Method for evaluating blocky carbonate rock gas reservoir production condition based on flow unit

Abstract

The invention relates to a method for evaluating the production condition of a blocky carbonate gas reservoir based on a flow unit, and belongs to the field of oil and gas field exploration and development. The method comprises the following steps: carrying out a seepage characteristic experiment by using a target layer core sample in a research area, determining the difference of seepage capacity indexes FI of different core samples, and determining flow unit characterization parameters through rendezvous analysis of the FI and reservoir characterization parameters; carrying out clustering analysis on the core sample, determining the type of a flow unit and a corresponding discrimination function, and carrying out classified flow unit quantitative identification and output condition analysis based on a conventional logging curve; and establishing a geologic model, calibrating an analysis conclusion in combination with a single well output condition, and evaluating a reserve utilization condition by utilizing a logic judgment and Gaussian truncation method. According to the method, the three-dimensional flow unit model is established, and the difference of output conditions of the classified flow units is calibrated by combining a single well, so that gas reservoir distribution characteristics and reserve scales under different use conditions can be evaluated.

Description

Technical Field

[0001] The invention relates to a method for evaluating the producing status of a massive carbonate gas reservoir based on a flow unit, and belongs to the field of oil and gas field exploration and development. Background Art

[0002] Since 2000, my country has discovered carbonate gas fields represented by Puguang, Yuanba, and Luojiazhai in the Sichuan Basin and other regions, with proven geological reserves exceeding 2 trillion cubic meters. The safe development of such gas fields is of great significance to ensuring the supply of natural gas.

[0003] The evaluation of reserve production status is a necessary basis for adjusting the potential of gas fields and continuing to improve the degree of reserve production. The conventional method for evaluating the production status of reserves is to determine the well control range based on the production well pattern and well control radius, and further determine the reserve production status and the distribution of unused reserves in combination with monitoring data such as stratified pressure measurement. For massive carbonate gas reservoirs, due to their strong heterogeneity, poor stratification, and multiple solutions of single well output monitoring data, it is impossible to monitor stratified pressure measurement data. The evaluation of the production status of similar massive carbonate gas reservoirs has always been a difficult problem.

[0004] The Chinese invention patent document with publication number CN104196523A discloses a method for evaluating the reserve production status of carbonate gas reservoirs. This method obtains the gas reservoir reserve production status evaluation profile and the gas reservoir reserve production status evaluation plane of different layers by constraining and controlling the continuous geological model of the three-dimensional seepage characteristics of the reservoir, and uses comprehensive logging evaluation parameters and three-dimensional visual intuitive maps to quantitatively evaluate the reserve production status of carbonate gas reservoirs. It is mainly based on the production profile test results of a single well, and refers to the inter-well seismic prediction of the reservoir porosity, permeability and other development conditions, and qualitatively determines the inter-well production layer development characteristics and reserve production status. No attempt has been made to use a technical method to quantitatively evaluate the production status of a single well and between wells by combining dynamic and static data and seepage capacity differences with a regional target. Summary of the invention

[0005] The purpose of the present invention is to provide a method for evaluating the production status of massive carbonate gas reservoirs based on flow units, so as to solve the problem that the existing method for qualitatively evaluating the production status of massive carbonate gas reservoirs based on single well production profile and inter-well reservoir prediction physical properties has limitations.

[0006] To achieve the above object, the solution of the present invention includes:

[0007] The steps of a method for evaluating the producing status of a massive carbonate gas reservoir based on a flow unit of the present invention are as follows:

[0008] 1) Using core samples of the target layer in the study area, the seepage characteristic experiment was carried out to clarify the difference in the seepage capacity index FI of different core samples, and the flow unit characterization parameters were determined through the intersection analysis of FI and reservoir characterization parameters;

[0009] 2) Cluster analysis is performed on core samples. Based on the analysis results, the flow unit categories and their corresponding discriminant functions are clarified, and quantitative identification of classified flow units and output status analysis based on conventional logging curves are performed;

[0010] 3) Establish a flow unit phase geological model, combine the calibration analysis conclusions of the single well production status, extract the plane thickness of the poorly utilized flow unit, and evaluate the reserve utilization status of different well areas in the plane.

