A method and system for calculating the pressure of buried hill formations based on the coupling of well logging and logging data

Abstract

The present invention relates to a method for calculating the buried hill formation pressure based on the coupling of logging and mud logging binary data, which mainly includes the following steps: S1 Collect logging parameters and mud logging parameters; S2 Simulate the actual formation pressure based on the Dc index, drilling efficiency - mechanical specific energy monitoring, gas logging auxiliary judgment, measured formation pressure data, etc.; S3 Use the unary linear regression method to draw the intersection diagram between the logging data and the formation pressure value, and obtain the unary fitting equation between the formation pressure value and the logging parameters; S4 Use the binary linear regression method to draw the intersection diagram between the logging-mud logging binary data and the formation pressure value, and obtain the binary fitting equation between the formation pressure value and the logging-mud logging parameters; S5 Integrate the binary fitting equation between the formation pressure value and the logging-mud logging parameters, and establish a buried hill formation pressure calculation model based on the logging-mud logging binary coupling data.

Description

Technical Field

[0001] The present invention belongs to the field of rock mechanics, and particularly relates to a method for calculating the pressure of buried hill strata based on the coupling of logging and well logging binary data. The method establishes an effective calculation model system and can realize the quantitative evaluation of overpressure in buried hills. Background Art

[0002] The basement of the Qiongdongnan Basin is mainly Indosinian and Yanshanian granite buried hills (age: 65 Ma). The formation and evolution of the granite buried hills in the Qiongdongnan Basin are affected by multiple tectonic movements in the Indosinian, Yanshanian, and Himalayan periods, providing good conditions for the formation of weathered crusts and internal fractured reservoirs in the buried hills. The Qiongdongnan buried hills are divided into three buried hill zones: the southern buried hill zone, the central buried hill zone, and the northern buried hill zone. Generally, from the southern buried hill zone to the northern buried hill zone, the burial depth, burial time, and current seawater depth are all decreasing, and the development position of the buried hills is rising.

[0003] At present, the research on overpressure in sandstone and mudstone strata at home and abroad has gradually become mature. In recent years, the implementation of formation pressure monitoring in the Yingqiong Basin has initially had means for monitoring formation pressure based on the causes of pressure. The monitoring accuracy of formation pressure is relatively high in strata with conventional lithology and common pressure causes (such as undercompaction, fluid expansion, pressure conduction, etc.). However, in recent years, bedrock buried hills have gradually become one of the hot areas of exploration and development. The technical means for evaluating the pressure of special lithology strata in the bedrock buried hills of the Qiongdongnan Basin are relatively limited, seriously restricting the evaluation accuracy of formation pressure.

[0004] Conventional formation pressure evaluation models mainly include the equivalent depth method, empirical coefficient method, Eaton method, Bowers method, etc. The evaluation parameters used are mainly logging and well logging parameters such as acoustic travel time, resistivity, density, and Dc index. There is no obvious response in traditional logging data such as wave velocity in the overpressure section of special lithology strata such as carbonate rocks. The adaptability of conventional formation pressure evaluation methods in special lithology strata such as carbonate rocks and basement granite is poor. Therefore, the present invention proposes a new method for calculating formation pressure based on the coupling of logging and well logging binary data, combining logging and well logging to solve the problem that conventional formation pressure evaluation models are difficult to apply to special lithology strata in bedrock buried hills, and providing a theoretical basis for the accurate evaluation of formation pressure in the Yingqiong Basin and buried hill strata. Summary of the Invention

[0005] The present invention provides a method for calculating the pressure of buried hill strata based on the coupling of logging and well logging binary data, which includes the following steps:

[0006] S1: Collect logging data and well logging data;

[0007] S2: Simulate the actual formation pressure based on the Dc index, drilling efficiency - mechanical specific energy monitoring, gas logging assisted judgment, measured pressure data, etc.

[0008] S3: Plot the cross plot between the logging data and the formation pressure value, and use the method of unary linear regression to obtain the unary fitting equation between the formation pressure value and the logging data;

[0009] S4: Plot the cross plot among the logging data, mud logging data and the formation pressure value, and use the method of binary linear regression to obtain the binary fitting equation between the formation pressure value and the logging-mud logging parameters;

[0010] S5: Integrate the binary fitting equation between the formation pressure value and the logging-mud logging parameters to establish a formation pressure calculation model based on the logging-mud logging binary coupled data.

[0011] Specifically, in the above-mentioned S1, the logging data includes the acoustic travel time VP and density DEN, and the mud logging data mainly includes the Dc index, SIGA index, lateral work, vertical work, and mechanical specific energy MSE.

