A method for driving automatic updating of three-dimensional geological models

Abstract

The present invention provides a method for driving automatic updating of a three-dimensional geological model, comprising the following steps: step 1, splitting a geological model update operation into multiple minimum execution units; step 2, compiling a command language control workflow to form an update control workflow; step 3, creating an expert modeling experience parameter library including multiple reservoir types for parameter calling during the operation of the update control workflow; step 4, programming the update control workflow using computer language programming; step 5, importing single well layered data into the update control workflow based on a data interface; the present invention is applied to the oil and gas field development stage, and based on realizing the automatic updating of the three-dimensional geological model, solves the timeliness problem of the existing geological model update, improves the speed and quality of the geological model update, and has great positive significance for promoting the acceleration and improvement of oil field development work.

Description

Technical Field

[0001] The invention belongs to the field of oil field development, and in particular relates to a method for driving automatic updating of a three-dimensional geological model. Background Art

[0002] Currently, geological modeling updates are primarily manual, following standard software workflows to complete data input corrections, parameter adjustments, algorithm optimization, and updates to structural, facies, and attribute models. This is a significant workload and time-consuming, with typical model updates taking anywhere from a few days to over a month. Timeliness is crucial for some oilfield development efforts, such as while-drilling (WDR) operations, which require timely guidance and recommendations for geological model layer updates to the field. However, existing geological modeling update speeds cannot meet these timelines, hindering the provision of real-time geological model update services for WDR. Some geological modeling platforms can implement geological model updates through the development of relevant geological model update workflows, which are then manually assisted. However, these approaches are relatively simple and streamlined, relying on existing parameter settings. However, each step in the process, including parameter adjustment and verification, algorithm optimization, variogram adjustment, and data analysis and comparison, still requires manual effort, lacking sufficient automation and intelligent capabilities. Invention content

[0003] In view of this, the present invention aims to propose a method for driving the automatic update of three-dimensional geological models, which can be applied to the oil and gas field development stage to realize the automatic update of three-dimensional geological models, solve the timeliness problem of existing geological model updates, and improve the speed of geological model updates.

[0004] To achieve the above object, the technical solution created by the present invention is implemented as follows:

[0005] A method for driving automatic updating of a three-dimensional geological model comprises the following steps:

[0006] Step 1: Split the geological model update operation into multiple minimum execution units, and compile a logical expression workflow according to the execution unit sequence and loop logic judgment rules. The logical expression workflow includes a first-level control workflow, which sequentially includes layer data difference analysis, layer structure correction, structural model update, lithofacies model update, and attribute model update;

[0007] Step 2: compiling a command language control workflow based on the logic expression workflow and the action instructions associated with each execution unit thereof, and integrating the command language control workflows to form an update control workflow;

[0008] Step 3: creating an expert modeling experience parameter library including various reservoir types based on the geological knowledge base and geological modeling experience parameters, for parameter calling during the operation of the update control workflow;

[0009] Step 4, programming the update control workflow using computer language programming;

[0010] Step 5: Import the single-well layer data into the update control workflow based on the data interface to drive the automatic update of the geological model.

[0011] Furthermore, in step 1, the logic expression workflow also includes a secondary control workflow, and the secondary control workflow is created under the primary control workflow.

[0012] Furthermore, the secondary control workflow created under the said layer data difference analysis includes extracting the intersection value of the well trajectory and the model layer, calculating the difference between the single well layer and the model layer, and performing logical judgment according to the size of the difference.

[0013] Furthermore, the secondary control workflow created under the layer structure correction includes well layer data scattering and layer data correction layers in sequence.

[0014] Furthermore, the secondary control workflow created under the structural model update sequentially includes establishing a layer group level, establishing a small layer level, and setting the model orthocenter resolution by subdividing the layers within the small layer.

[0015] Furthermore, the secondary control workflow created under the updating of the lithofacies model sequentially includes intelligent division of lithofacies types by neural network, lithofacies data coarsening, lithofacies data analysis and lithofacies data analysis.

[0016] Furthermore, the secondary control workflow established under the attribute model update includes attribute data coarsening, attribute data analysis and attribute modeling in sequence.

