CN111967117A - Underground reservoir prediction method and device based on outcrop carbonate reservoir modeling - Google Patents

Abstract

The application provides an underground reservoir prediction method and device based on outcrop carbonate reservoir modeling, and the method comprises the following steps: acquiring a two-dimensional outcrop geological model corresponding to the outcrop carbonate rock reservoir, and performing three-dimensional digital scanning and labeling processing on the outcrop carbonate rock reservoir to obtain a corresponding three-dimensional image; obtaining three-dimensional sedimentary microfacies models respectively corresponding to each stratigraphic unit according to the three-dimensional images and lithofacies information in the actually measured section of the outcrop carbonate rock reservoir; and respectively obtaining a three-dimensional porosity model and a three-dimensional permeability model corresponding to each stratum unit according to the three-dimensional sedimentary microfacies model corresponding to each stratum unit so as to predict the effective reservoir in the underground reservoir corresponding to the outcrop carbonate rock reservoir. According to the method and the device, the three-dimensional geological model for the outcrop carbonate reservoir can be accurately and quickly established, and the prediction accuracy and reliability of the effectiveness of the underground reservoir under the reservoir scale standard can be effectively improved.

Description

Subsurface reservoir prediction method and device based on outcrop carbonate reservoir modeling

technical field

The present application relates to the technical field of petroleum exploration, in particular to a method and device for predicting an underground reservoir based on outcrop carbonate reservoir modeling.

Background technique

Due to the strong heterogeneity of carbonate reservoirs, the characterization and evaluation of the heterogeneity of carbonate reservoirs has become one of the key issues in the exploration and development of carbonate reservoirs. Reservoir geological modeling is an important means of reservoir heterogeneity characterization and evaluation. Generally speaking, reservoir geological modeling includes three scales: one is macro-scale reservoir geological modeling based on the understanding of the distribution law of reservoir geological bodies and non-reservoir geological bodies, revealing the distribution law of reservoirs in the sequence framework, Provide a basis for the evaluation of favorable reservoir distribution areas and exploration fields; second, reservoir-scale reservoir geological modeling based on reservoir heterogeneity and evaluation understanding, revealing the distribution pattern and quality of flow units and barriers; third, The micro-scale reservoir geological modeling based on the understanding of the pore-throat structure of the reservoir reveals the seepage characteristics of the reservoir and its influence on the development effect.

In the prior art, in the oilfield development stage, in order to achieve reservoir prediction that can meet the second reservoir scale standard, it is usually necessary to establish a reservoir scale reservoir geological model based on well and seismic data. , the limitation of the quantity and quality of seismic data, and the current status of reservoir-scale outcrop reservoir geological modeling in the two-dimensional stage, there are unclear geostatistical basis for carbonate reservoir geological modeling, reservoir modeling Imperfect technologies and procedures restrict the establishment of reservoir-scale 3D outcrop carbonate reservoir geological models, making it difficult to establish models that meet the reservoir-scale standards and conform to the actual geological conditions. Prediction of underground reservoir availability under standard.

Based on this, there is an urgent need to provide an effective way to accurately predict the effectiveness of underground reservoirs under reservoir scale standards.

SUMMARY OF THE INVENTION

In view of the problems in the prior art, the present application provides an underground reservoir prediction method and device based on outcrop carbonate reservoir modeling, which can accurately and quickly establish a three-dimensional geological model for outcrop carbonate reservoirs , and can effectively improve the prediction accuracy and reliability of the underground reservoir effectiveness under the reservoir scale standard.

In order to solve the above-mentioned technical problems, the application provides the following technical solutions:

In a first aspect, the present application provides an underground reservoir prediction method based on outcrop carbonate reservoir modeling, including:

Obtain a two-dimensional outcrop geological model corresponding to the outcrop carbonate rock reservoir, and perform three-dimensional digital scanning and labeling processing on the outcrop carbonate rock reservoir to obtain a corresponding three-dimensional image, wherein the outcrop carbonate rock The reservoir is pre-divided into a plurality of stratigraphic units;

According to the 3D image and the lithofacies information in the measured section of the outcrop carbonate reservoir, obtain a 3D sedimentary microfacies model corresponding to each of the stratigraphic units;

According to the three-dimensional sedimentary microfacies model corresponding to each of the formation units, the three-dimensional porosity model and the three-dimensional permeability model corresponding to each of the formation units are obtained respectively, so as to obtain the corresponding three-dimensional sedimentary microfacies model of each of the formation units according to the corresponding three-dimensional sedimentary microfacies model of each of the formation units. , a three-dimensional porosity model and a three-dimensional permeability model to predict the effective reservoir in the underground reservoir corresponding to the outcrop carbonate reservoir.

Further, before obtaining the two-dimensional outcrop geological model corresponding to the outcrop carbonate reservoir, the method further includes:

According to the actual geological conditions of the outcrop carbonate reservoir, the outcrop carbonate reservoir is divided into multiple survey lines;

determining the stratigraphic layers of the outcrop carbonate reservoir, and dividing a plurality of the stratigraphic units according to the stratigraphic layers;

And, the lithofacies classification in the outcrop carbonate reservoir is determined, and the rock structure section corresponding to each of the survey lines is determined.

Further, obtaining the two-dimensional outcrop geological model corresponding to the outcrop carbonate reservoir includes:

obtaining a two-dimensional sedimentary microfacies model of the outcrop carbonate reservoir;

Reservoir evaluation is performed on each section in the two-dimensional sedimentary microfacies model to obtain a two-dimensional outcrop geological model corresponding to the outcrop carbonate reservoir.

Further, the obtaining of the two-dimensional sedimentary microfacies model of the outcrop carbonate reservoir includes:

According to the rock structure section corresponding to each of the survey lines, a two-dimensional sedimentary microfacies model of the outcrop carbonate reservoir is established.

Further, performing reservoir evaluation on each section in the two-dimensional sedimentary microfacies model to obtain a two-dimensional outcrop geological model corresponding to the outcrop carbonate reservoir, including:

obtaining physical property test results of multiple core samples of the outcrop carbonate reservoir;

According to the physical property test results and the pre-obtained correspondence between porosity, permeability and lithofacies, the reservoirs are carried out for each section in the two-dimensional sedimentary microfacies model of the outcrop carbonate reservoir. The evaluation is performed to obtain a two-dimensional outcrop geological model corresponding to the outcrop carbonate reservoir.

Further, performing three-dimensional digital scanning and labeling processing on the outcrop carbonate reservoir to obtain a corresponding three-dimensional image, including:

Performing three-dimensional digital scanning on the outcrop carbonate rock reservoir to obtain a three-dimensional point cloud image corresponding to the outcrop carbonate rock reservoir;

According to the two-dimensional outcrop geological model, stratigraphic tracking and labeling processing is performed on the three-dimensional point cloud image to obtain a corresponding three-dimensional image.

Further, performing three-dimensional digital scanning on the outcrop carbonate rock reservoir to obtain a three-dimensional point cloud image corresponding to the outcrop carbonate rock reservoir, including:

collecting spatial orientation data of the outcrop carbonate reservoir by using a lidar mapping instrument;

The spatial orientation data is edited by data processing software to form a three-dimensional point cloud image of the outcrop carbonate reservoir.

Further, performing stratigraphic tracking and labeling processing on the three-dimensional point cloud image according to the two-dimensional outcrop geological model to obtain a corresponding three-dimensional image, including:

Using image acquisition equipment to collect panoramic photos of the outcrop carbonate reservoir;

According to the panoramic photo and the two-dimensional outcrop geological model, stratigraphic tracking and interpretation processing is performed on the three-dimensional point cloud image, and the positions of sampling points are calibrated on the three-dimensional point cloud image to obtain the three-dimensional image.

Further, according to the three-dimensional image and the lithofacies information in the measured section of the outcrop carbonate reservoir, the three-dimensional sedimentary microfacies model corresponding to each of the stratigraphic units is obtained, including:

The information corresponding to the three-dimensional image is loaded into the three-dimensional geological modeling tool, and the lithofacies information in the measured section of the outcrop carbonate reservoir is used as a constraint, and three-dimensional quantitative random modeling is carried out for each of the stratigraphic units respectively. The three-dimensional sedimentary microfacies model corresponding to each of the stratigraphic units is obtained.