[0011] Based on core seepage experiments, the present invention introduces a seepage capacity index to characterize the difference in seepage capacity of different rock samples, and proposes flow unit identification and characterization parameters through intersection analysis of various reservoir characterization parameters such as porosity and permeability; guided by the seepage capacity index, with the help of mathematical operations such as cluster analysis, the differences in lithology characterization parameters of different flow units are clarified, and a classification discriminant function is established, which is extended to conventional logging curves to achieve flow unit identification and division based on conventional logging curves, and the differences in the production conditions of different flow units are clarified in combination with the production profile of a single well; using geological modeling means, a geological model of various characterization parameters between wells is established, and a classified flow unit model is obtained by model operation to achieve three-dimensional and quantitative evaluation of the production condition of massive gas reservoirs.

[0012] Furthermore, before carrying out step 1), core samples are subjected to analytical testing and geological analysis to preliminarily clarify the reservoir porosity-permeability relationship, reservoir pore type and its relationship with permeability, porosity and reservoir quality factor RQI.

[0013] The present invention provides data support for subsequent intersection analysis by conducting analytical tests and geological analysis on core samples in advance.

[0014] Furthermore, the reservoir characterization parameters in step 1) include porosity, permeability, and reservoir zone index FZI.

[0015] Furthermore, in step 1), after the intersection analysis, the flow unit characterization parameters are determined according to the magnitude of the correlation.

[0016] The present invention optimizes reservoir characterization parameters and performs intersection analysis with FI, thereby improving the efficiency of the seepage experiment, determining flow unit characterization parameters according to correlation, and making subsequent flow unit division more accurate.

[0017] Furthermore, in step 2), the cluster analysis is: clustering the flow unit characterization parameters corresponding to each core sample to achieve flow unit classification and determine the threshold value of each type of flow unit characterization parameter.

[0018] The present invention determines the threshold intervals of key parameters of various flow units through cluster analysis, and can more comprehensively reflect general rules.

[0019] Furthermore, in step 2), the quantitative identification of the classified flow units and the analysis of the output status are as follows: based on conventional logging curves, the flow unit characterization parameters are obtained, and according to the characterization parameter thresholds of the classified flow units, the vertical classified flow unit distribution of each well is determined, and combined with the single well flow unit evaluation and the output profile conclusions, the differences in the output proportions of the classified flow units are statistically analyzed to clarify the differences in the output characteristics of the classified flow units.

[0020] The present invention can obtain the difference in output characteristics of each classified flow unit through quantitative identification of classified flow units and output status analysis.

[0021] Furthermore, in step 3), a flow unit phase geological model is established by the following method: using geological modeling methods, a geological model of each characterization parameter between wells is established, the single well flow unit identification data is input into the geological model, and at the same time, based on the attribute models such as porosity and permeability, the parameter model required for the flow unit characterization parameters is calculated, and the flow unit phase geological model is established by adding the well point flow unit to the inter-well porosity, permeability, and RQI model constraints.

[0022] The present invention can intuitively display the gas reservoir production status by establishing a flow unit phase geological model.

[0023] Further, the flow unit identification data is input into the geological model as flow unit phase.

[0024] Based on the present invention, a three-dimensional flow unit model can be established, and at the same time, combined with the differences in the output conditions of the flow units classified by single well calibration, the distribution characteristics and reserve scale of gas reservoirs with good and poor producing conditions can be clarified. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 It is a technical solution flow chart in the method embodiment of the present invention;

[0026] Figure 2 is a cross-plot of seepage index and permeability of a carbonate reservoir sample in an embodiment of the method of the present invention;

[0027] Figure 3 is a cross-plot of porosity and permeability of a carbonate reservoir sample in an embodiment of the method of the present invention;

[0028] Figure 4 The flow unit discriminant function in the method embodiment of the present invention calculates the single well flow unit distribution map;

[0029] Figure 5is a comparative histogram of the number of classified flow units identified and the capacity ratio in the method embodiment of the present invention;

[0030] Figure 6 is a schematic diagram of spatial distribution of a flow unit geological model in an embodiment of the method of the present invention;

[0031] Figure 7 It is a plane distribution diagram of the gas layer thickness of the differential flow unit used in the method embodiment of the present invention. DETAILED DESCRIPTION

[0032] In order to make the purpose, technical scheme and advantages of the present invention more clear, the present invention is further described in detail below by taking a certain massive carbonate reservoir in the main marine facies in Puguang area of ​​Sichuan, my country as an example in conjunction with the accompanying drawings.