[0012] Preferably, in the above-mentioned S2, based on the Dc index, drilling efficiency - mechanical specific energy monitoring, gas logging auxiliary judgment, measured formation pressure data, etc., simulate the actual formation pressure, and the specific steps are as follows:

[0013] 1) For the same well A, select the logging and mud logging data used for calculating the formation pressure;

[0014] 2) Based on the Dc index, drilling efficiency - mechanical specific energy, monitor the formation pressure and calculate the formation pressure at different depths;

[0015] 3) Based on the gas logging data, assist in judging the formation pressure;

[0016] 4) Obtain the formation pressure at the test point through on-site actual testing;

[0017] 5) Through the mutual correction of the formation pressure results evaluated by the Dc index, drilling efficiency - mechanical specific energy monitoring, gas logging auxiliary judgment, and measured formation pressure data, obtain the final simulated actual formation pressure.

[0018] In the specific implementation manner, in the above-mentioned S3, plot the cross plot between the logging data and the formation pressure value, and use the method of unary linear regression to obtain the unary fitting equation between the formation pressure value and the logging data. The specific steps are as follows:

[0019] 1) Based on the logging data collected in step 1 and the formation pressure data calculated in step 2, plot the cross plot of the logging data and the formation pressure. Specific examples are as Figure 3 and Figure 4 shown.

[0020] 2) Use the method of unary linear regression to obtain the binary fitting equation between the formation pressure value and the logging data.

[0021] In a specific embodiment, in S4, a cross-plot between well logging parameters, mud logging data, and formation pressure values is drawn, and a binary fitting equation between the formation pressure value and well logging and mud logging parameters is obtained using the binary linear regression method. The specific steps are as follows:

[0022] 1) Based on the mud logging data collected in S1 and the formation pressure data calculated in S2, draw a cross-plot of the mud logging data and formation pressure of Well A;

[0023] 2) Use the binary linear regression method to obtain a binary fitting equation between the formation pressure value and well logging and mud logging parameters.

[0024] In another embodiment, in S5, the calculation model of the buried hill formation pressure based on the coupling of well logging-mud logging binary data is:

[0025] P p = m×VP + n×mud logging parameters (Dc, SIGA, MSE, longitudinal work, lateral work) + O

[0026] P p = j×DEN + k×mud logging parameters (Dc, SIGA, MSE, longitudinal work, lateral work) + L

[0027] Where: m, n, O, j, k, L are coefficients, which need to be determined by sub-blocks.

[0028] Specifically, the variation law of the fitting equation coefficients includes the distinction of magnitude and positive / negative. The closer the coefficient is to 1, the greater the correlation between the well logging and mud logging parameter and the formation pressure. A positive coefficient indicates a positive correlation, and a negative coefficient indicates a negative correlation.

[0029] The present invention provides a system for calculating the buried hill formation pressure based on the coupling of well logging-mud logging binary data, which includes modules for executing steps S1 to S5 of the method. Specifically, it includes a data entry module for entering the data from step S1; a data processing module for performing data calculations in steps S2 to S5; and a result output module for outputting the results obtained by the data processing module.

[0030] Optionally, it further includes a result display module.

[0031] Preferably, the entry is achieved through keyboard input and scanner recognition, and the result display template is a screen, remote terminal, or mobile terminal.

[0032] Compared with the prior art, the present invention has the following advantages: 1) A formation pressure calculation method based on the coupling of logging and well logging binary data disclosed by the present invention makes full use of logging and well logging data, comprehensively considers the complex geological background of buried hill reservoirs, and establishes an effective buried hill formation pressure calculation model through the methods of unary linear regression and binary linear regression, providing a new method and approach for realizing the quantitative evaluation of buried hill overpressure. 2) By drawing the crossplot between logging-well logging data and formation pressure values, and based on the analysis of well logging data, the present invention comprehensively considers the interaction relationship between the drill bit and the buried hill formation, and further obtains the binary fitting equation between logging-well logging parameters, constructing a well logging data volume that can effectively characterize the overpressure of the buried hill formation. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 FIG. is a flow chart of a method for calculating the formation pressure of a buried hill based on the coupling of logging and well logging binary data.

[0034] Figure 2 FIG. is the logging and well logging data collected in step 1.

[0035] Figure 3 FIG. is a crossplot fitting diagram of well logging density and formation pressure.

[0036] Figure 4 FIG. is a crossplot fitting diagram of acoustic time difference and formation pressure.

[0037] Figure 5 FIG. is a crossplot fitting diagram of Dc index and formation pressure.

[0038] Figure 6 FIG. is a crossplot fitting diagram of MSE and formation pressure.

[0039] Figure 7 FIG. is the logging and well logging data of Well B.