In a second aspect, the present application provides an underground reservoir prediction device based on outcrop carbonate reservoir modeling, including:

A three-dimensional digital outcrop acquisition module is used to acquire a two-dimensional outcrop geological model corresponding to an outcrop carbonate rock reservoir, and perform three-dimensional digital scanning and labeling processing on the outcrop carbonate rock reservoir to obtain a corresponding three-dimensional image, wherein , the outcrop carbonate reservoir is pre-divided into a plurality of stratigraphic units;

a three-dimensional sedimentary microfacies model building module, configured to obtain a three-dimensional sedimentary microfacies model corresponding to each of the stratigraphic units according to the three-dimensional image and the lithofacies information in the measured section of the outcrop carbonate reservoir;

The underground reservoir prediction module is used to obtain the corresponding three-dimensional porosity model and the three-dimensional permeability model of each of the formation units according to the corresponding three-dimensional sedimentary microfacies model of each of the formation units, so as to obtain the corresponding three-dimensional porosity model and the three-dimensional permeability model of each of the formation units respectively, so as to obtain the corresponding three-dimensional porosity model and the three-dimensional permeability model of each of the formation units according to the corresponding three-dimensional sedimentary microfacies model of each of the formation units. The corresponding three-dimensional sedimentary microfacies model, three-dimensional porosity model and three-dimensional permeability model respectively predict the effective reservoir in the underground reservoir corresponding to the outcrop carbonate reservoir.

Further, it also includes:

A survey line division module, used for dividing a plurality of survey lines on the outcrop carbonate rock reservoir according to the actual geological conditions of the outcrop carbonate rock reservoir;

a stratigraphic unit division module, configured to determine the stratigraphic layers of the outcrop carbonate reservoir, and obtain a plurality of the stratigraphic units according to the stratigraphic layer division;

The rock structure section acquisition module is used for determining the lithofacies classification in the outcrop carbonate reservoir, and according to the rock structure section corresponding to each of the survey lines.

Further, the three-dimensional digital outcrop acquisition module includes:

a two-dimensional sedimentary microfacies model acquisition unit, used for acquiring the two-dimensional sedimentary microfacies model of the outcrop carbonate reservoir;

The reservoir evaluation unit is used to perform reservoir evaluation on each section in the two-dimensional sedimentary microfacies model, and obtain a two-dimensional outcrop geological model corresponding to the outcrop carbonate reservoir.

Further, the two-dimensional depositional microphase model acquisition unit includes:

The two-dimensional sedimentary microfacies model construction subunit is used for establishing a two-dimensional sedimentary microfacies model of the outcrop carbonate reservoir according to the rock structure section corresponding to each of the survey lines.

Further, the reservoir evaluation unit includes:

a physical property testing subunit, used for acquiring physical property testing results of multiple core samples of the outcrop carbonate reservoir;

The two-dimensional outcrop geological model constructs a sub-unit, which is used for the two-dimensional deposition of the outcrop carbonate reservoir according to the physical property test results and the pre-acquired correspondence between porosity, permeability and lithofacies Reservoir evaluation is performed on each section in the microfacies model to obtain a two-dimensional outcrop geological model corresponding to the outcrop carbonate reservoir.

Further, the three-dimensional digital outcrop acquisition module includes:

a three-dimensional digital scanning unit, used for performing three-dimensional digital scanning on the outcrop carbonate rock reservoir to obtain a three-dimensional point cloud image corresponding to the outcrop carbonate rock reservoir;

The image processing unit is configured to perform stratigraphic tracking and labeling processing on the three-dimensional point cloud image according to the two-dimensional outcrop geological model to obtain a corresponding three-dimensional image.

Further, the three-dimensional digital scanning unit includes:

a spatial orientation data acquisition subunit, used for collecting the spatial orientation data of the outcrop carbonate reservoir by using a lidar mapping instrument;

The spatial orientation data editing subunit is used to edit the spatial orientation data through data processing software to form a three-dimensional point cloud image of the outcrop carbonate reservoir.

Further, the image processing unit includes:

A panorama photo acquisition subunit, used for acquiring a panorama photo of the outcrop carbonate reservoir by using an image acquisition device;

The image processing calibration subunit is used to perform stratigraphic tracking and interpretation processing on the three-dimensional point cloud image according to the panoramic photo and the two-dimensional outcrop geological model, and to calibrate the sampling point position on the three-dimensional point cloud image to obtain the three-dimensional image.

Further, the three-dimensional sedimentary microfacies model building module includes:

The three-dimensional quantitative stochastic modeling unit is used to load the information corresponding to the three-dimensional image into the three-dimensional geological modeling tool, and is constrained by the lithofacies information in the measured section of the outcrop carbonate reservoir, respectively, for each Three-dimensional quantitative stochastic modeling is performed on the stratigraphic units to obtain three-dimensional sedimentary microfacies models corresponding to each of the stratigraphic units.

In a third aspect, the present application provides an electronic device, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, when the processor executes the program, the outcrop carbonate-based carbonate is implemented Steps of a subsurface reservoir prediction method for rock reservoir modeling.

In a fourth aspect, the present application provides a computer-readable storage medium on which a computer program is stored, and when the computer program is executed by a processor, realizes the underground reservoir prediction method based on outcrop carbonate reservoir modeling A step of.

It can be seen from the above technical solutions that the present application provides an underground reservoir prediction method and device based on outcrop carbonate reservoir modeling. By obtaining the two-dimensional outcrop geological model corresponding to the outcrop carbonate reservoir, performing three-dimensional digital scanning and labeling processing on the outcrop carbonate reservoir to obtain a corresponding three-dimensional image, wherein the outcrop carbonate reservoir is pre-divided into a plurality of stratigraphic units; according to the three-dimensional image and the According to the lithofacies information in the measured section of the outcrop carbonate reservoir, the three-dimensional sedimentary microfacies model corresponding to each of the stratigraphic units is obtained; according to the three-dimensional sedimentary microfacies model corresponding to each of the stratigraphic units, the The three-dimensional porosity model and the three-dimensional permeability model corresponding to each of the formation units are obtained, so that the outcrop carbonate rock reservoir is determined according to the corresponding three-dimensional sedimentary microfacies model, three-dimensional porosity model and three-dimensional permeability model of each of the formation units. It can accurately and quickly establish a three-dimensional geological model for outcrop carbonate reservoirs, and can effectively improve the effectiveness of underground reservoirs under the reservoir scale standard. Prediction accuracy and reliability, which in turn can ensure the accuracy of oil exploration based on the prediction results and reduce the cost of oil exploration.

Description of drawings

In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the accompanying drawings that need to be used in the description of the embodiments or the prior art. Obviously, the drawings in the following description are For some embodiments of the present application, for those of ordinary skill in the art, other drawings can also be obtained according to these drawings without any creative effort.

FIG. 1 is a schematic flowchart of an underground reservoir prediction method based on outcrop carbonate reservoir modeling according to an embodiment of the present application.

FIG. 2 is a schematic flowchart of steps 001 to 003 in the method for predicting an underground reservoir based on outcrop carbonate reservoir modeling in an embodiment of the present application.

FIG. 3 is a schematic flowchart of step 100 in the method for predicting an underground reservoir based on outcrop carbonate reservoir modeling in an embodiment of the present application.

FIG. 4 is a schematic diagram of two types of flowcharts of step 100 in the underground reservoir prediction method based on outcrop carbonate reservoir modeling in the embodiment of the present application.

FIG. 5 is a schematic logical diagram of an underground reservoir prediction method based on outcrop carbonate reservoir modeling in an embodiment of the present application.

FIG. 6 is a schematic diagram of the macroscopic features of the Shoerblak Formation in the Sugetblak outcrop in an application example of the present application.

FIG. 7 is a schematic diagram of a two-dimensional sedimentary microfacies model of the Shoerbrak Formation in the Sugetbulak outcrop area in the application example of the present application.