[0033] Example of a method for evaluating the producing status of massive carbonate gas reservoirs based on flow units:

[0034] The technical solution of the present invention is as follows Figure 1 As shown, the specific steps are as follows:

[0035] 1. Carry out seepage experiments using core samples of the target layer in the study area to clarify the differences in seepage index (flow rate under unit pressure difference) of different core samples, and determine the flow unit characterization parameters through the intersection analysis of the seepage index with reservoir characterization parameters such as porosity, permeability, and FZI.

[0036] 1.1. Carry out core sample analysis and geological analysis (porosity, permeability, RQI and pore type analysis) to preliminarily clarify the reservoir porosity-permeability relationship, reservoir pore type and its relationship with permeability, porosity and RQI; based on 180 samples of different pore types in the target layer of Puguang work area, analyze the mercury injection curve types and pore-permeability cross-plots, and overlap similar curves and points to divide them into five types of pore types.

[0037] 1.2. Conduct start-up pressure and seepage experiments to support the preliminary confirmation of the flow unit type and clarify the differences in start-up pressure and seepage index (FI) of samples with different pore types. 15 samples with different permeability of the Feixianguan Formation in the Puguang area were selected to carry out seepage characteristic experiments. By introducing the FI parameter (Q / (△P△S)), the differences in seepage characteristics of different samples can be clearly distinguished.

[0038] 1.3. Flow units are considered to be predictable reservoirs with specific seepage characteristics and a certain spatial distribution. When optimizing parameters, we should not only consider whether the parameters can reflect the seepage characteristics, but also the predictability of the parameters. Therefore, we optimize the flow unit division parameters, and use multiple dynamic and static reservoir parameters such as porosity, permeability, and RQI to conduct intersection analysis with FI. According to the size of the correlation, we can clarify the flow unit characterization parameters. We optimize permeability, porosity, RQI, FZI, R 35 The following five parameters are used as flow unit characterization parameters. Figure 2 As shown, taking permeability as an example, when the permeability is less than 0.03mD, the FI value is the smallest, indicating that the seepage capacity is the weakest; when the permeability is 0.03-0.11mD; when the permeability is 0.11-1mD, and when the permeability is 1-10mD, the FI gradually increases; when the permeability is greater than 10mD, the FI is the largest and tends to be stable.

[0039] 2. Based on the results of sample cluster analysis, the flow unit categories and their corresponding discriminant functions are clarified to achieve quantitative identification of classified flow units and output status analysis based on conventional logging curves.

[0040] 2.1. Conduct cluster analysis of reservoir parameters at multiple sample points (characterization parameters such as porosity, permeability, RQI, etc. corresponding to each sample) to achieve flow unit classification and determine the threshold value of each type of flow unit characterization parameter. Figure 3 As shown in the figure, by analyzing the porosity, permeability, R 35 , FZI, RQI and other five parameters are used for cluster analysis using statistical analysis software, and all flow units can be clustered into five categories: Class I flow unit, Class II flow unit, Class III flow unit, Class IV flow unit, and Class V flow unit.

[0041] 2.2 As shown in Table 2, five types of flow unit discriminant functions are established, corresponding to different pore types such as fracture type, medium-high porosity-medium-high permeability type, medium-porosity-medium permeability type, low-porosity-low permeability type and intragranular pore type.

[0042] Table 2 The discriminant function relationship of five types of flow units in the method embodiment of the present invention

[0043]

[0044] Based on the analysis of core sample points, the flow unit characterization parameters are obtained based on conventional logging curves, and the vertical classified flow unit distribution of each well is determined according to the threshold of the classified flow unit characterization parameters.

[0045] 2.3. Combined with the single well flow unit evaluation and output profile conclusions, statistical analysis was conducted on the differences in output ratios of classified flow units to clarify the differences in output characteristics of classified flow units. Figure 4As shown in the figure, based on the statistics and analysis of the production profile characteristics of the gas well classification flow units, it is clear that the production of Class III and Class IV flow units is relatively poor. Figure 5 As shown, the number of identified two types of flow units accounts for 61%, while the number of production layers accounts for only 23%.

[0046] 3. If Figure 6 As shown, the flow unit phase geological model is established by using the well point flow unit phase and the inter-well porosity, permeability and RQI model constraints; combined with the calibration analysis conclusions of the single well output status, the logical judgment and Gaussian truncation method are used to evaluate the reserve utilization status.

[0047] 3.1. Load the single well flow unit identification and division data into the geological model, and use the basic porosity, permeability and other attribute models to calculate the parameter model required for the flow unit characterization parameters.

