Represents the total volume, V z Represents the area volume, and prop represents the configured volume ratio.
[0009] Preferably, the step of determining the total number of caves includes: obtaining the total number using the configured cave development density and the regional volume of the target area, wherein the total number is calculated using the following expression:
[0010] N r =V z *den
[0011] Among them, N r Indicates the total quantity, V z It represents the regional volume, and den represents the configured cave development density.
[0012] Preferably, the karst cave development probability body is constructed based on the correlation between the seismic data, well logging data and fault data in the geological information and the karst cave development probability.
[0013] Preferably, the step of determining the location of the cave includes: firstly gridding the development probability body, and then arbitrarily selecting a grid matching the total number as the center of the cave to be modeled, thereby obtaining the location of the cave.
[0014] Preferably, the step of obtaining the volume distribution characteristics of the cave includes: determining the distance between the cave position and the fault according to the positional relationship between the cave position and the fault in the target area, and based on this, calculating a volume index characterizing the relative size relationship between the volumes of the various caves in combination with the total volume and total number of the caves, thereby calculating the volume of each cave using the volume index.
[0015] Preferably, the volume of each cave is calculated using the following expression:
[0016]
[0017] V x1 ′=V x1 *a
[0018] V x2 ′=V x2 *a
[0019] …
[0020] V xNr '=V xNr *a
[0021] Where a represents the volume corresponding to the unit volume index, V r Represents the total volume, V x1 、V x2 ……V xNr Respectively represent the 1st, 2nd, ... Nth r The volume index of the cave, V x1 '、V x2 '……V xNr , Respectively represent the 1st, 2nd, ... Nth r The volume of a cave.
[0022] Preferably, the step of constructing a target spherical cave model according to the cave volume distribution characteristics includes: calculating the radius of each spherical cave according to the cave volume distribution characteristics, and then taking the corresponding cave position as the center of the sphere to form each spherical cave to be modeled.
[0023] On the other hand, the present invention also provides a system for constructing a spherical cave model, the system comprising the following modules: a function construction module, which is used to divide the target area where the cave is located into multiple cave statistical spaces, and collect geological information of each statistical space, so as to respectively construct a first probability density function for describing the volume proportion of the cave in the statistical space, and a second probability density function for describing the cave development density in the statistical space; a first parameter acquisition module, which is used to configure the volume proportion and cave development density for the model used to simulate the target area, and use each probability density function to determine the total volume and total number of caves required for the current model to be built; a second parameter acquisition module, which is used to determine the cave position of the model to be built based on the cave development probability body representing the existence state of the cave in the target area, so as to obtain the cave volume distribution characteristics of the model to be built according to the positional relationship between the cave position and the fault layer in the target area, and the total volume and total number of the caves; a model construction module, which is used to construct a target spherical cave model according to the cave volume distribution characteristics.
[0024] Compared with the prior art, one or more embodiments of the above scheme may have the following advantages or beneficial effects:
[0025] The present invention proposes a method and system for constructing a spherical karst cave model. The method first obtains multiple types of prior geological knowledge (e.g., overall proportional distribution density function, development density, spatial development probability distribution, etc.) of the spherical karst cave distribution for constraining the constructed spherical karst cave model by statistically analyzing the geological information of the target area where the karst cave is located. Then, according to the obtained multiple types of prior geological knowledge, the distribution of the spherical karst caves in the target area is constrained, thereby constructing a spherical karst cave model in the target area. The spherical karst cave model constructed by the present invention retains the "spherical" shape and satisfies the constraints of multiple types of prior geological knowledge (overall proportional probability density distribution of spherical karst caves, probability density distribution of spherical karst cave development density, spatial development probability body of spherical karst caves, and spatial distribution body of spherical karst cave scale (volume)), thereby realizing the accurate construction of a spherical karst cave model that conforms to reality.
[0026] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the description, claims and drawings. BRIEF DESCRIPTION OF THE DRAWINGS
[0027] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:
[0028] Figure 1 It is a step diagram of the method for constructing a spherical cave model according to an embodiment of the present application.
[0029] Figure 2 It is an example diagram of a field outcrop spherical cave in the method for constructing a spherical cave model in an embodiment of the present application.