[0017] Furthermore, the logic expression workflow is not limited to two levels. According to the needs of model parameter adjustment, a three-level workflow can be created under the second-level workflow; and so on, until a complete logic expression workflow for executing three-dimensional geological model updates is established.

[0018] Furthermore, the expert modeling empirical parameter library includes a variety of reservoir types, and as the knowledge base increases, the empirical parameter library can be continuously expanded.

[0019] Furthermore, the single-well stratified data is imported into the update control workflow through the bridging of the data interface.

[0020] Compared with the prior art, the method for automatically updating a three-dimensional geological model created by the present invention has the following advantages:

[0021] The present invention creates an update method by establishing a logical representation workflow on step-by-step execution units, compiling a command language control workflow based on the logical representation workflow, and integrating the command language control workflow to establish an update control workflow. Parameters are then called through an expert modeling experience parameter library. Single-well layer data is imported into the geological model update control workflow via a data interface, driving automatic updates of the geological model. During the oil and gas field development phase, this method addresses the timeliness issues associated with existing geological model updates by enabling automatic updates of three-dimensional geological models. This significantly improves the speed and quality of geological model updates, allowing the results to be rapidly used to guide oilfield development-related work, significantly contributing to accelerating and improving the quality of oilfield development. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] The accompanying drawings, which constitute part of the present invention, are intended to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are intended to explain the present invention and do not constitute an undue limitation of the present invention. In the accompanying drawings:

[0023] Figure 1 A schematic diagram of a logical expression workflow according to an embodiment of the present invention;

[0024] Figure 2 A schematic diagram of a layer structure modification workflow according to an embodiment of the present invention;

[0025] Figure 3 A schematic diagram of a small-level workflow for creating an embodiment of the present invention;

[0026] Figure 4 The invention creates a neural network intelligent lithologic type workflow as described in an embodiment.

[0027] Figure 5 A schematic diagram of the petrographic data analysis workflow according to an embodiment of the present invention;

[0028] Figure 6 A schematic diagram of the attribute data analysis workflow according to an embodiment of the present invention;

[0029] Figure 7 A schematic diagram of the attribute modeling workflow described in an embodiment of the present invention;

[0030] Figure 8 The present invention creates a flowchart of the automatic update method described in an embodiment.

[0031] Description of reference numerals:

[0032] 1- Layer data difference analysis; 2- Layer structure correction; 3- Structural model update; 4- Lithofacies model update; 5- Attribute model update; 11- Execution unit; 12- Logical expression workflow; 13- Command language control workflow; 14- Update control workflow; 15- Expert modeling experience parameter library; 16- Single well layer data. DETAILED DESCRIPTION

[0033] It should be noted that, in the absence of conflict, the embodiments of the present invention and the features in the embodiments can be combined with each other.

[0034] The present invention will be described in detail below with reference to the accompanying drawings and in combination with embodiments.

[0035] like Figure 1 、 8 As shown, a method for driving automatic updating of a three-dimensional geological model includes the following steps:

[0036] Step 1: Split the geological model update operation into multiple minimum execution units 11. According to the sequence of the execution units 11 and the loop logic judgment rules, compile a logical expression workflow 12. The logical expression workflow 12 includes a first-level control workflow, which sequentially includes layer data difference analysis 1, layer structure correction 2, structural model update 3, lithofacies model update 4, and attribute model update 5.

[0037] In step 1, it is necessary to further explain that: based on the conventional operation process and steps of 3D geological modeling, the geological model update operation steps are finely divided and split into each step level, namely the execution unit; based on the split step results, following their sequence and loop logic judgment rules, a logical expression workflow for the 3D geological model update is compiled.

[0038] Step 2: compile a command language control workflow 13 based on the logic expression workflow 12 and the action instructions associated with each execution unit 11, and integrate the command language control workflow 13 to form an update control workflow 14;

[0039] What needs to be further explained in step 2 is that: the update control workflow 14 is established on the basis of the logical expression workflow 12, and the compilation of the command language control workflow 13 is completely dependent on each step action instruction involved in the logical expression workflow 12, that is, the logical expression workflow 12 is operationalized and instructed, and the update control workflow 14 is executed in sequence.