FIG. 8 is a schematic diagram of a two-dimensional reservoir geological model of the Xiaoerbulak Formation in the Sugetbulak outcrop area in the application example of the application.

FIG. 9 is a schematic diagram of a three-dimensional digital outcrop of the Shoalbrak group in the Sugetbulak outcrop area in an application example of the present application.

FIG. 10 is an example schematic diagram of the lithofacies model slice (Xiaoshang 2 top) in the application example of the present application.

FIG. 11 is an example schematic diagram of the lithofacies model slice (Xiao Shang 2 bottom) in the application example of the present application.

FIG. 12 is an exemplary schematic diagram of a three-dimensional porosity model in an application example of the present application.

FIG. 13 is an exemplary schematic diagram of the porosity model slice (2 tops on Xiao) in the application example of the present application.

FIG. 14 is an example schematic diagram of the porosity model slice (2 bottom of the Xiao) in the application example of the present application.

FIG. 15 is an exemplary schematic diagram of a three-dimensional permeability model in an application example of the present application.

FIG. 16 is a schematic diagram of an example of a permeability model slice (2 tops on the top) in an application example of the present application.

FIG. 17 is an exemplary schematic diagram of the permeability model slice (the upper part and the lower part) in the application example of the present application.

FIG. 18 is a schematic diagram of an underground reservoir prediction device based on outcrop carbonate reservoir modeling according to an embodiment of the present application.

FIG. 19 is a schematic structural diagram of an electronic device in an embodiment of the present application.

Detailed ways

In order to make the purposes, technical solutions and advantages of the embodiments of the present application more clear, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments It is a part of the embodiments of the present application, but not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the protection scope of the present application.

Considering that the existing technology is limited by the quantity and quality of wells and seismic data, and the current status of reservoir-scale outcrop reservoir geological modeling is in the two-dimensional stage, there are geostatistics that constitute the geological modeling of carbonate rock reservoirs. Unclear scientific basis, imperfect reservoir modeling technology and process, etc., restrict the establishment of reservoir-scale 3D outcrop carbonate reservoir geological models, making it difficult to establish a geological model that can meet reservoir-scale standards. Therefore, it is impossible to realize the problem of predicting the effectiveness of underground reservoirs under the reservoir scale standard. The embodiment of the present application provides an underground reservoir prediction method based on outcrop carbonate reservoir modeling, and an underground reservoir prediction method based on outcrop carbonate reservoir modeling. An underground reservoir prediction device, electronic device and storage medium for modeling salt rock reservoirs, by obtaining a two-dimensional outcrop geological model corresponding to an outcrop carbonate rock reservoir, and performing a three-dimensional digital calculation on the outcrop carbonate rock reservoir. Scan and label processing to obtain a corresponding three-dimensional image, wherein the outcrop carbonate reservoir is pre-divided into a plurality of stratigraphic units; according to the three-dimensional image and the measured section of the outcrop carbonate reservoir According to the lithofacies information corresponding to each of the stratigraphic units, the three-dimensional sedimentary microfacies model corresponding to each of the stratigraphic units is obtained; The three-dimensional permeability model is used to determine the effective reservoir in the underground reservoir corresponding to the outcrop carbonate reservoir according to the three-dimensional sedimentary microfacies model, the three-dimensional porosity model and the three-dimensional permeability model corresponding to each of the formation units. Prediction can accurately and quickly establish a three-dimensional geological model for outcrop carbonate reservoirs, and can effectively improve the prediction accuracy and reliability of the effectiveness of underground reservoirs under the reservoir scale standard, and then can predict The results ensure the accuracy of oil exploration and reduce the cost of oil exploration.

The present application provides an underground reservoir prediction based on outcrop carbonate reservoir modeling, whose execution body can be an underground reservoir prediction device, processor, server or user terminal device based on outcrop carbonate reservoir modeling In an embodiment of the method, referring to FIG. 1 , the underground reservoir prediction method based on outcrop carbonate reservoir modeling specifically includes the following contents:

Step 100: Obtain a two-dimensional outcrop geological model corresponding to the outcrop carbonate reservoir, and perform three-dimensional digital scanning and labeling processing on the outcrop carbonate reservoir to obtain a corresponding three-dimensional image, wherein the outcrop carbon Salt rock reservoirs are pre-divided into stratigraphic units.

It can be understood that the outcrop carbonate reservoir refers to a carbonate reservoir with an outcrop area exposed above the surface. Among them, the storage space of the carbonate reservoir is usually divided into three types: primary pores, caves and fractures. Compared with the sandstone reservoir, the storage space of the carbonate reservoir has many types and secondary changes. Larger, with greater complexity and variety.

Among them, the three-dimensional digital scanning can convert the three-dimensional information of the object into a digital signal that can be directly processed by the computer, which provides a very convenient and fast means for the digitization of the object. Three-dimensional digital scanning technology can realize non-contact measurement, and has the advantages of high speed and high precision. And its measurement results can be directly interfaced with a variety of software, which makes it increasingly popular in CAD, CAM, CIMS and other technical applications.

The marking processing refers to marking the location of the collection point on the collected image corresponding to the outcrop carbonate reservoir.

In addition, the three-dimensional image refers to the three-dimensional point cloud image of the outcrop area of the carbonate reservoir with the location mark of the collection point, and the three-dimensional point cloud image can be applied to the outcrop using ILRIS-3D lidar. The profile of the carbonate reservoir is digitally scanned in 3D and output after data processing.

Step 200: According to the three-dimensional image and the lithofacies information in the measured section of the outcrop carbonate reservoir, obtain a three-dimensional sedimentary microfacies model corresponding to each of the stratigraphic units.

In a specific example, the petrographic information may include petrographic classification.

Step 300: According to the three-dimensional sedimentary microfacies model corresponding to each of the formation units, respectively obtain the corresponding three-dimensional porosity model and the three-dimensional permeability model of each of the formation units, so as to obtain the corresponding three-dimensional sedimentary model of each of the formation units according to the corresponding three-dimensional sedimentary model of the formation unit. The microfacies model, the three-dimensional porosity model and the three-dimensional permeability model predict the effective reservoir in the underground reservoir corresponding to the outcrop carbonate reservoir.

It can be seen from the above description that the underground reservoir prediction method based on outcrop carbonate reservoir modeling provided by the embodiments of the present application can accurately and quickly establish a three-dimensional geological model for outcrop carbonate reservoirs, and can effectively The prediction accuracy and reliability of the validity of the underground reservoir under the reservoir scale standard can be improved, so as to ensure the accuracy of oil exploration and reduce the cost of oil exploration according to the prediction results.

In the embodiment of the underground reservoir prediction method based on outcrop carbonate reservoir modeling of the present application, referring to FIG. 2 , in the underground reservoir prediction method based on outcrop carbonate reservoir modeling Before step 100 in , it also specifically includes the following content:

Step 001: According to the actual geological conditions of the outcrop carbonate reservoir, the outcrop carbonate reservoir is divided into multiple survey lines.

Step 002: Determine the stratigraphic layers of the outcrop carbonate reservoir, and obtain a plurality of the stratigraphic units according to the stratigraphic layers.

Step 003: Determine the lithofacies classification in the outcrop carbonate reservoir, and according to the rock structure profiles corresponding to each of the survey lines.

Specifically, the preliminary work before step 100 in the underground reservoir prediction method based on outcrop carbonate reservoir modeling may include the following contents:

(1) Regional geological survey technology: outcrop modeling section selection (it is recommended that the modeling section is perpendicular to the facies zone, the spread width is > 2km, and more than 3 sections are measured), and research on the distribution law of reservoirs in the sequence framework.

(2) Outcrop profile measurement technology: In the outcrop area of a reservoir scale, three or more profiles are selected, and stratigraphic stratification and thickness measurement with lithofacies as the unit are carried out.

(3) The lithofacies identification technology combining macro and micro facies: to clarify the types of lithofacies and sedimentary microfacies, and the vertical variation law, and to establish the type of lithofacies assemblage, the facies sequence, and the relationship with sea level rise and fall.

(4) Outcrop lithofacies transverse facies tracking technology: to clarify the contrast relationship, facies transition and spatial distribution of lithofacies between the measured sections.