[0030] Figure 3 It is an example diagram of the distribution of caves in the statistical space of the method for constructing a spherical cave model in an embodiment of the present application.
[0031] Figure 4 It is a frequency histogram of cave volume ratio and cave development density of the method for constructing a spherical cave model in an embodiment of the present application.
[0032] Figure 5 It is an example diagram of a horizontal cross section of a spherical karst cave development probability body in the method for constructing a spherical karst cave model in an embodiment of the present application.
[0033] Figure 6 This is an example diagram of the volume index of the method for constructing a spherical cave model according to an embodiment of the present application, which varies with the distance to the fault.
[0034] Figure 7 It is an example diagram of a cross section of the three-dimensional distribution of volume index in the method for constructing a spherical cave model in an embodiment of the present application.
[0035] Figure 8 It is an example diagram of a target spherical cave model of the method for constructing a spherical cave model in an embodiment of the present application.
[0036] Fig. 9 It is a module block diagram of a system for constructing a spherical cave model according to an embodiment of the present application. DETAILED DESCRIPTION
[0037] The following will describe the implementation methods of the present invention in detail with reference to the accompanying drawings and embodiments, so that the implementation process of how the present invention applies technical means to solve technical problems and achieve technical effects can be fully understood and implemented accordingly. It should be noted that as long as there is no conflict, the various embodiments of the present invention and the various features in the embodiments can be combined with each other, and the technical solutions formed are all within the protection scope of the present invention.
[0038] In addition, the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be performed in an order different from that shown here.
[0039] The storage space of the Ordovician fracture-cave oil reservoirs in the Tahe Oilfield is caves, pores and fractures of different scales, among which caves are the main storage space. The cave reservoir is characterized by continuous strong reflection (underground dark river) and near-circular shape (fault control) in seismic response. Spherical caves are a very important type of cave reservoir. In recent years, with the continuous deepening of research on fracture-cave oil reservoirs, many experts and scholars have conducted many studies on the characteristics of this type of cave reservoir, such as: (1) By studying the reservoir characteristics, genesis and development laws of the "fault-karst body" during the burial period, the main controlling factors and characteristics of cave development are clarified; (2) Based on the strong correlation between seismic attributes and cave development, the seismic attribute threshold is determined, and the seismic attributes such as the root mean square amplitude are directly truncated to obtain the cave geological model; (3) Based on the statistical analysis of well point identification data, the regional theoretical variation function is obtained, and then based on this The variogram function is used to predict underground karst reservoirs; (4) The spatial distribution law of spherical karst reservoirs is obtained by scanning pre-given training images, and then based on this law, multi-point geostatistical algorithms such as Snesim are used to predict the spatial distribution of spherical karst reservoirs; (5) By constructing a knowledge base of fracture-cavity reservoirs, training images are established based on the geometric morphology and distribution law of underground rivers revealed by the knowledge base, and the spatial distribution of underground underground river reservoirs is simulated through multi-point geostatistical methods; (6) Based on the modeling idea of "hierarchical constraints, genetic control, and step-by-step modeling" of fault-karst systems, a large-scale karst model is established using a deterministic method.
[0040] In the process of realizing the present invention, the inventors found that the existing technology mainly uses deterministic methods and random simulations (sequential indication and multi-point geostatistical simulation methods) to characterize the spatial distribution of caves. Among them, the cave model characterized by the deterministic method is very consistent with the seismic attributes, but it is impossible to control the shape of the constructed cave, and when the correlation between the seismic attributes and the cave is not strong, the error of the established cave model is large; the sequential indication method controls the cave reservoir with a variogram, which can make the prediction results consistent with the well point observation data in the spatial distribution law of the geological body to a certain extent, but its shortcomings are very obvious, such as: the prediction process is not controlled by geological factors such as the total volume of the cave, and the prediction results obtained are inaccurate; the multi-point geostatistical method can reproduce the "spherical" shape of the cave to a certain extent, but the prediction process is also not constrained by multiple types of prior geological knowledge, such as: the total volume of the cave, the number of caves, the volume of each cave, etc., and the prediction results obtained are also inaccurate.