[0040] Step 3: creating an expert modeling experience parameter library 15 including various reservoir types based on the geological knowledge base and geological modeling experience parameters, for parameter calling during the operation of the update control workflow 14;

[0041] What needs to be further explained in step 3 is that it is necessary to use the geological knowledge base data and relevant geological modeling experience parameters to establish the relevant parameters needed for the geological model update process. These parameters play an important reference role in guiding the update and optimization of the geological model. Each type of oil reservoir corresponds to specific relevant modeling experience parameters. The expert modeling experience parameter library 15 contains a variety of oil reservoir types, and as the knowledge base increases, the experience parameter library can be continuously expanded, thereby providing model update services for more oil reservoir types.

[0042] Step 4, programming the update control workflow 14 using computer language programming;

[0043] In step 4, it is necessary to further explain that the operation of the geological model update control workflow is realized by programming in a computer language to form a system program. The update of the entire geological model is completed through the operation of the program. In the system program, intelligent analysis, judgment or optimization kinetic energy can be added to the relevant instruction actions. This can be achieved by adding a secondary control workflow, thereby ensuring that the system program has related functions such as logical judgment, intelligent matching targets, and automatic control, greatly expanding the automation capability.

[0044] Step 5: import the single well layer data 16 into the update control workflow 14 based on the data interface to drive the geological model to be automatically updated.

[0045] What needs to be further explained in step 5 is that the automatic import of well layer data is achieved through the bridging effect of the data interface, thereby driving the operation of the geological model update control workflow and realizing the automation of the entire geological model update process.

[0046] The present invention provides a method for driving automatic geological model updates. Based on a finely segmented, step-by-step geological modeling process, a logical representation workflow for three-dimensional geological model updates is created according to a logical architecture and sequence, and in accordance with cyclic logic judgment rules. A command language control workflow is compiled based on the created geological model update logical representation workflow and the action instructions associated with each step, creating a geological model update control workflow. Based on a geological knowledge base and geological modeling experience parameters, an expert modeling experience parameter library covering multiple reservoir types is created for parameter call during the execution of the geological model update control workflow. The geological model update control workflow is programmable using language programming and includes functions such as logical judgment, intelligent target matching, and automatic control. Single-well layer data is imported into the geological model update control workflow via a data interface, driving automatic geological model updates. During the oil and gas field development phase, the present invention addresses the timeliness issue of existing geological model updates by enabling automatic updates of three-dimensional geological models, significantly improving the speed and quality of geological model updates. The results can be quickly used to guide oilfield development-related work, significantly contributing to the acceleration and improvement of oilfield development.

[0047] like Figure 1 As shown, in step 2, the logical representation workflow also includes a secondary control workflow, which is created under the primary control workflow. It should be further noted that the logical representation workflow is not limited to a two-level workflow. Depending on the needs of model parameter adjustment, a third-level control workflow can be created under the secondary control workflow, and so on, until a complete logical representation workflow for executing 3D geological model updates is established.

[0048] like Figure 1 As shown, the secondary control workflow created under the layer data difference analysis 1 includes extracting the intersection value of the well trajectory and the model layer 101, calculating the difference between the single well layer and the model layer 102, and performing logical judgment according to the difference size 103.

[0049] like Figure 1 As shown, the secondary control workflow created under the layer structure modification 2 sequentially includes well layer data scattering 201 and layer data modification layer 201 .

[0050] like Figure 1 As shown, the secondary control workflow created under the structural model update 3 sequentially includes establishing a layer group level 301, establishing a small layer level 302, and setting the model orthocenter resolution 303 of the subdivision layer within the small layer.

[0051] like Figure 1As shown, the secondary control workflow created under the facies model update 4 includes, in sequence, a neural network intelligent division of facies types 401 , facies data coarsening 402 , facies data analysis 403 and facies data analysis 404 .

[0052] like Figure 1 As shown, the secondary control workflow established under the attribute model update 5 includes attribute data coarsening 501, attribute data analysis 502 and attribute modeling 503 in sequence.