(5) Reservoir evaluation technology based on lithofacies: evaluation of reservoir physical properties, evaluation of reservoir pore throat structure, establishment of the relationship between lithofacies and reservoir physical properties, and identification of the main controlling factors for reservoir development.

In an embodiment of the underground reservoir prediction method based on outcrop carbonate reservoir modeling of the present application, referring to FIG. 3 , in the underground reservoir prediction method based on outcrop carbonate reservoir modeling Step 100 specifically includes the following contents:

Step 101: Obtain a two-dimensional sedimentary microfacies model of the outcrop carbonate reservoir.

In step 101, the underground reservoir prediction device based on outcrop carbonate reservoir modeling establishes a two-dimensional deposition of the outcrop carbonate reservoir according to the rock structure profiles corresponding to each of the survey lines Microphase model.

Step 102: Perform reservoir evaluation on each section in the two-dimensional sedimentary microfacies model to obtain a two-dimensional outcrop geological model corresponding to the outcrop carbonate reservoir.

In step 102, the underground reservoir prediction device based on outcrop carbonate rock reservoir modeling obtains physical property test results of multiple core samples of the outcrop carbonate rock reservoir; according to the physical property test results, And, based on the pre-acquired correspondence between porosity, permeability and lithofacies, perform reservoir evaluation on each section in the two-dimensional sedimentary microfacies model of the outcrop carbonate reservoir, and obtain the outcrop carbon The two-dimensional outcrop geological model corresponding to the salt rock reservoir.

In the embodiment of the underground reservoir prediction method based on outcrop carbonate reservoir modeling of the present application, referring to FIG. 4 , in the underground reservoir prediction method based on outcrop carbonate reservoir modeling Step 100 also specifically includes the following contents:

Step 103 : performing a three-dimensional digital scan on the outcrop carbonate rock reservoir to obtain a three-dimensional point cloud image corresponding to the outcrop carbonate rock reservoir.

In step 103, the underground reservoir prediction device based on outcrop carbonate reservoir modeling controls the lidar mapping instrument to collect spatial orientation data of the outcrop carbonate reservoir; The spatial orientation data is edited to form a three-dimensional point cloud image of the outcrop carbonate reservoir.

In a specific example, the lidar mapping instrument may specifically be an ILRIS-3D lidar.

Step 104: Perform stratigraphic tracking and labeling processing on the three-dimensional point cloud image according to the two-dimensional outcrop geological model to obtain a corresponding three-dimensional image.

In step 104, the underground reservoir prediction device based on outcrop carbonate reservoir modeling controls an image acquisition device to collect a panoramic photo of the outcrop carbonate reservoir; and according to the panoramic photo and the For a two-dimensional outcrop geological model, stratigraphic tracking and interpretation processing is performed on the three-dimensional point cloud image, and the positions of sampling points are calibrated on the three-dimensional point cloud image to obtain the three-dimensional image.

In a specific example, the image acquisition device may be a GigaPan camera. The Gigapan camera is a camera with the highest pixel in the world, with a pixel of more than 1 billion, and the size of the captured photo exceeds 1 GB.

In the embodiment of the underground reservoir prediction method based on outcrop carbonate reservoir modeling of the present application, step 200 in the underground reservoir prediction method based on outcrop carbonate reservoir modeling is specifically Contains the following:

Step 201: Load the information corresponding to the three-dimensional image into the three-dimensional geological modeling tool, and take the lithofacies information in the measured section of the outcrop carbonate reservoir as a constraint, and perform three-dimensional analysis on each of the stratigraphic units respectively. Quantitative stochastic modeling is performed to obtain a three-dimensional sedimentary microfacies model corresponding to each of the stratigraphic units.

In a specific example, the three-dimensional geological modeling tool may be Petrel software, wherein petrel is developed by Schlumberger, an exploration and development integration platform centered on a three-dimensional geological model, and belongs to professional geophysics software.

Based on the above content, it can be seen that the underground reservoir prediction method based on outcrop carbonate reservoir modeling provided by this application is an integration of a series of technologies, and is suitable for outcrop geological modeling of all facies-controlled carbonate reservoirs. See Figure 5, which specifically includes the following:

1. Point out the statistical basis for the geological modeling of facies-controlled carbonate reservoirs

(1) There are regular changes in the contact relationship, development scale, morphological characteristics, distribution range and vertical facies sequence of different lithofacies types in different depositional backgrounds, which are consistent with Wilson's facies law;

(2) The facies belt is closely related to lithofacies development characteristics, reservoir characteristics, reservoir genesis and distribution.

2. Established a series of reservoir-scale 3D outcrop carbonate reservoir geological modeling techniques

(1) Regional geological survey technology: outcrop modeling section selection (it is recommended that the modeling section is perpendicular to the facies zone, the spread width is > 2km, and more than 3 sections are measured), and the research on the distribution law of reservoirs in the sequence framework;

(2) Outcrop profile measurement technology: select more than three profiles in an outcrop area of a reservoir scale, and perform formation stratification and thickness measurement with lithofacies as a unit;

(3) The lithofacies identification technology combining macro- and micro-facies: clarify the types of lithofacies and sedimentary microfacies, and the vertical variation law, and establish the type of lithofacies assemblage, facies sequence, and the relationship with sea level rise and fall;

(4) Outcrop lithofacies transverse facies tracking technology: to clarify the contrast relationship, facies transformation and spatial distribution of lithofacies between the measured sections;

(5) Reservoir evaluation technology based on lithofacies: evaluation of reservoir physical properties, evaluation of reservoir pore throat structure, establishing the relationship between lithofacies and reservoir physical properties, and clarifying the main controlling factors of reservoir development;

(6) Two-dimensional reservoir geological modeling technology of outcrop profile: establish a two-dimensional reservoir geological model, characterize the heterogeneity of the reservoir on the two-dimensional profile, evaluate the reservoir, and study the main controlling factors of the reservoir heterogeneity and changing laws;

(7) 3D digital outcrop construction technology: use Lidar (Lidar) and other surveying and mapping instruments to collect spatial orientation data of outcrop profiles, and use GigaPan (intelligent PTZ) to collect high-resolution panoramic photos of outcrop profiles; use cloud data processing software such as Polyworks The spatial orientation data is edited to form a 3D point cloud image of the outcrop profile. At the same time, combined with high-resolution panoramic photos, stratigraphic tracking and interpretation are carried out in the 3D point cloud image, and the location of sampling points is calibrated, so as to complete the construction of a 3D digital outcrop for coverage. The area provides data volume through interpolation method lithofacies identification and reservoir 3D construction;

(8) Reservoir 3D construction technology: According to the modeling idea of facies-controlled reservoirs, a 3D lithofacies model of reservoirs based on 3D digital outcrops is constructed by applying modeling software such as Petrel, and then the reservoir porosity under lithofacies control is constructed. model and permeability model.

3. The results of geological modeling of reservoir-scale 3D outcrop carbonate reservoirs are clarified

(1) Reservoir deposition pattern map based on regional geological survey;

(2) Several sheets of reservoir evaluation maps corresponding to the measured stratigraphic profiles (including facies sequence and combination type, sedimentary facies type, sequence, porosity and permeability data, etc.);

(3) Two-dimensional reservoir geological model of outcrop profile (revealing the distribution law of reservoir and barrier layer on two-dimensional profile);

(4) Three-dimensional reservoir geological model (three-dimensional sedimentary microfacies model, three-dimensional porosity model and three-dimensional permeability model).

4. Integrate reservoir-scale 3D outcrop carbonate reservoir geological modeling techniques and processes

It integrates the selection of modeling profiles involved in reservoir-scale 3D outcrop carbonate reservoir geological modeling, the fine anatomy of outcrop profile reservoirs, the series of modeling techniques, the construction of 3D geological models of reservoirs, the types of drawings and specification requirements, etc. The reservoir-scale 3D outcrop carbonate reservoir geological modeling technology and process are constructed, which provides a means for understanding the heterogeneity of similar underground reservoirs and the establishment of a 3D spatial distribution geological model of high-quality reservoirs and barriers.