[0041] Therefore, in order to solve the above problems, the present invention proposes a method and system for constructing a spherical karst cave model. The method first obtains multiple types of prior geological knowledge (for example, overall proportional distribution density function, development density, spatial development probability distribution, etc.) of the spherical karst cave distribution for constraining the constructed spherical karst cave model by statistically analyzing the geological information of the target area where the karst cave is located. Then, according to the obtained multiple types of prior geological knowledge, the distribution of spherical karst caves in the target area is constrained, thereby constructing a spherical karst cave model in the target area. The spherical karst cave model constructed by the present invention retains the "spherical" shape and satisfies the constraints of multiple types of prior geological knowledge (overall proportional probability density distribution of spherical karst caves, probability density distribution of spherical karst cave development density, spatial development probability body of spherical karst caves, and spatial distribution body of spherical karst cave scale (volume)), thereby realizing the accurate construction of a spherical karst cave model that conforms to reality.
[0042] Embodiment 1
[0043] Figure 1 This is a step diagram of the method for constructing a spherical cave model in an embodiment of the present application. Figure 1 To illustrate the various steps of this method.
[0044] like Figure 1 As shown, in step S110, the target area where the cave is located is divided into a plurality of cave statistical spaces, and the geological information of each statistical space is collected to respectively construct a first probability density function for describing the volume proportion of the cave in the statistical space, and a second probability density function for describing the density of the cave development in the statistical space. In order to ensure that the constructed model has the same spherical cave distribution characteristics as the actual reservoir, this embodiment is based on the analysis of the current cave distribution characteristics of the target area where the cave is located, and the spherical cave distribution characteristics of the actual reservoir are used as the spherical cave distribution characteristics of the constructed model to obtain a target spherical cave model that conforms to the actual situation. In an embodiment of the present application, the target area where the cave is located is divided into a plurality of cave statistical spaces of the same size, and the geological information of each statistical space is collected respectively (for example: the length, width, height scale data of the cave, the number of caves, and other information related to the cave distribution state), and then the geological information of each statistical space is used to analyze the cave distribution state in the corresponding statistical space to obtain a function (a first probability density function and a second probability density function) for characterizing the cave distribution state of the current reservoir.
[0045] In the process of obtaining the function for characterizing the cave distribution state of the current reservoir, the collected geological information is first used to calculate the sum of the volumes of all caves contained in each statistical space (the total volume of the caves), and the number of caves contained in each statistical space is determined. The total volume of the caves is divided by the volume of the statistical space to obtain the volume ratio of the caves in each statistical space (i.e., the volume ratio of the caves in the statistical space), and the number of caves is divided by the volume of the statistical space to obtain the cave development density in each statistical space (i.e., the cave development density in the statistical space). In this way, after obtaining the volume ratio of the caves and the cave development density in each statistical space, the purpose of constructing a first probability density function for describing the volume ratio of the caves in the statistical space and a second probability density function for describing the cave development density in the statistical space can be achieved by analyzing and integrating the volume ratio of the caves and the cave development density.
[0046] In the process of analyzing and integrating the volume proportion of caves and the density of cave development to obtain various probability density functions, the first probability density function of the volume proportion (%) of spherical caves in the statistical space is determined according to the volume proportion of caves in each statistical space (for example: the volume proportion in the statistical space obeys a normal distribution with a mean of 0.8% and a standard deviation of 0.2%), and the second probability density function of the cave development density (individuals / cubic kilometer) of spherical caves in the statistical space is determined according to the cave development density in each statistical space (for example: the cave development density in the statistical space obeys a normal distribution with a mean of 7 and a standard deviation of 3).
[0047] In the embodiment of the present application, the geological information of each statistical space is obtained by analyzing the geological characteristics of the oil field outcrops and similar karst areas in the target area where the cave is located. Specifically, according to the formation conditions of the target area where the cave is located, it can be known that the target area is located in the oil field outcrops and similar karst areas. Therefore, this embodiment determines the information related to the distribution state of the caves, including the length, width, and height scale data of the caves, the number of caves, etc. of each divided statistical space by analyzing the geological characteristics of the oil field outcrops and similar karst areas including the target area, thereby realizing the acquisition of geological information of each statistical space.