[0053] As one of the preferred embodiments of the present invention, the logical representation workflow is not limited to a two-level workflow. Based on the needs of model parameter adjustment, a three-level workflow can be created within the second-level workflow. This process can be repeated until a complete logical representation workflow for executing 3D geological model updates is established. The expert modeling empirical parameter library encompasses multiple reservoir types and can be continuously expanded as the knowledge base grows. Single-well layered data is imported into the update control workflow via a data interface bridge.

[0054] Taking the drilling-while-drilling scenario of an oilfield development well as an example, the specific implementation methods of the present invention are further described with reference to the accompanying drawings: First, based on the data of reservoir interface, physical property parameters, fluid parameters and other data transmitted in real time from the drilling-while-drilling work site of the oilfield development well, the data is received through the data interface and imported into the initial three-dimensional geological model in real time, and the geological model update control workflow is started;

[0055] like Figure 1 As shown, the first-level control workflow's layer data difference analysis 1 starts running, and the control modeling program sequentially completes the following tasks: First, based on the running of the second-level control workflow, the intersection value data of the well trajectory and the model layer is extracted 101; Second, the difference between the single well layer data and the model layer data extracted in the first step is calculated 102; the single well layer data is the reservoir interface data of the drilling evaluation; Third, a logical judgment is performed based on the size of the difference 103. If the difference is zero, it means that the layering of the well while drilling is consistent with the layering in the original model, and the geological model does not need to be adjusted, and the control flow is terminated. If the difference is not equal to zero, the next step of the layer structure correction 2 of the first-level control workflow is executed;

[0056] like Figure 1 As shown, after the layer structure modification 2 of the first-level control workflow is executed, the following tasks are completed in sequence: the first step is to execute the well layer data scattering 201 of the second-level control workflow, and the layers are selected cyclically according to the layer sequence, thereby completing the discretization operation of the layer data of multiple layers while drilling; the second step is to execute the layer data modification layer 202; preferably, the steps shown in the attached figure are executed. Figure 2The illustrated workflow for layer structure correction sequentially executes the tool module startup, layer creation, layer selection, associated input data options, intelligent boundary setting, and well point layer data selection for control. Layer selection cycles are then performed to locally correct the structural diagrams of each layer within the model based on well layer changes. Upon completion, the next level of control workflow, structure model update 3, is executed.

[0057] like Figure 1 As shown, the structural model update of the first-level control workflow is started 3, and the following tasks are completed in sequence: the first step is to control the modeling program to run based on the corrected structural level data and establish the creation of the layer group level 301 model; the second step is to establish the creation of the small level 302 model and execute the following steps: Figure 3 As shown, a small-level workflow is established, which cyclically executes the selection of interval layers, intelligent calculation and setting of the number of inserted layers, intelligent optimization of the layering method, setting of empirical parameter values, intelligent selection of insertion along the top or bottom of the layer, layer correction method, and thickness method. In the third step, the relevant control workflow is executed to complete the further fine-grained layering 303 within the small layer, thereby setting the vertical resolution of the model. The number of subdivided layers and the subdivided layer method (equal division or proportional) can all refer to the modeling empirical parameter library. After completion, the lithofacies model update 4 of the next-level control workflow is automatically executed.

[0058] The lithofacies model update 4 of the first-level control workflow is executed, and the following tasks are completed in sequence: Step 1, perform the neural network intelligent division of lithofacies types 401, and execute as shown in the attached Figure 4 The neural network intelligent division of lithofacies type workflow shown in FIG2 is based on the selected characteristic logging curve (modeling experience parameter library can be referenced) and the neural network model is used to complete the lithofacies type division of the well while drilling. The lithofacies division of multiple new wells can be completed according to the workflow. The second step is to execute the relevant control workflow, select the coarsening algorithm type 402, and complete the coarsening of the lithofacies curve while drilling. The third step is to execute the algorithm shown in FIG2. Figure 5 The illustrated lithofacies data analysis workflow, based on the selection of lithology and horizon, completes lithofacies data analysis 403 for all horizons by running the relevant three-level control workflows. The data analysis includes proportion analysis, lithofacies thickness distribution analysis, physical property and lithology correlation analysis, and variogram analysis based on modeling empirical parameters. Upon completion, the attribute model update 5 of the next first-level control workflow is automatically executed.

