A method, system, and computer equipment for predicting the maturity of shale and mudstone through well logging.

Abstract

This invention provides a method, system, and computer equipment for predicting the maturity of shale and mudstone reservoirs through well logging. By analyzing the total porosity and total organic carbon content of shale and mudstone cores from different regions, this invention obtains a mathematical relationship between relative porosity and total organic carbon content. This mathematical relationship reflects the porosity-enhancing efficiency of organic matter and reveals a close relationship between this efficiency and vitrinite reflectivity, which reflects the thermal maturity of organic matter. As maturity increases, the porosity-enhancing efficiency of reservoir organic matter decreases. Therefore, the maturity of shale and mudstone reservoirs can be predicted and evaluated based on the porosity-enhancing efficiency of organic matter. Based on this, this invention establishes a "three-parameter" chart using data on total porosity, total organic carbon content, and vitrinite reflectivity of shale and mudstone from different regions. By processing the data in the area to be tested, the mathematical relationship between relative porosity and total organic carbon content of the shale and mudstone reservoir is obtained. Combined with the "three-parameter" chart, the organic matter maturity can be determined, providing a reference for reservoir evaluation and prediction.

Description

Technical Field

[0001] This invention relates to the field of evaluating oil and gas reservoirs containing organic mudstone and shale, and particularly to a well logging prediction method, system, and computer equipment for mudstone and shale maturity. Background Technology

[0002] After years of research and practice, my country has explored geological evaluation methods for shale oil and gas reservoirs, including oil and gas accumulation zones, sweet spots, and sweet sections. Among them, sweet sections are shale oil and gas layers with good oil and gas content, superior reservoir conditions, strong modifiability, and commercial development value under current economic and technological conditions. The specific evaluation contents include hydrocarbon generation quality, reservoir quality, engineering mechanical quality, and oil content.

[0003] From the perspective of the development of well logging petrophysical evaluation technology, it has gone through the analysis of the "four properties" of conventional sandstone and mudstone reservoirs, to the analysis of the "seven properties" of tight oil and gas and shallow and medium-depth mudstone and shale gas, and then to the analysis of "reservoirability," "oil (gas) content," "mobility," and "compressibility" of mudstone and shale oil and deep mudstone and shale gas, and the selection of "sweet spots" for well logging "three quality" evaluation. Among them, the core of reservoir quality evaluation is reservoirability, the key of which is to accurately evaluate the micro-nano pore system of organic-rich mudstone and shale, including the quantitative characterization of porosity and pore structure. The micro-nano pore system has a great influence on the reservoir performance, oil and gas occurrence state, and transport mechanism of mudstone and shale oil and gas. In addition, most of the oil and gas in mudstone and shale reservoirs exist in the pores in the form of adsorption, and accurate pore structure description and evaluation are the key to predicting and developing mudstone and shale oil and gas.

[0004] The pore system of organic-rich shale mainly consists of organic matter pores and inorganic mineral matrix pores. Its pore system evolution during geological periods is more complex than that of conventional reservoirs, influenced not only by diagenesis but also by the hydrocarbon generation and expulsion processes of organic matter. Organic matter, as the material basis of organic pores, exhibits a positive correlation; the thermal maturity of organic matter directly determines the development degree of organic pores. The compaction resistance of inorganic mineral components affects the preservation capacity of organic pores. As the thermal maturity of organic matter increases, oil-generating pores, gas-generating pores, and mechanical compaction of organic pores, and even the disappearance of organic pores, appear successively. The mechanism by which the organic matter evolution process affects the inorganic reservoir space of shale is still debated. Macroscopically, it may be related to burial history, thermal evolution history, and sedimentary environment; microscopically, it may be related to the complex fabric of shale.