[0048] Further, in step S120, the volume proportion and the density of karst caves are configured for the model used to simulate the target area, and each probability density function is used to determine the total volume and total number of karst caves required for the current model to be built. In an embodiment of the present application, an original geological model matching the actual geological characteristics is preliminarily constructed according to the actual geological characteristics of the target area (for example, the distribution of faults, the size of the target area). Based on the original geological model, after obtaining the first probability density function and the second probability density function, the present embodiment configures the volume proportion and the density of karst caves for the model used to simulate the target area according to actual needs, and then substitutes the configured volume proportion and the density of karst caves into the corresponding probability density function, so as to calculate the total volume and total number of karst caves required for the current model to be built.
[0049] In the step of determining the total volume of the cave, the total volume is obtained using the configured volume fraction and the regional volume of the target area, wherein the total volume is calculated using the following expression:
[0050] V r =V z *prop (1)
[0051] Among them, V r Represents the total volume, V z Represents the area volume, and prop represents the configured volume ratio.
[0052] In the step of determining the total number of caves, the total number is obtained using the configured cave development density and the regional volume of the target area, wherein the total number is calculated using the following expression:
[0053] N r =V z *den (2)
[0054] Among them, N r represents the total number, and den represents the configured cave development density.
[0055] Further, in step S130, based on the karst cave development probability body representing the existence state of the karst cave in the target area, the karst cave position of the model is determined, so as to obtain the karst cave volume distribution characteristics of the model according to the positional relationship between the karst cave position and the fault layer in the target area, as well as the total volume and total number of the karst caves. In the embodiment of the present application, the target area where the karst cave is located is divided into a plurality of single-well karst cave reservoirs based on well logging and emptying loss, and the correlation between the development probability body and data such as earthquakes and faults is analyzed for each single-well karst cave reservoir, so as to construct a spherical karst cave development three-dimensional probability body in the target area, and then use the current three-dimensional probability body as the karst cave development probability body representing the existence state of the karst cave in the target area. Next, with the karst cave development probability body representing the existence state of the karst cave in the target area as the weight, different positions specified on the model are randomly selected as the center of the spherical karst cave, thereby determining the karst cave position of the model. In practical applications, the volume of the spherical karst cave is mainly related to its distance from the fault. Therefore, this embodiment obtains the relative size relationship between different caves in the model based on the positional relationship between the cave location and the fault layer in the target area, as well as the total volume and total number of caves, and then obtains the cave volume distribution characteristics of the model based on the relative size relationship.
[0056] In the embodiment of the present application, the probability body of karst cave development is constructed based on the correlation between the seismic data, well logging data and fault data in the geological information and the probability of karst cave development. Specifically, based on the geological information, the present embodiment determines the data such as earthquakes, well logging and faults in similar karst areas, and then obtains the correlation between these data and the probability of spherical karst cave development through analysis. Finally, the karst cave development probability body representing the existence state of the karst caves in the target area is constructed using the phase relationship.
[0057] In the step of determining the location of the cave, the present invention first grids the development probability body, and then randomly selects a grid that matches the total number as the center of the cave in the model, thereby obtaining the location of the cave. In order to accurately represent the center position of the spherical cave in the model, this embodiment uses the cave development probability body representing the existence status of the cave in the target area as the weight, and randomly selects N r The corresponding N grids of the model r The center of the spherical cave is obtained, and the accurate cave position of the model is obtained, where each center is recorded as x1, x2, ..., xN r .
[0058] Next, in the step of obtaining the volume distribution characteristics of the cave, the present invention determines the distance between the cave position and the fault according to the positional relationship between the cave position and the fault in the target area, based on which, combined with the total volume and total number of the caves, calculates the volume index that characterizes the volume relative size relationship between each cave, thereby using the volume index to calculate the volume of each cave. Based on the above analysis, it can be seen that the volume of the spherical cave is mainly related to its distance to the fault. According to the fault data of similar karst areas and the correlation between the fault distribution and the volume of the spherical cave, the spatial distribution of the relative size of the volume between different caves in the model can be obtained, and the spatial distribution of the relative size of the volume does not represent the specific size of the volume, but can only reflect the relative value of the volume size of the spherical cave. Therefore, this embodiment first determines the distance between the cave position (the center of the determined spherical cave) and the fault of the model according to the positional relationship between the cave position and the fault in the target area, and then uses the determined distance, the total volume and the total number of the caves to determine the spatial distribution of the relative size of the volume between different caves in the model, and characterizes the relative size relationship of the volume between each cave by calculating the volume index. Finally, when the volume index of each cave is obtained, the volume index is used to calculate the volume of each cave.