[0059] After the attribute model update 5 of the first-level control workflow is executed, the following tasks are completed in sequence: Step 1, execute the relevant control workflow, add the new well physical property (porosity, permeability, etc.) curve, select the relevant coarsening algorithm type, and complete the physical property data coarsening 501; Step 2, execute the following steps: Figure 6 The attribute data analysis workflow shown in the figure, as well as the three-level control workflow required, completes the change analysis and variogram analysis of each layer of physical property data; the third step is to execute the following steps: Figure 7 The attribute modeling workflow shown, along with the associated three-level control workflow, uses facies control and the sequential Gaussian simulation algorithm, optionally with the addition of secondary attribute constraints, to update the relevant attribute models. This completes the automated geological model update process, ultimately yielding updated structural, lithofacies, and attribute models. These model updates can be used to guide subsequent wellbore decisions while drilling.

[0060] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for driving automatic updating of a three-dimensional geological model, characterized in that: The following steps are involved: Step 1: Split the geological model update operation into multiple minimum execution units, and compile a logical expression workflow according to the execution unit sequence and loop logic judgment rules. The logical expression workflow includes a first-level control workflow, which sequentially includes layer data difference analysis, layer structure correction, structural model update, lithofacies model update, and attribute model update; Step 2: compiling a command language control workflow based on the logic expression workflow and the action instructions associated with each execution unit thereof, and integrating the command language control workflows to form an update control workflow; Step 3: creating an expert modeling experience parameter library including various reservoir types based on the geological knowledge base and geological modeling experience parameters, for parameter calling during the operation of the update control workflow; Step 4, programming the update control workflow using computer language programming; Step 5: Import the single-well layer data into the update control workflow based on the data interface to drive the automatic update of the geological model.

2. The method for automatically updating a three-dimensional geological model according to claim 1, wherein: In the step 1, the logic expression workflow also includes a secondary control workflow, and the secondary control workflow is created under the primary control workflow.

3. The method for automatically updating a three-dimensional geological model according to claim 2, wherein: The secondary control workflow created under the said layer data difference analysis includes extracting the intersection value of the well trajectory and the model layer, calculating the difference between the single well layer and the model layer, and performing logical judgment according to the size of the difference.

4. The method for automatically updating a three-dimensional geological model according to claim 2, wherein: The secondary control workflow created under the said level structure correction includes well layer data scattering and layer data correction levels in sequence.

5. The method for driving automatic updating of a three-dimensional geological model according to claim 2, characterized in that: The secondary control workflow created under the structural model update sequentially includes establishing layer group level, establishing small layer level and setting model orthocenter resolution by subdividing layers within small layers.

6. The method for driving automatic updating of a three-dimensional geological model according to claim 2, characterized in that: The secondary control workflow created under the updating of the lithofacies model includes, in sequence, intelligent division of lithofacies types by neural network, lithofacies data coarsening, lithofacies data analysis and lithofacies data analysis.

7. The method for driving automatic updating of a three-dimensional geological model according to claim 2, characterized in that: The secondary control workflow established under the attribute model update includes attribute data coarsening, attribute data analysis and attribute modeling in sequence.

8. The method for driving automatic updating of a three-dimensional geological model according to claim 3, characterized in that: The logic expression workflow is not limited to two levels. According to the needs of model parameter adjustment, a three-level workflow can be created under the second-level workflow; and so on, until a complete logic expression workflow for executing three-dimensional geological model updates is established.

9. The method for driving automatic updating of a three-dimensional geological model according to claim 1, characterized in that: The expert modeling experience parameter library includes a variety of reservoir types, and as the knowledge base increases, the experience parameter library can be continuously expanded.

10. The method for driving automatic updating of a three-dimensional geological model according to claim 1, characterized in that: Single-well stratified data are imported into the update control workflow through the data interface bridge.

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