[0005] The impact of organic matter in shale on reservoir space is manifested in the physical and chemical alteration of the formation during thermal evolution, far exceeding its contribution to the total porosity. Therefore, clarifying the relationship between organic matter, its thermal maturity, and total porosity in shale reservoirs is of great significance for reservoir evaluation and the prediction of "sweet spots." Summary of the Invention

[0006] To address the problems of the prior art, this invention provides a well logging prediction method and system for shale maturity, revealing the influence mechanism of organic matter on total reservoir porosity during geological and thermal evolution, and providing a reference for reservoir evaluation and prediction of "sweet spots".

[0007] This invention is achieved through the following technical solution:

[0008] A well logging method for predicting the maturity of shale and mudstone is characterized by comprising:

[0009] S1, obtain the total porosity and total organic carbon content of the mudstone and shale reservoir in the area to be tested by regional logging data;

[0010] S2, establish the mathematical relationship between the total porosity and total organic carbon content of the shale reservoir in the area to be tested, and perform a translation transformation through the origin of the coordinate system to obtain the mathematical relationship between the relative porosity and total organic carbon content of the shale reservoir;

[0011] S3 projects the mathematical relationship between the relative porosity and total organic carbon content of shale reservoirs onto a three-parameter chart to predict the maturity of shale reservoirs in the area to be tested.

[0012] The three-parameter chart is obtained through the following method: obtaining the total porosity, total organic carbon content, and vitrinite reflectance of shale cores from multiple different regions; establishing the mathematical relationship between the total porosity and total organic carbon content of cores from each region and performing a translational transformation through the origin of the coordinate system to obtain the mathematical relationship between the relative porosity and total organic carbon content of cores from each region; and using the mathematical relationship between the relative porosity and total organic carbon content of each region and the vitrinite reflectance, drawing a three-parameter chart reflecting the maturity of shale.

[0013] Preferably, when the total organic carbon content is less than or equal to 2%, the mathematical relationship between total porosity and total organic carbon content is as shown in equation (1), and when the total organic carbon content is greater than 2%, the mathematical relationship between total porosity and total organic carbon content is as shown in equation (2):

[0014]

[0015]

[0016] in, , where is the total porosity (%), TOC is the total organic carbon content (%), and a1, a2, b1, and b2 are regression coefficients.

[0017] Furthermore, when the total organic carbon content is less than or equal to 2%, the mathematical relationship between the relative porosity and the total organic carbon content is shown in equation (3):

[0018]

[0019] When the total organic carbon content is greater than 2%, the mathematical relationship between the relative porosity and the total organic carbon content is as shown in equation (4):

[0020]

[0021] in, is the relative porosity after translation, %; k is the defined organic matter porosimetry efficiency.

[0022] Preferably, the mudstones from the various regions include marine sedimentary mudstones and terrestrial sedimentary mudstones.

[0023] Preferably, the total porosity, total organic carbon content, and vitrinite reflectance of shale cores from multiple different regions are obtained specifically from laboratory test data.

[0024] Preferably, establishing the mathematical relationship between the total porosity and total organic carbon content of the shale reservoir in the test area specifically involves: drawing a cross-plot of the total porosity and total organic carbon content of the shale reservoir in the test area, and establishing the mathematical relationship between the total porosity and total organic carbon content of the shale reservoir in the test area based on the cross-plot;

[0025] The specific steps for establishing the mathematical relationship between the total porosity and total organic carbon content of core samples from different regions are as follows: draw a cross-plot of the total porosity and total organic carbon content of mudstone and shale core samples from different regions, and establish the mathematical relationship between the total porosity and total organic carbon content of core samples from different regions based on the cross-plot.

[0026] Furthermore, the mathematical relationship between the total porosity and total organic carbon content of the shale reservoir in the test area is established based on the cross plot. Specifically, regression analysis is performed on the cross plot to establish the mathematical relationship between the total porosity and total organic carbon content of the shale in the test area.