[0059] In the embodiment of the present application, the volume of each cave is calculated using the following expression:
[0060]
[0061] V x1 , =V x1 *a (4)
[0062] V x2 '=V x2 *a (5)
[0063] …
[0064] V xNr '=V xNr *a (6)
[0065] Where a represents the volume corresponding to the unit volume index, V r Represents the total volume, V x1 、V x2 ……V xNr Respectively represent the 1st, 2nd, ... Nth r The volume index of the cave, V x1 '、V x2 '……V xNr ' respectively represent the 1st, 2nd...Nth r The volume of a cave.
[0066] In the step of constructing the target spherical cave model according to the cave volume distribution characteristics, the radius of each spherical cave is calculated according to the cave volume distribution characteristics, and then the corresponding cave position is used as the sphere center to form each spherical cave of the model. According to the volume of each spherical cave obtained by the above calculation, the radius of each spherical cave of the model is determined, and then the grid within the radius of the sphere center is defined as the corresponding spherical cave, so as to obtain each spherical cave of the model.
[0067] Further, in step S140, a target spherical karst cave model is constructed according to the karst cave volume distribution characteristics. In the embodiment of the present application, the karst cave volume distribution characteristics include the karst cave position (the spherical center of the spherical karst cave), and the volume and radius of each spherical karst cave, so by mapping the aforementioned karst cave volume distribution characteristics to the constructed model, the purpose of constructing the target spherical karst cave model can be achieved. It can be seen that the spherical karst cave of the target spherical karst cave model constructed by the present invention retains a "spherical" shape, and the constructed target spherical karst cave model is consistent with multiple prior geological knowledge (i.e.: the overall proportion probability density distribution of spherical karst caves, the probability density distribution of spherical karst cave development density, the spatial development probability body of spherical karst caves and the spatial distribution body of spherical karst cave scale (volume)), and the target spherical karst cave model constructed by the present invention is used to carry out karst cave development prediction research, and accurate and practical prediction results can be obtained.
[0068] Embodiment 2
[0069] The Tahe Oilfield is a typical fracture-cave oil reservoir, the development of which is mainly controlled by faults, and the development density of the cave reservoir and the size of the cave are related to the faults. In a specific embodiment of the present application, the cave area located in the Tahe Oilfield is used as the target area to construct a corresponding target spherical cave model. Next, the construction of the spherical cave model of the target area of the Tahe Oilfield in this embodiment is illustrated.
[0070] In the embodiment of the present application, according to the method for constructing a spherical karst cave model described in Example 1, the karst outcrop area in Tabei, Tahe Oilfield is first divided into 10 subdivided karst cave statistical spaces, where the size of each statistical space is 5km (length) × 5km (width) × 15m (height). These statistical spaces are full of gullies, and the karst caves formed during the karst geological period are basically exposed. Afterwards, the drone camera is used to conduct a full-scale scan and take photos of the areas where these statistical spaces are located to obtain the following Figure 2 Based on the volume and density changes of the field outcrop spherical karst caves shown in the photo, all the karst cave data including the size (length, width, height) and number of karst caves in each statistical space are obtained ( Figure 2is an example of a field outcrop spherical cave in the method for constructing a spherical cave model in an embodiment of the present application). Further, the following is obtained: Figure 3 The three-dimensional distribution of caves in different cave statistical spaces is shown in Figure 2. Figure 3 is an example diagram of the distribution of caves in the statistical space of the method for constructing a spherical cave model in an embodiment of the present application). Finally, based on the three-dimensional distribution of caves in the entire statistical space, the following is obtained: Figure 4 The characteristics of cave volumes and cave densities at different locations in Tabei are shown in Figure 2. Figure 4 is a histogram of the cave volume ratio and cave development density frequency of the method for constructing a spherical cave model in an embodiment of the present application). Figure 4 (Left) and (Right) are the volume proportion of caves and the frequency of occurrence of cave development density in the above 10 statistical spaces, respectively.