It can be seen from the above content that the underground reservoir prediction method based on outcrop carbonate reservoir modeling provided by the embodiments of the present application clarifies the statistical basis for constituting the geological modeling of facies-controlled carbonate reservoirs, and the oil The reservoir-scale 2D outcrop carbonate reservoir geological modeling has advanced to a new stage of reservoir-scale 3D outcrop carbonate reservoir geological modeling. The reservoir-scale three-dimensional outcrop carbonate reservoir geological model constructed according to the embodiments of the present application will provide a basis for understanding the heterogeneity and quality of similar underground reservoirs, the distribution of high-quality reservoirs and barrier layers in the oilfield development stage, It provides calibration for the construction of a reservoir-scale carbonate reservoir geological model that is more in line with geological reality based on limited well and seismic data.

To further illustrate the solution, the present application also provides a specific application example of an underground reservoir prediction method based on outcrop carbonate reservoir modeling, the underground reservoir prediction method based on outcrop carbonate reservoir modeling. It can be used to establish a three-dimensional outcrop carbonate reservoir geological model, characterize the heterogeneity of the reservoir in three-dimensional space, evaluate the effectiveness of the reservoir, and focus on solving the problem of effective carbonate reservoirs and barriers. The problem of distribution prediction is an important means to understand the heterogeneity of carbonate reservoirs and evaluate them. It is also an important bridge to understand the heterogeneity and quality of similar underground reservoirs, and to predict the distribution of high-quality reservoirs and barrier layers. . Through the fine anatomy of outcrop reservoir rock types, reservoir space and sedimentary microfacies, the three-dimensional spatial distribution pattern of lithofacies is established, and the correlation between lithofacies assemblages and subfacies, microfacies, physical properties (even microscopic pore-throat structure) is established It can characterize the heterogeneity of reservoirs, clarify the main controlling factors and distribution rules of the development of high-quality reservoirs and barriers, and provide geological information for understanding the heterogeneity of similar underground reservoirs and the three-dimensional spatial distribution of high-quality reservoirs and barriers. The model is described as follows:

Taking the geological modeling of the 3D outcrop reservoir of the Lower Cambrian Xiaoerbulak Formation in the Sugetbulak outcrop area in the Aksu area of the Tarim Basin as an example.

(1) Selection and measurement of the research profile: According to the actual geological conditions, combined with the horizontal and vertical distribution rules of reef flats, four survey lines were measured within the range of nearly 1km in the outcrop area, see Figure 6. Through the fine measurement, description and lateral tracking analysis of the Sugetbulak section, the Xiaoerbulak Formation is divided into 35 layers with a thickness of 144.5m, which are divided into upper, middle and lower sections according to whether reefs and flats are developed. .

And, a total of 8 lithofacies were identified based on macroscopic description and microscopic identification.

(2) Macro- and micro-combination to establish rock structure profiles: A total of 8 types of lithofacies were identified according to the description of macro outcrops and the identification of micro slices, and rock structure profiles of 4 survey lines were established. for a complete three-level sequence.

(3) Establishment of a two-dimensional outcrop geological model: A sedimentary microfacies model was established by synthesizing the lithofacies profiles of the four survey lines and the lateral tracking and comparative analysis, as shown in Figure 7; the physical properties of the 148 collected plunger samples were tested and analyzed. The correlation between porosity, permeability and lithofacies, and then the reservoir is evaluated for each section, and the reservoir geological model is established, see Figure 8.

Specifically, the specific way to establish a two-dimensional outcrop geological model is as follows:

3-1) According to the actual situation of the outcrop, it is preferable to measure multiple sections (more than 3), collect typical samples, and carry out stratification and segmentation;

3-2) According to the macroscopic outcrop feature description and the microscopic thin-film lithofacies identification, establish the rock structure section of each section, and carry out high-frequency sequence division at the same time;

3-3) In the sequence framework, carry out multi-section comparison, and establish a two-dimensional sedimentary microfacies (lithofacies) model in combination with the sedimentary model, and obtain the vertical and lateral distribution of different sedimentary microfacies (lithofacies) law;

3-4) Carry out correlation analysis on the lithofacies and measured porosity and permeability data of each sample, then carry out reservoir evaluation for each profile, and then carry out multi-profile reservoir comparison analysis to establish a two-dimensional reservoir geological model , the distribution law of the reservoir in the vertical and lateral directions is obtained.

The 2D sedimentary microfacies (lithofacies) model and the 2D reservoir geological model can be combined to analyze the homogeneity, main controlling factors and distribution law of the reservoir.

(4) Establish a digital outcrop: that is, use the ILRIS-3D laser radar to perform three-dimensional digital scanning of the section, and after data processing, output a three-dimensional point cloud image of the outcrop with a resolution of 2cm, and then according to the two-dimensional outcrop geological model information, in The stratigraphic tracking and interpretation are carried out in the 3D point cloud image of the outcrop, and the sampling position, special deposition and structural phenomena are marked, and the 3D digital outcrop is constructed, see Fig. 9.

(5) Establish a 3D outcrop geological model: load the digital outcrop information into Petrel, and according to the idea of facies-controlled reservoirs, take the lithofacies information in the measured profile (virtual well) as a constraint, and carry out a 3D analysis of each stratigraphic unit. Quantitative stochastic modeling is used to establish a three-dimensional sedimentary microfacies model, and then porosity and permeability simulations are performed in each phase unit to establish a porosity model and a permeability model, see Figure 10 to Figure 17.

(6) Establish a three-dimensional lithofacies model, a three-dimensional porosity model and a three-dimensional permeability model through the methods of the above steps (1) to (5), and according to the corresponding three-dimensional sedimentary microfacies model, three-dimensional pores of each of the formation units The degree model and the three-dimensional permeability model are used to predict the effective reservoir in the underground reservoir corresponding to the outcrop carbonate reservoir, which specifically includes:

6-1) The 3D lithofacies model finely depicts the lateral distribution characteristics and vertical changes of eight lithofacies such as lamellarite, thrombolite, stromatolite and algal sand dolomite in the Xiaoerbulak Formation Generally, it can be divided into 3 sections: the lower section mainly develops argillaceous-powder crystal dolomite, which is thicker; the lower section of the middle section mainly develops interbedded thrombolite dolomite and lamellar dolomite, and develops algae with a built-up structure. Framework dolomite, the upper part of the middle section mainly develops layered algal sand dolomite and stromatolite dolomite; the upper section mainly develops micrite powder dolomite intercalated with a thin layer of bonded sand dolomite. Obviously, the 3D model reflects the sedimentary characteristics of "small reefs and large shoals" in the Xiaoerbulak Formation as a whole, and the microbial reefs and shoals are mainly developed in the middle section.

6-2) The three-dimensional porosity model describes the relationship between different lithofacies and porosity and their homogeneity: the porosity of algal lattice dolomite, algal sand dolomite and stromatolite dolomite with built-up features in the middle section It has the highest porosity and good homogeneity, and can be evaluated as a type I reservoir; the porosity of thrombolite dolomite and bound algal-cut dolomite is second, and has a certain degree of heterogeneity on the plane, which can be comprehensively evaluated It is a type II reservoir; the lamellar dolomite in the middle section and the micrite dolomite in the upper and lower sections have low porosity as a whole, and are comprehensively evaluated as non-reservoirs.

6-3) The three-dimensional permeability model depicts the relationship between different lithofacies and permeability and their homogeneity: on the whole, the Xiaoerbulake Formation dolomite has low permeability, but the algal-framework dolomite, algal dolomite Sandy dolomite and stromatolite dolomite have relatively high permeability and still have certain seepage properties, while lamellar dolomite is the densest.

Based on the above three-dimensional outcrop reservoir geological model, it can be judged that the Lower Cambrian Xiaoerbulak Formation in the Tarim Basin is generally developed with medium-high porosity-medium-low permeability reef-shoal facies reservoirs, algal sand beaches and stromatolite beaches in the middle. , algal shelf reefs and the clotted rock beaches on their wings are favorable reservoir facies belts, while lamellar dolomite can form a tight barrier layer with an effective reservoir thickness of 45m, which has facies control, cyclicity and scale. sex. Therefore, according to the 3D outcrop model, the vertical wells should be drilled in the center of the reef as much as possible, and the horizontal wells should be deployed as far as possible to communicate with the sand beach belt in the upper middle section and avoid the laminar barrier.