[0027] The specific steps for establishing the mathematical relationship between total porosity and total organic carbon content of core samples from different regions based on the cross plot are as follows: Regression analysis is performed on the cross plot to establish the mathematical relationship between total porosity and total organic carbon content of core samples from different regions.

[0028] Furthermore, the regression analysis is specifically performed using data analysis software.

[0029] A well logging prediction system for shale maturity includes:

[0030] The data acquisition module obtains the total porosity and total organic carbon content of the mudstone and shale reservoirs in the area to be tested through regional logging data;

[0031] The data analysis module establishes the mathematical relationship between the total porosity and total organic carbon content of the shale reservoir in the test area and performs a translational transformation through the origin of the coordinate system to obtain the mathematical relationship between the relative porosity and total organic carbon content of the shale reservoir. The mathematical relationship between the relative porosity and total organic carbon content of the shale reservoir is then projected onto a three-parameter chart to predict the maturity of the shale reservoir in the test area.

[0032] The three-parameter chart is obtained through the following method: obtaining the total porosity, total organic carbon content, and vitrinite reflectance of shale cores from multiple different regions; establishing the mathematical relationship between the total porosity and total organic carbon content of cores from each region and performing a translational transformation through the origin of the coordinate system to obtain the mathematical relationship between the relative porosity and total organic carbon content of cores from each region; and using the mathematical relationship between the relative porosity and total organic carbon content of each region and the vitrinite reflectance, drawing a three-parameter chart reflecting the maturity of shale.

[0033] A computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the well logging prediction method for shale maturity as described above.

[0034] Compared with the prior art, the present invention has the following beneficial effects:

[0035] This invention analyzes the total porosity and total organic carbon content of shale cores from different regions to obtain a mathematical relationship between relative porosity and total organic carbon content. This relationship reflects the porosity-enhancing efficiency of organic matter and reveals a close relationship between this efficiency and vitrinite reflectivity, which reflects the thermal maturity of organic matter. As maturity increases, the porosity-enhancing efficiency of reservoir organic matter decreases. Therefore, the porosity-enhancing efficiency of organic matter can be used to predict and evaluate the maturity of shale reservoirs. Based on this, this invention establishes a "three-parameter" chart using data on total porosity, total organic carbon content, and vitrinite reflectivity of shale from different regions. By processing the data for the tested area, the mathematical relationship between relative porosity and total organic carbon content of shale reservoirs is obtained. Combined with the "three-parameter" chart, the maturity of organic matter can be determined. This invention establishes the intrinsic relationship between total porosity, total organic carbon content, and thermal maturity of shale reservoirs through the analysis of existing experimental data, revealing the influence mechanism of organic matter on total reservoir porosity during geological thermal evolution, and providing a new approach to predicting the thermal maturity of shale reservoirs. Attached Figure Description

[0036] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0037] Figure 1 This is a flowchart of the well logging prediction method for mudstone and shale maturity provided in this embodiment of the invention;

[0038] Figure 2 These are cross plots of total porosity and total organic carbon content of shale reservoirs in five regions, along with mathematical relationships from regression analysis, provided in this embodiment of the invention.

[0039] Figure 3 This embodiment of the invention provides a graph showing the relationship between relative porosity and TOC after shifting the mathematical expression through the origin for five regions with TOC less than or equal to 2%.

[0040] Figure 4 This is an evaluation and prediction chart of the three parameters of relative porosity, total organic carbon content, and vitrinite reflectance provided in the embodiments of the present invention. Detailed Implementation

[0041] To further understand the present invention, the present invention will be described below with reference to embodiments. These descriptions are only for further explaining the features and advantages of the present invention and are not intended to limit the claims of the present invention.