[0071] Continue to refer to Figure 4 , respectively, the probability density functions (pdf) of the cave volume ratio and the cave development density are approximately fitted. Through fitting, it can be seen that the cave volume ratio of this embodiment is approximately similar to a normal Gaussian distribution with a mean of 0.35% and a variance of 0.1%, while the cave development density is approximately similar to a normal Gaussian distribution with a mean of 1.0 and a variance of 0.5. Accordingly, from the pdf functions of the cave volume ratio and the cave development density, the values corresponding to each function are randomly selected, namely: a cave volume ratio value (0.27%) and a cave development density value (0.8), and the selected values are used as the two basic parameters of the constructed model.
[0072] Next, based on the original geological model preliminarily constructed according to the actual geological characteristics of the target area and matching the actual geological characteristics, the total volume of the karst cave in the model was calculated based on the above two basic parameters to be 1.19×10 6 Cubic meters, the total number of caves is 35. Among them, the area of the target area of this embodiment is irregular, and the volume is approximately 3km (width)×4.2km (length)×35m (thickness).
[0073] Furthermore, based on well logging and emptying, the target area where the cave is located is divided into multiple single-well cave reservoirs, and the correlation between the development probability body and seismic and fault data is analyzed for each single-well cave reservoir, and the following is obtained: Figure 5 The change of the probability of cave development on a certain horizontal interface in the target area shown in the figure is used to construct a spherical three-dimensional probability body of cave development in the target area where the cave is located ( Figure 5 It is an example diagram of the horizontal cross-section of the spherical cave development probability body of the method for constructing a spherical cave model in an embodiment of the present application).
[0074] After constructing the three-dimensional probability body of spherical karst cave development, this embodiment uses the current three-dimensional probability body as the weight and randomly selects 35 grids as the centers of the 35 spherical karst caves corresponding to the model, thereby obtaining the accurate karst cave positions of the model, where each center is recorded as x1, x2, ..., x 35 .
[0075] Through the study and statistics of the scale of the caves in the Tabei karst outcrop, it was found that the scale of the cave is closely related to the distance from the cave to the fault. Therefore, this example uses the method for constructing a spherical cave model described in Example 1 to statistically analyze the changes in the scale of the caves developed around 10 faults of different sizes in the Tabei outcrop, and obtains the following: Figure 6 The statistical results shown ( Figure 6 is an example diagram of the volume index of the method for constructing a spherical cave model according to an embodiment of the present application varying with the distance to the fault). Figure 6 It can be seen that the farther away from the fault, the smaller the volume of the cave. Since the size of the fault has a significant impact on the absolute size of the cave, Figure 6 The ordinate in only represents the relative change in the volume of the caves around the same fault, and does not represent specific data. This embodiment also characterizes the relative size relationship between the volumes of the various caves by calculating the volume index.
[0076] according to Figure 6 The volume index changes with the distance to the fault and the spatial distribution of the faults in the target area. The spatial distribution of the cave volume index attribute in the target area is calculated. This distribution only reflects the relative value of the volume size of a single spherical cave. Among them, on a certain cross section of the three-dimensional distribution of the volume index, the relative value of the volume size of a single spherical cave is as follows: Figure 7 As shown ( Figure 7 It is an example diagram of a cross section of the three-dimensional distribution of volume index in the method for constructing a spherical cave model in an embodiment of the present application).
[0077] After the volume index is obtained, the volume of each spherical cave is calculated according to the method for constructing a spherical cave model described in Example 1, the radius of the corresponding spherical cave is determined, and the grid within the radius of the sphere is defined as a spherical cave, thereby constructing a spherical cave model as shown in FIG. Figure 8 The target spherical cave model shown ( Figure 8 is an example diagram of a target spherical cave model of the method for constructing a spherical cave model in an embodiment of the present application). Figure 8 The irregular shapes of some caves are caused by the superposition of two or more caves, rather than errors in the construction process. It can be seen that the present invention realizes the accurate construction of the spherical cave model.