[0040] Figure 8 FIG. is a semi-logarithmic curve relationship diagram of the dc index - depth of Well B.

[0041] Figure 9 FIG. is a comparison diagram of the formation pressure obtained by the traditional method and the new method. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0042] The following further describes in detail a new method for calculating the formation pressure of a buried hill based on the coupling of logging and well logging binary data of the present invention with reference to the accompanying drawings and examples. The flow chart of the calculation method is as Figure 1 shown, and the specific implementation process is as follows:

[0043] Example 1. Establishment of the formation pressure calculation model system

[0044] Step 1: Select a well A in the buried hill formation with overpressure, and query the corresponding VP and DEN logging data, as well as the Dc index, SIGA index, lateral work, vertical work, and MSE logging parameters. The specific collection situation is as Figure 2 .

[0045] Step 2: Based on the Dc index, drilling efficiency - mechanical specific energy monitoring, gas logging assisted judgment, measured formation pressure data, etc., simulate the actual formation pressure. The specific steps are as follows:

[0046] 1) For the same well A, select the logging and well logging data used to calculate the formation pressure;

[0047] 2) Based on the Dc index and drilling efficiency - mechanical specific energy, monitor the formation pressure and calculate the formation pressure at different depths;

[0048] 3) Based on the gas logging data, assist in judging the formation pressure;

[0049] 4) Obtain the formation pressure at the test point through on-site actual testing;

[0050] 5) Through the mutual correction of the formation pressure results evaluated by the Dc index, drilling efficiency - mechanical specific energy monitoring, gas logging assisted judgment, and measured formation pressure data, obtain the final simulated actual formation pressure.

[0051] Step 3: Draw a crossplot between the logging data and the formation pressure value, and use the method of unary linear regression to obtain a unary fitting equation between the formation pressure value and the logging data. The specific steps are as follows:

[0052] 1) Based on the logging data collected in Step 1 and the formation pressure data calculated in Step 2, draw a crossplot of the logging data and the formation pressure, as Figure 3 and Figure 4 shown.

[0053] 2) Use the method of unary linear regression to obtain a binary fitting equation between the formation pressure value and the logging data.

[0054] Step 4: Draw a crossplot between the logging parameters, well logging data and the formation pressure value, and use the method of binary linear regression to obtain a binary fitting equation between the formation pressure value and the logging and well logging parameters. The specific steps are as follows:

[0055] 1) Based on the well logging data collected in Step 1 and the formation pressure data calculated in Step 2, draw a crossplot of the well logging data of Well A and the formation pressure, as Figure 5 and Figure 6 shown.

[0056] 2) Use the method of binary linear regression to obtain a binary fitting equation between the formation pressure value and the logging and well logging parameters, as shown in the following table:

[0057] Table 1, Binary fitting equations between formation pressure values and logging and well logging parameters of Well A

[0058]

[0059] Step 5: Synthesize the binary fitting equations between formation pressure values and logging - well logging parameters, and establish a buried - hill formation pressure calculation model based on logging - well logging binary - coupled data.

[0060] P p = m×VP + n×well logging parameters (Dc, SIGA, MSE, longitudinal work, transverse work)+O

[0061] P p = j×DEN + k×well logging parameters (Dc, SIGA, MSE, longitudinal work, transverse work)+L

[0062] Example 2: Application example of the formation pressure calculation model system of the present invention

[0063] Taking a buried - hill formation in the Ying - Qiong Basin of China as an example, the application of the present invention in formation pressure calculation during the exploration and development of buried - hill reservoirs is systematically described.

[0064] Step 1: In this example, Well B in the buried - hill reservoir is selected as an example, and the corresponding VP, DEN logging data and well logging parameters such as Dc index, SIGA index, transverse work, longitudinal work, and MSE are collected, as Figure 7 shown.

[0065] Step 2: Based on Example 1, establish a formation pressure calculation model for Well B, and the binary fitting equations between formation pressure values and logging - well logging parameters can be obtained as shown in the following table:

[0066] Table 2, Binary fitting equations between formation pressure values and logging - well logging parameters of Well B

[0067]

[0068] Step 3: Based on the traditional formation pressure calculation method, taking the dc - index method as an example, calculate the magnitude of reservoir overpressure. The specific steps are as follows:

[0069] 1) For the same Well B, select the logging - well logging data used for calculating formation pressure;

[0070] 2) Establish the normal trend - line equation of the dc index of this well. Draw the semi - logarithmic curve relationship diagram between the dc index and depth of Well B, as Figure 8 shown, and obtain the normal trend - line equation of the well as follows:

[0071] h = 388.314lgd cn + 4020.35

[0072] where h is the well depth, in m; d cn — the normal trend line d at depth h c value.