The present application provides an embodiment of an underground reservoir prediction device based on outcrop carbonate reservoir modeling for performing all or part of the above-mentioned underground reservoir prediction method based on outcrop carbonate reservoir modeling 18, the underground reservoir prediction device based on outcrop carbonate reservoir modeling specifically includes the following contents:

The three-dimensional digital outcrop acquisition module 10 is used for acquiring a two-dimensional outcrop geological model corresponding to the outcrop carbonate reservoir, and performing three-dimensional digital scanning and labeling processing on the outcrop carbonate reservoir to obtain a corresponding three-dimensional image, Wherein, the outcrop carbonate reservoir is pre-divided into a plurality of stratigraphic units;

A three-dimensional sedimentary microfacies model building module 20, configured to obtain a three-dimensional sedimentary microfacies model corresponding to each of the stratigraphic units according to the three-dimensional image and the lithofacies information in the measured section of the outcrop carbonate reservoir;

The underground reservoir prediction module 30 is configured to obtain the three-dimensional porosity model and the three-dimensional permeability model corresponding to each of the formation units according to the three-dimensional sedimentary microfacies model corresponding to each of the formation units, so as to obtain the corresponding three-dimensional porosity model and the three-dimensional permeability model of each of the formation units respectively, so as to obtain the corresponding three-dimensional porosity model and the three-dimensional permeability model of each of the formation units according to the corresponding three-dimensional sedimentary microfacies model of each of the formation units. The three-dimensional sedimentary microfacies model, the three-dimensional porosity model and the three-dimensional permeability model corresponding to the units respectively predict the effective reservoir in the underground reservoir corresponding to the outcrop carbonate reservoir.

In the embodiment of the underground reservoir prediction device based on outcrop carbonate reservoir modeling of the present application, the underground reservoir prediction device based on outcrop carbonate reservoir modeling further specifically includes the following: content:

The survey line division module 01 is used to divide the outcrop carbonate rock reservoir into multiple survey lines according to the actual geological conditions of the outcrop carbonate rock reservoir;

A stratigraphic unit division module 02, configured to determine the stratigraphic layering of the outcrop carbonate reservoir, and obtain a plurality of the stratigraphic units according to the stratigraphic layering;

The rock structure profile acquisition module 03 is used to determine the lithofacies classification in the outcrop carbonate reservoir, and according to the rock structure profiles corresponding to each of the survey lines.

In the embodiment of the underground reservoir prediction device based on outcrop carbonate reservoir modeling of the present application, the three-dimensional digital outcrop in the underground reservoir prediction device based on outcrop carbonate reservoir modeling The acquisition module 10 specifically includes the following contents:

The two-dimensional sedimentary microfacies model acquisition unit 11 is configured to acquire the two-dimensional sedimentary microfacies model of the outcrop carbonate reservoir.

Wherein, the two-dimensional sedimentary microfacies model acquisition unit 11 specifically includes: a two-dimensional sedimentary microfacies model construction subunit, which is used to build the outcrop carbonate rock according to the rock structure section corresponding to each of the survey lines A 2D sedimentary microfacies model of a reservoir.

The reservoir evaluation unit 12 is configured to perform reservoir evaluation on each section in the two-dimensional sedimentary microfacies model to obtain a two-dimensional outcrop geological model corresponding to the outcrop carbonate reservoir.

Wherein, the reservoir evaluation unit 12 specifically includes:

(1) A physical property testing subunit, used for acquiring physical property testing results of multiple core samples of the outcrop carbonate reservoir.

(2) A subunit is constructed for the two-dimensional outcrop geological model, which is used to determine the correlation between the outcrop carbonate reservoir and the pre-acquired porosity, permeability and lithofacies according to the physical property test results. Reservoir evaluation is performed on each section in the two-dimensional sedimentary microfacies model, and a two-dimensional outcrop geological model corresponding to the outcrop carbonate reservoir is obtained.

In the embodiment of the underground reservoir prediction device based on outcrop carbonate reservoir modeling of the present application, the three-dimensional digital outcrop in the underground reservoir prediction device based on outcrop carbonate reservoir modeling The acquiring module 10 also specifically includes the following contents:

The three-dimensional digital scanning unit 13 is configured to perform three-dimensional digital scanning on the outcrop carbonate rock reservoir to obtain a three-dimensional point cloud image corresponding to the outcrop carbonate rock reservoir.

Wherein, the three-dimensional digital scanning unit 13 specifically includes:

(1) a spatial orientation data acquisition sub-unit, which is used to collect the spatial orientation data of the outcrop carbonate reservoir by using a lidar mapping instrument;

(2) A spatial orientation data editing subunit, used for editing the spatial orientation data through data processing software to form a three-dimensional point cloud image of the outcrop carbonate reservoir.

The image processing unit 14 is configured to perform stratigraphic tracking and labeling processing on the three-dimensional point cloud image according to the two-dimensional outcrop geological model to obtain a corresponding three-dimensional image.

Wherein, the image processing unit 14 specifically includes:

(1) A panoramic photo acquisition sub-unit, used for acquiring a panoramic photo of the outcrop carbonate reservoir by using an image acquisition device.

(2) Image processing calibration sub-unit, for performing stratigraphic tracking and interpretation processing on the 3D point cloud image according to the panoramic photo and the 2D outcrop geological model, and calibrating on the 3D point cloud image The position of the sampling point is obtained to obtain the three-dimensional image.

In the embodiment of the underground reservoir prediction device based on outcrop carbonate reservoir modeling of the present application, the three-dimensional sedimentary microstructure in the underground reservoir prediction device based on outcrop carbonate reservoir modeling The phase model building module 20 specifically includes the following contents:

The three-dimensional quantitative stochastic modeling unit 21 is used to load the information corresponding to the three-dimensional image into the three-dimensional geological modeling tool, and take the lithofacies information in the measured section of the outcrop carbonate reservoir as a constraint, respectively Each of the formation units is subjected to three-dimensional quantitative stochastic modeling to obtain a three-dimensional sedimentary microfacies model corresponding to each of the formation units.

Embodiments of the present application also provide specific implementations of an electronic device capable of realizing all steps in the method for predicting underground reservoirs based on outcrop carbonate reservoir modeling in the above-mentioned embodiments. Referring to FIG. 19 , the electronic device The equipment specifically includes the following:

a processor (processor) 601, a memory (memory) 602, a communication interface (CommunicationsInterface) 603 and a bus 604;

The processor 601, the memory 602, and the communication interface 603 communicate with each other through the bus 604; the communication interface 603 is used to implement an underground reservoir prediction device based on outcrop carbonate reservoir modeling, Information transfer between client terminals, related databases, servers and other participating institutions;

The processor 601 is configured to call a computer program in the memory 602, and when the processor executes the computer program, the method for predicting an underground reservoir based on outcrop carbonate reservoir modeling in the foregoing embodiment is implemented. All steps of, for example, the processor implements the following steps when executing the computer program:

Step 100: Obtain a two-dimensional outcrop geological model corresponding to the outcrop carbonate reservoir, and perform three-dimensional digital scanning and labeling processing on the outcrop carbonate reservoir to obtain a corresponding three-dimensional image, wherein the outcrop carbon Salt rock reservoirs are pre-divided into stratigraphic units.

Step 200: According to the three-dimensional image and the lithofacies information in the measured section of the outcrop carbonate reservoir, obtain a three-dimensional sedimentary microfacies model corresponding to each of the stratigraphic units.

Step 300: According to the three-dimensional sedimentary microfacies model corresponding to each of the formation units, respectively obtain the corresponding three-dimensional porosity model and the three-dimensional permeability model of each of the formation units, so as to obtain the corresponding three-dimensional sedimentary model of each of the formation units according to the corresponding three-dimensional sedimentary model of the formation unit. The microfacies model, the three-dimensional porosity model and the three-dimensional permeability model predict the effective reservoir in the underground reservoir corresponding to the outcrop carbonate reservoir.