[0078] Embodiment 3
[0079] Based on the method for constructing a spherical cave model described in the first embodiment, the embodiment of the present invention further provides a system for constructing a spherical cave model. Fig. 9 It is a module block diagram of a system for constructing a spherical cave model according to an embodiment of the present application.
[0080] like Fig. 9 As shown, the system for constructing a spherical karst cave model in an embodiment of the present invention includes: a function construction module 91, a first parameter acquisition module 92, a second parameter acquisition module 93 and a model construction module 94. The function construction module 91 is implemented according to the method described in step S110 above, and is configured to divide the target area where the karst cave is located into multiple karst cave statistical spaces, and collect geological information of each statistical space to respectively construct a first probability density function for describing the volume proportion of the karst cave in the statistical space, and a second probability density function for describing the density of karst cave development in the statistical space; the first parameter acquisition module 92 is implemented according to the method described in step S120 above, and is configured to configure the volume proportion and the density of karst cave development for the model used to simulate the target area, and use the probability density functions constructed by the function construction module 91 to determine the current karst cave to be constructed. The total volume and total number of caves required for the model; the second parameter acquisition module 93 is implemented in accordance with the method described in the above step S130, and is configured to determine the cave positions of the model based on the cave development probability body representing the existence status of caves in the target area, so as to obtain the cave volume distribution characteristics of the model according to the positional relationship between the cave position and the fault layer in the target area, and the total volume and total number of caves obtained by the first parameter acquisition module 92; the model construction module 94 is implemented in accordance with the method described in the above step S140, and is configured to construct a target spherical cave model according to the cave volume distribution characteristics obtained by the second parameter acquisition module 93.
[0081] The present invention discloses a method and system for constructing a spherical karst cave model. The method first obtains multiple types of prior geological knowledge (e.g., overall proportional distribution density function, development density, spatial development probability distribution, etc.) of the spherical karst cave distribution constraining the constructed spherical karst cave model by statistically analyzing the geological information of the target area where the karst cave is located. Then, according to the obtained multiple types of prior geological knowledge, the distribution of the spherical karst caves in the target area is constrained, thereby constructing the spherical karst cave model in the target area. The spherical karst cave model constructed by the present invention retains the "spherical" shape and satisfies the constraints of multiple types of prior geological knowledge (overall proportional probability density distribution of spherical karst caves, probability density distribution of spherical karst cave development density, spatial development probability body of spherical karst caves, and spatial distribution body of spherical karst cave scale (volume)), thereby realizing the accurate construction of a spherical karst cave model that conforms to reality. The construction of an accurate spherical cave model can not only help oilfield geologists and reservoir developers accurately understand the structure and morphology of underground reservoirs, but also provide a training data set for the geological modeling method based on generative adversarial networks, and then construct an accurate oilfield cave geological model to increase oil and gas geological reserves and production.
[0082] The above is only a preferred specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by any person familiar with the technology within the technical scope disclosed by the present invention should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.
[0083] Of course, the present invention may have many other embodiments. Without departing from the spirit and essence of the present invention, those skilled in the art may make various corresponding changes and modifications based on the present invention, but these corresponding changes and modifications should all fall within the scope of protection of the claims of the present invention.
[0084] It should be understood by those skilled in the art that the modules or steps of the present invention described above can be implemented by a general-purpose computing device, they can be concentrated on a single computing device, or distributed on a network composed of multiple computing devices, and optionally, they can be implemented by a program code executable by a computing device, so that they can be stored in a storage device and executed by the computing device, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. Thus, the present invention is not limited to any specific combination of hardware and software.
[0085] Although the embodiments disclosed in the present invention are as above, the above contents are only embodiments adopted for facilitating the understanding of the present invention and are not intended to limit the present invention. Any technician in the technical field to which the present invention belongs can make any modifications and changes in the form and details of the implementation without departing from the spirit and scope disclosed in the present invention, but the patent protection scope of the present invention shall still be subject to the scope defined in the attached claims.