[0073] 3) According to the traditional formation pressure calculation method, calculate the formation pressures at different depths. The pressure calculation formula is as follows:

[0074]

[0075] where P P — the formation pressure, in MPa; Cd is the correction coefficient, obtained by back-calculating from the measured formation pressure; P n — the normal formation pore pressure, in MPa.

[0076] Step 4, draw a comparison chart of the formation pressures calculated by the traditional method and the formation pressures calculated by the new method for buried hill formation pressure calculation based on the coupling of logging and well logging binary data, as Figure 9 shown, and evaluate the overpressure of the buried hill reservoir.

[0077] In this embodiment, the formation pressures of the buried hill formation are calculated respectively by using the traditional formation pressure calculation method and the new method for formation pressure calculation based on the coupling of logging and well logging binary data, and compared with the measured formation pressure. It is found that the formation pressures obtained by the new method have higher prediction accuracy than those by the traditional formation pressure calculation method, and the relative error is reduced from 6% to 3%, revealing the rationality and effectiveness of the present invention.

Claims

1. A method for calculating buried hill formation pressure based on the coupling of logging binary data, characterized in that: The following steps are involved: S1: Collect well logging data and mud logging data; S2: Simulate the actual formation pressure based on Dc index, drilling efficiency-mechanical specific energy monitoring, gas measurement auxiliary judgment, measured pressure data, etc.; In the above S2, the actual formation pressure is simulated based on the Dc index, drilling efficiency-mechanical specific energy monitoring, gas measurement auxiliary judgment, measured pressure data, etc. The specific steps are as follows: 1) For the same well A, select the logging data used to calculate the formation pressure; 2) Monitor formation pressure based on Dc index and drilling efficiency-mechanical specific energy, and calculate formation pressure at different depths; 3) Assist in judging formation pressure based on gas logging data; 4) Obtain the formation pressure at the test point through actual on-site testing; 5) The mutual correction between the formation pressure results is evaluated through Dc index, drilling efficiency-mechanical specific energy monitoring, gas measurement auxiliary judgment, and measured pressure data to obtain the final simulated actual formation pressure; S3: draw an intersection diagram between the well logging data and the formation pressure value, and use a univariate linear regression method to obtain a univariate fitting equation between the formation pressure value and the well logging data; S4: draw an intersection diagram between logging data, mud logging data and formation pressure values, and use a binary linear regression method to obtain a binary fitting equation between the formation pressure value and the logging-mud logging parameters; S5: A binary fitting equation between the formation pressure value and the logging parameters is integrated to establish a formation pressure calculation model based on the logging-logging binary coupling data.

2. The calculation method according to claim 1, characterized in that: In the S1, the logging data include the acoustic time difference VP and the density DEN, and the logging data mainly include the Dc index, the SIGA index, the lateral work, the longitudinal work, and the mechanical specific energy MSE.

3. The calculation method according to claim 1, characterized in that: In the above S3, an intersection diagram between the well logging data and the formation pressure value is drawn, and a univariate linear regression method is used to obtain a univariate fitting equation between the formation pressure value and the well logging data. The specific steps are as follows: 1) Based on the well logging data collected in step 1 and the formation pressure data calculated in step 2, draw an intersection diagram of the well logging data and the formation pressure; 2) Using the univariate linear regression method, the binary fitting equation between the formation pressure value and the logging data is obtained.

4. The calculation method according to claim 1, characterized in that: In the above S4, an intersection diagram between logging parameters, logging data and formation pressure values ​​is drawn, and a binary fitting equation between formation pressure values ​​and logging parameters is obtained by using a binary linear regression method. The specific steps are as follows: 1) Based on the logging data collected in S1 and the formation pressure data calculated in S2, draw an intersection diagram of the logging data of Well A and the formation pressure; 2) The binary linear regression method is used to obtain the binary fitting equation between the formation pressure value and the logging parameters.

5. The calculation method according to claim 1, characterized in that: In the above S5, the buried hill formation pressure calculation model based on the well logging-mud logging binary data coupling is: ； Where: m, n, O, j, k, L are coefficients, which need to be determined by block.

6. A system for calculating buried hill formation pressure based on the coupling of logging and well logging binary data, characterized in that: It comprises a module for executing steps S1 to S5 of the method according to any one of claims 1 to 5, including a data entry module for entering data from step S1; A data processing module, used to perform data calculations in steps S2 to S5; And a result output module is used to output the results obtained by the data processing module.

7. The system according to claim 6, characterized in that Also includes a result display module.

8. The system according to claim 7, characterized in that The input is realized through a keyboard and a scanner, and the result display module is a screen, a remote terminal, or a mobile terminal.

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