It can be seen from the above description that the electronic equipment provided by the embodiments of the present application can accurately and quickly establish a three-dimensional geological model for outcrop carbonate reservoirs, and can effectively improve the effectiveness of underground reservoirs under the reservoir scale standard. Prediction accuracy and reliability, which in turn can ensure the accuracy of oil exploration based on the prediction results and reduce the cost of oil exploration.

Embodiments of the present application also provide a computer-readable storage medium capable of implementing all steps in the method for predicting underground reservoirs based on outcrop carbonate reservoir modeling in the above-mentioned embodiments, on the computer-readable storage medium. A computer program is stored, which, when executed by a processor, implements all steps of the method for predicting an underground reservoir based on outcrop carbonate reservoir modeling in the above embodiment, for example, the processor executes the computer program When implementing the following steps:

Step 100: Obtain a two-dimensional outcrop geological model corresponding to the outcrop carbonate reservoir, and perform three-dimensional digital scanning and labeling processing on the outcrop carbonate reservoir to obtain a corresponding three-dimensional image, wherein the outcrop carbon Salt rock reservoirs are pre-divided into stratigraphic units.

Step 200: According to the three-dimensional image and the lithofacies information in the measured section of the outcrop carbonate reservoir, obtain a three-dimensional sedimentary microfacies model corresponding to each of the stratigraphic units.

Step 300: According to the three-dimensional sedimentary microfacies model corresponding to each of the formation units, respectively obtain the corresponding three-dimensional porosity model and the three-dimensional permeability model of each of the formation units, so as to obtain the corresponding three-dimensional sedimentary model of each of the formation units according to the corresponding three-dimensional sedimentary model of the formation unit. The microfacies model, the three-dimensional porosity model and the three-dimensional permeability model predict the effective reservoir in the underground reservoir corresponding to the outcrop carbonate reservoir.

It can be seen from the above description that the computer-readable storage medium provided by the embodiments of the present application can accurately and rapidly establish a three-dimensional geological model for outcrop carbonate reservoirs, and can effectively improve the underground reservoirs under the reservoir scale standard. Effective prediction accuracy and reliability, and then can ensure the accuracy of oil exploration according to the prediction results, and reduce the cost of oil exploration.

Each embodiment in this specification is described in a progressive manner, and the same and similar parts between the various embodiments may be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the hardware+program embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and for related parts, please refer to the partial description of the method embodiment.

The foregoing describes specific embodiments of the present specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims can be performed in an order different from that in the embodiments and still achieve desirable results. Additionally, the processes depicted in the figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

Although the present application provides method operation steps as described in the embodiments or flow charts, more or less operation steps may be included based on routine or non-creative work. The sequence of steps enumerated in the embodiments is only one of the execution sequences of many steps, and does not represent the only execution sequence. When an actual device or client product is executed, the methods shown in the embodiments or the accompanying drawings may be executed sequentially or in parallel (for example, a parallel processor or a multi-threaded processing environment).

The systems, devices, modules or units described in the above embodiments may be specifically implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, the computer can be, for example, a personal computer, a laptop computer, an in-vehicle human-computer interaction device, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet A computer, wearable device, or a combination of any of these devices.

These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory result in an article of manufacture comprising instruction means, the instructions The apparatus implements the functions specified in the flow or flow of the flowcharts and/or the block or blocks of the block diagrams.

These computer program instructions can also be loaded on a computer or other programmable data processing device to cause a series of operational steps to be performed on the computer or other programmable device to produce a computer-implemented process such that The instructions provide steps for implementing the functions specified in the flow or blocks of the flowcharts and/or the block or blocks of the block diagrams.

In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.

Memory may include non-persistent memory in computer readable media, random access memory (RAM) and/or non-volatile memory in the form of, for example, read only memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.

Computer-readable media includes both persistent and non-permanent, removable and non-removable media, and storage of information may be implemented by any method or technology. Information may be computer readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read only memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), Flash Memory or other memory technology, Compact Disc Read Only Memory (CD-ROM), Digital Versatile Disc (DVD) or other optical storage, Magnetic tape cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include transitory computer-readable media, such as modulated data signals and carrier waves.

As will be appreciated by one skilled in the art, the embodiments of the present specification may be provided as a method, a system or a computer program product. Accordingly, embodiments of this specification may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects.

Embodiments of this specification may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. Embodiments of the description may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including storage devices.

Each embodiment in this specification is described in a progressive manner, and the same and similar parts between the various embodiments may be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, as for the system embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and for related parts, please refer to the partial descriptions of the method embodiments. In the description of this specification, description with reference to the terms "one embodiment," "some embodiments," "example," "specific example," or "some examples", etc., mean specific features described in connection with the embodiment or example , structures, materials, or features are included in at least one example or example of embodiments of this specification. In this specification, schematic representations of the above terms are not necessarily directed to the same embodiment or example. Furthermore, the particular features, structures, materials or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, those skilled in the art may combine and combine the different embodiments or examples described in this specification, as well as the features of the different embodiments or examples, without conflicting each other.

The above descriptions are only the embodiments of the present specification, and are not intended to limit the embodiments of the present specification. For those skilled in the art, various modifications and variations can be made to the embodiments of the present specification. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the embodiments of the present specification shall be included within the scope of the claims of the embodiments of the present specification.

Claims (20)