[0048] 3.2. Based on the well point data and the well characterization parameter model, a three-dimensional flow unit model is established, and the "flow unit phase" geological model is established using porosity, permeability and RQI phase control constraints; combined with the single well calibration classification flow unit output status difference output status, extract Figure 7 The plane thickness map of the poorly developed flow units shown in the figure shows that there are 6 flow units with poor development and large reserves, with a total geological reserve of 19.147 billion cubic meters.

[0049] The monitoring results of gas wells that have been tested for production profiles in the current study area are used to compare the prediction results of the producing status. As shown in Table 1, the prediction results of the two are relatively close, indicating that the method of using the current flow unit characterization parameters to clarify the flow unit category and producing status is effective.

[0050] Table 1 Data table of experimental results of seepage characteristics of carbonate reservoir core samples in the method embodiment of the present invention

[0051]

[0052] In summary, combined with the analysis of the embodiments, it is shown that the prediction and evaluation of the gas reservoir production status by the present invention is relatively close to the production profile test results, and the production status of the massive gas reservoir is accurately and quantitatively evaluated, thereby clarifying the distribution characteristics of the poorly produced and unproduced reserves, and providing guidance for gas reservoir potential tapping and improving the degree of reserve production. Therefore, the present invention can meet the needs of evaluating the reserve production status and formulating efficient potential tapping plans in massive carbonate gas reservoirs.

Claims

1. A method for evaluating the producing status of massive carbonate gas reservoirs based on flow units, characterized in that: The steps include: 1) Using core samples of the target layer in the study area, the seepage characteristic experiment was carried out to clarify the difference in the seepage capacity index FI of different core samples, and the flow unit characterization parameters were determined through the intersection analysis of FI and reservoir characterization parameters; 2) Cluster analysis is performed on core samples. Based on the analysis results, the flow unit categories and their corresponding discriminant functions are clarified, and quantitative identification of classified flow units and output status analysis based on conventional logging curves are performed; 3) Establish a flow unit phase geological model, combine the calibration analysis conclusions of the single well production status, extract the plane thickness of the poorly utilized flow unit, and evaluate the reserve utilization status of different well areas in the plane.

2. The method for evaluating the producing status of massive carbonate gas reservoirs based on flow units according to claim 1, characterized in that: Before carrying out step 1), the core samples are subjected to analytical testing and geological analysis to preliminarily clarify the reservoir porosity-permeability relationship, reservoir pore type and its relationship with permeability, porosity and reservoir quality factor RQI.

3. The method for evaluating the producing status of massive carbonate gas reservoirs based on flow units according to claim 1, characterized in that: Step 1) The reservoir characterization parameters include porosity, permeability, and reservoir zone index FZI.

4. The method for evaluating the producing status of massive carbonate gas reservoirs based on flow units according to claim 1, characterized in that: In step 1), after intersection analysis, the flow unit characterization parameters are determined according to the magnitude of the correlation.

5. The method for evaluating the producing status of massive carbonate gas reservoirs based on flow units according to claim 1, characterized in that: In step 2), the cluster analysis is as follows: clustering the flow unit characterization parameters corresponding to each core sample to achieve flow unit classification and determine the threshold value of each type of flow unit characterization parameter.

6. The method for evaluating the producing status of massive carbonate gas reservoirs based on flow units according to claim 1, characterized in that: In step 2), the quantitative identification of the classified flow units and the analysis of the output status are as follows: based on conventional logging curves, the flow unit characterization parameters are obtained, and according to the characterization parameter thresholds of the classified flow units, the vertical classified flow unit distribution of each well is determined, and combined with the single well flow unit evaluation and the output profile conclusions, the differences in the output ratios of the classified flow units are statistically analyzed to clarify the differences in the output characteristics of the classified flow units.

7. The method for evaluating the producing status of massive carbonate gas reservoirs based on flow units according to claim 1, characterized in that: In step 3), the flow unit phase geological model is established by the following method: using geological modeling methods, the geological model of each characterization parameter between wells is established, the single well flow unit identification data is input into the geological model, and at the same time, based on the attribute models such as porosity and permeability, the parameter model required for the flow unit characterization parameters is calculated, and the flow unit phase geological model is established by adding the well point flow unit to the inter-well porosity, permeability, and RQI model constraints.

8. The method for evaluating the producing status of massive carbonate gas reservoirs based on flow units according to claim 7, characterized in that: The flow unit identification data is input into the geological model as flow unit phases.

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