Claims
1. A method for constructing a spherical cave model, characterized in that: The method comprises: The target area where the caves are located is divided into a plurality of cave statistical spaces, and the geological information of each statistical space is collected to respectively construct a first probability density function for describing the volume proportion of the caves in the statistical space, and a second probability density function for describing the density of the cave development in the statistical space; Configuring the volume percentage and cave development density for the model used to simulate the target area, and using each probability density function to determine the total volume and total number of caves required for the current model to be built; Based on the karst cave development probability body representing the existence status of the karst caves in the target area, the location of the karst caves to be built in the model is determined, so as to obtain the volume distribution characteristics of the karst caves to be built in the model according to the positional relationship between the karst cave location and the fault layer in the target area, as well as the total volume and total number of the karst caves; A target spherical cave model is constructed according to the cave volume distribution characteristics.
2. The method according to claim 1, characterized in that: The geological information of each statistical space is obtained by analyzing the geological characteristics of oil field outcrops and similar karst areas in the target area where the caves are located.
3. The method according to claim 1 or 2, characterized in that: The step of determining the total volume of the cave comprises: The total volume is obtained by using the configured volume percentage and the area volume of the target area, wherein the total volume is calculated using the following expression: V r =V z *prop Among them, V r Represents the total volume, V z Represents the area volume, and prop represents the configured volume ratio.
4. The method according to any one of claims 1 to 3, characterized in that: The steps in determining the total number of caves include: The total number is obtained by using the configured cave development density and the regional volume of the target area, wherein the total number is calculated using the following expression: N r =V z *den Among them, N r Indicates the total quantity, V z It represents the regional volume, and den represents the configured cave development density.
5. The method according to any one of claims 1 to 4, characterized in that: The karst cave development probability body is constructed based on the correlation between the seismic data, well logging data and fault data in the geological information and the karst cave development probability.
6. The method according to any one of claims 1 to 5, characterized in that: The step of determining the location of the cave includes: The development probability body is first gridded, and then a grid matching the total number is arbitrarily selected as the center of the cave to be modeled, thereby obtaining the location of the cave.
7. The method according to any one of claims 1 to 6, characterized in that: The step of obtaining the cave volume distribution characteristics includes: According to the positional relationship between the cave location and the fault in the target area, the distance between the cave location and the fault is determined. Based on this, combined with the total volume and total number of the caves, the volume index characterizing the relative size relationship between the various caves is calculated, and the volume of each cave is calculated using the volume index.
8. The method according to claim 7, characterized in that The volume of each cave is calculated using the following expression: In x1 '=V x1 *and In x2 '=V x2 *and … In xNr '=V xNr *and Where a represents the volume corresponding to the unit volume index, V r Represents the total volume, V x1 、V x2 ……V xNr Respectively represent the 1st, 2nd, ... Nth r The volume index of the cave, V x1 '、V x2 '……V xNr ' respectively represent the 1st, 2nd...Nth r The volume of a cave.
9. The method according to any one of claims 1 to 8, characterized in that: The step of constructing a target spherical cave model according to the cave volume distribution characteristics includes: According to the volume distribution characteristics of the caves, the radius of each spherical cave is calculated, and then the corresponding cave position is used as the center of the sphere to form each spherical cave of the model to be built.
10. A system for constructing a spherical cave model, characterized in that: The system includes the following modules: A function construction module, which is used to divide the target area where the caves are located into multiple cave statistical spaces, and collect geological information of each statistical space to respectively construct a first probability density function for describing the volume proportion of the caves in the statistical space, and a second probability density function for describing the density of cave development in the statistical space; A first parameter acquisition module, which is used to configure the volume proportion and cave development density for the model used to simulate the target area, and use each probability density function to determine the total volume and total number of caves required for the current model to be built; A second parameter acquisition module is used to determine the location of the caves to be built in the model based on the cave development probability body representing the existence status of the caves in the target area, so as to obtain the volume distribution characteristics of the caves to be built in the model according to the positional relationship between the location of the caves and the fault layer in the target area, as well as the total volume and total number of the caves; A model building module is used to build a target spherical cave model according to the cave volume distribution characteristics.