1. an underground reservoir prediction method based on outcrop carbonate reservoir modeling, is characterized in that, comprises: Obtain a two-dimensional outcrop geological model corresponding to the outcrop carbonate rock reservoir, and perform three-dimensional digital scanning and labeling processing on the outcrop carbonate rock reservoir to obtain a corresponding three-dimensional image, wherein the outcrop carbonate rock The reservoir is pre-divided into a plurality of stratigraphic units; According to the 3D image and the lithofacies information in the measured section of the outcrop carbonate reservoir, obtain a 3D sedimentary microfacies model corresponding to each of the stratigraphic units; According to the three-dimensional sedimentary microfacies model corresponding to each of the formation units, the three-dimensional porosity model and the three-dimensional permeability model corresponding to each of the formation units are obtained respectively, so as to obtain the corresponding three-dimensional sedimentary microfacies model of each of the formation units according to the corresponding three-dimensional sedimentary microfacies model of each of the formation units. , a three-dimensional porosity model and a three-dimensional permeability model to predict the effective reservoir in the underground reservoir corresponding to the outcrop carbonate reservoir. 2 . The method for predicting underground reservoirs according to claim 1 , wherein, before the acquiring the two-dimensional outcrop geological model corresponding to the outcrop carbonate reservoir, the method further comprises: 3 . According to the actual geological conditions of the outcrop carbonate reservoir, the outcrop carbonate reservoir is divided into multiple survey lines; determining the stratigraphic layers of the outcrop carbonate reservoir, and dividing a plurality of the stratigraphic units according to the stratigraphic layers; And, the lithofacies classification in the outcrop carbonate reservoir is determined, and the rock structure section corresponding to each of the survey lines is determined. 3. The method for predicting underground reservoirs according to claim 2, wherein the acquiring a two-dimensional outcrop geological model corresponding to an outcrop carbonate reservoir comprises: obtaining a two-dimensional sedimentary microfacies model of the outcrop carbonate reservoir; Reservoir evaluation is performed on each section in the two-dimensional sedimentary microfacies model to obtain a two-dimensional outcrop geological model corresponding to the outcrop carbonate reservoir. 4. The method for predicting underground reservoirs according to claim 3, wherein the acquiring a two-dimensional sedimentary microfacies model of the outcrop carbonate reservoir comprises: According to the rock structure section corresponding to each of the survey lines, a two-dimensional sedimentary microfacies model of the outcrop carbonate reservoir is established. 5 . The method for predicting underground reservoirs according to claim 3 , wherein the reservoir evaluation is performed on each section in the two-dimensional sedimentary microfacies model to obtain the outcrop carbonate reservoir. 6 . The corresponding two-dimensional outcrop geological model includes: obtaining physical property test results of multiple core samples of the outcrop carbonate reservoir; According to the physical property test results and the pre-obtained correspondence between porosity, permeability and lithofacies, the reservoirs are carried out for each section in the two-dimensional sedimentary microfacies model of the outcrop carbonate reservoir. The evaluation is performed to obtain a two-dimensional outcrop geological model corresponding to the outcrop carbonate reservoir. 6. The method for predicting underground reservoirs according to claim 1, characterized in that, performing three-dimensional digital scanning and labeling processing on the outcrop carbonate reservoir to obtain a corresponding three-dimensional image, comprising: Performing three-dimensional digital scanning on the outcrop carbonate rock reservoir to obtain a three-dimensional point cloud image corresponding to the outcrop carbonate rock reservoir; According to the two-dimensional outcrop geological model, stratigraphic tracking and labeling processing is performed on the three-dimensional point cloud image to obtain a corresponding three-dimensional image. 7 . The method for predicting underground reservoirs according to claim 6 , wherein the three-dimensional digital scanning is performed on the outcrop carbonate reservoir to obtain a three-dimensional point cloud corresponding to the outcrop carbonate reservoir. 8 . images, including: collecting spatial orientation data of the outcrop carbonate reservoir by using a lidar mapping instrument; The spatial orientation data is edited by data processing software to form a three-dimensional point cloud image of the outcrop carbonate reservoir. 8. The method for predicting underground reservoirs according to claim 6, characterized in that, performing stratigraphic tracking and labeling processing on the three-dimensional point cloud image according to the two-dimensional outcrop geological model to obtain a corresponding three-dimensional image, comprising: Using image acquisition equipment to collect panoramic photos of the outcrop carbonate reservoir; According to the panoramic photo and the two-dimensional outcrop geological model, stratigraphic tracking and interpretation processing is performed on the three-dimensional point cloud image, and the positions of sampling points are calibrated on the three-dimensional point cloud image to obtain the three-dimensional image. 9 . The method for predicting an underground reservoir according to claim 1 , wherein the strata are obtained according to the three-dimensional image and the lithofacies information in the measured section of the outcrop carbonate reservoir. 10 . The three-dimensional sedimentary microfacies models corresponding to the units, including: The information corresponding to the three-dimensional image is loaded into the three-dimensional geological modeling tool, and the lithofacies information in the measured section of the outcrop carbonate reservoir is used as a constraint, and three-dimensional quantitative random modeling is carried out for each of the stratigraphic units respectively. The three-dimensional sedimentary microfacies model corresponding to each of the stratigraphic units is obtained. 10. An underground reservoir prediction device based on outcrop carbonate reservoir modeling, characterized in that it comprises: A three-dimensional digital outcrop acquisition module is used to acquire a two-dimensional outcrop geological model corresponding to an outcrop carbonate rock reservoir, and perform three-dimensional digital scanning and labeling processing on the outcrop carbonate rock reservoir to obtain a corresponding three-dimensional image, wherein , the outcrop carbonate reservoir is pre-divided into a plurality of stratigraphic units; a three-dimensional sedimentary microfacies model building module, configured to obtain a three-dimensional sedimentary microfacies model corresponding to each of the stratigraphic units according to the three-dimensional image and the lithofacies information in the measured section of the outcrop carbonate reservoir; The underground reservoir prediction module is used to obtain the three-dimensional porosity model and the three-dimensional permeability model corresponding to each of the formation units according to the three-dimensional sedimentary microfacies model corresponding to each of the formation units respectively, so as to obtain the corresponding three-dimensional porosity model and the three-dimensional permeability model of each of the formation units respectively, so as to obtain the corresponding three-dimensional porosity model and the three-dimensional permeability model of each of the formation units according to the corresponding three-dimensional sedimentary microfacies model of each of the formation units. The corresponding three-dimensional sedimentary microfacies model, three-dimensional porosity model and three-dimensional permeability model respectively predict the effective reservoir in the underground reservoir corresponding to the outcrop carbonate reservoir. 11. The underground reservoir prediction device according to claim 10, further comprising: A survey line division module, used for dividing a plurality of survey lines on the outcrop carbonate rock reservoir according to the actual geological conditions of the outcrop carbonate rock reservoir; a stratigraphic unit division module, configured to determine the stratigraphic layers of the outcrop carbonate reservoir, and obtain a plurality of the stratigraphic units according to the stratigraphic layer division; The rock structure section acquisition module is used for determining the lithofacies classification in the outcrop carbonate reservoir, and according to the rock structure section corresponding to each of the survey lines. 12. The underground reservoir prediction device according to claim 11, wherein the three-dimensional digital outcrop acquisition module comprises: a two-dimensional sedimentary microfacies model acquisition unit, used for acquiring the two-dimensional sedimentary microfacies model of the outcrop carbonate reservoir; The reservoir evaluation unit is used to perform reservoir evaluation on each section in the two-dimensional sedimentary microfacies model, and obtain a two-dimensional outcrop geological model corresponding to the outcrop carbonate reservoir. 13. The underground reservoir prediction device according to claim 12, wherein the two-dimensional sedimentary microfacies model acquisition unit comprises: The two-dimensional sedimentary microfacies model construction subunit is used for establishing a two-dimensional sedimentary microfacies model of the outcrop carbonate reservoir according to the rock structure section corresponding to each of the survey lines. 14. The underground reservoir prediction device according to claim 12, wherein the reservoir evaluation unit comprises: a physical property testing subunit, used for acquiring physical property testing results of multiple core samples of the outcrop carbonate reservoir; The two-dimensional outcrop geological model constructs a sub-unit, which is used for the two-dimensional deposition of the outcrop carbonate reservoir according to the physical property test results and the pre-acquired correspondence between porosity, permeability and lithofacies Reservoir evaluation is performed on each section in the microfacies model to obtain a two-dimensional outcrop geological model corresponding to the outcrop carbonate reservoir. 15. The underground reservoir prediction device according to claim 10, wherein the three-dimensional digital outcrop acquisition module comprises: a three-dimensional digital scanning unit, used for performing three-dimensional digital scanning on the outcrop carbonate rock reservoir to obtain a three-dimensional point cloud image corresponding to the outcrop carbonate rock reservoir; The image processing unit is configured to perform stratigraphic tracking and labeling processing on the three-dimensional point cloud image according to the two-dimensional outcrop geological model to obtain a corresponding three-dimensional image. 16. The underground reservoir prediction device according to claim 15, wherein the three-dimensional digital scanning unit comprises: a spatial orientation data acquisition subunit, used for collecting the spatial orientation data of the outcrop carbonate reservoir by using a lidar mapping instrument; The spatial orientation data editing subunit is used to edit the spatial orientation data through data processing software to form a three-dimensional point cloud image of the outcrop carbonate reservoir. 17. The underground reservoir prediction device according to claim 15, wherein the image processing unit comprises: A panorama photo acquisition subunit, used for acquiring a panorama photo of the outcrop carbonate reservoir by using an image acquisition device; The image processing calibration subunit is used to perform stratigraphic tracking and interpretation processing on the three-dimensional point cloud image according to the panoramic photo and the two-dimensional outcrop geological model, and to calibrate the sampling point position on the three-dimensional point cloud image to obtain the three-dimensional image. 18. The underground reservoir prediction device according to claim 10, wherein the three-dimensional sedimentary microfacies model building module comprises: The three-dimensional quantitative stochastic modeling unit is used to load the information corresponding to the three-dimensional image into the three-dimensional geological modeling tool, and is constrained by the lithofacies information in the measured section of the outcrop carbonate reservoir, respectively, for each Three-dimensional quantitative stochastic modeling is performed on the stratigraphic units to obtain three-dimensional sedimentary microfacies models corresponding to each of the stratigraphic units. 19. An electronic device comprising a memory, a processor and a computer program stored on the memory and running on the processor, wherein the processor implements any one of claims 1 to 9 when executing the program The steps of the underground reservoir prediction method based on outcrop carbonate reservoir modeling. 20. A computer-readable storage medium on which a computer program is stored, characterized in that, when the computer program is executed by a processor, the outcrop carbonate reservoir construction according to any one of claims 1 to 9 is realized. Steps of a subsurface reservoir prediction method of the model.

Images