[0042] See Figure 1 The well logging prediction method for shale maturity according to the present invention includes the following steps:

[0043] Step 1: Obtain the total porosity, total organic carbon content, and vitrinite reflectance of shale cores from multiple different regions from laboratory test data;

[0044] Step 2: Draw a cross-plot of total porosity and total organic carbon content for shale cores from various regions. Based on this plot, use regression analysis to establish the mathematical relationship between total porosity and total organic carbon content for each region. When the total organic carbon content is less than or equal to 2%, the relationship is linear; when the total organic carbon content is greater than 2%, the relationship is logarithmic. Specifically:

[0045]

[0046]

[0047] in, , where is the total porosity of the core, %, and TOC is the total organic carbon content of the corresponding core, % (mass percentage). a1, a2, b1, and b2 are regression coefficients.

[0048] Step 3: For TOC less than or equal to 2%, the linear formula (1) in Step 2 is translated through the origin of the coordinate system to obtain the mathematical relationship between relative porosity and total organic carbon content:

[0049]

[0050] When TOC is greater than 2%, the mathematical relationship between relative porosity and total organic carbon content is obtained by translating formula (2) in step 2 through the origin of the coordinate system:

[0051]

[0052] in, The relative porosity after translation, in %;

[0053] Step 4, define the porosity of organic matter in shale reservoirs:

[0054]

[0055]

[0056] Where Ro is the vitrinite reflectance, %; k is the defined organic matter porosimetry efficiency, which represents the increase in reservoir porosity per unit of total organic carbon content. It is closely related to the organic matter thermal maturity Ro. As the maturity Ro increases, the reservoir organic matter porosimetry efficiency decreases.

[0057] Step 5: Using the mathematical relationship between relative porosity and total organic carbon content of core samples from different regions and vitrinite reflectance data, plot the "three-parameter" chart reflecting the organic matter porosity efficiency k and vitrinite reflectance Ro from Step 4.

[0058] Step 6: Obtain the total porosity and total organic carbon content of the shale reservoir core in the area to be tested using regional logging data. Use the methods described in Steps 2-3 above to obtain the mathematical relationship between the relative porosity and total organic carbon content in the area to be tested. Based on this mathematical relationship, predict the maturity of the shale using a "three-parameter" chart, thereby evaluating and predicting favorable shale reservoirs in unknown areas.

[0059] This invention also provides a well logging prediction system for shale maturity, comprising:

[0060] The data acquisition module obtains the total porosity and total organic carbon content of the mudstone and shale reservoirs in the area to be tested through regional logging data;

[0061] The data analysis module establishes the mathematical relationship between the total porosity and total organic carbon content of the shale reservoir in the test area and performs a translational transformation through the origin of the coordinate system to obtain the mathematical relationship between the relative porosity and total organic carbon content of the shale reservoir. The mathematical relationship between the relative porosity and total organic carbon content of the shale reservoir is then projected onto a three-parameter chart to predict the maturity of the shale reservoir in the test area.

[0062] The three-parameter chart is obtained through the following method: obtaining the total porosity, total organic carbon content, and vitrinite reflectance of shale cores from multiple different regions; establishing the mathematical relationship between the total porosity and total organic carbon content of cores from each region and performing a translational transformation through the origin of the coordinate system to obtain the mathematical relationship between the relative porosity and total organic carbon content of cores from each region; and using the mathematical relationship between the relative porosity and total organic carbon content of each region and the vitrinite reflectance, drawing a three-parameter chart reflecting the maturity of shale.

[0063] The present invention also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that the processor executes the computer program to implement the steps of the well logging prediction method for shale maturity as described above.

[0064] Example

[0065] See Figure 1 This invention provides a well logging prediction method for shale maturity, which is operated according to the following steps:

[0066] Step 1: In this embodiment, total porosity, total organic carbon content, and vitrinite reflectance test data were obtained from mudstone and shale cores from five marine and terrestrial regions both domestically and internationally.

[0067] Step 2: Construct a cross-plot between total porosity and total organic carbon content in the core (see...). Figure 2 Based on the cross plot of total porosity and total organic carbon content in the core samples, data analysis software (such as Excel) was used to perform regression analysis on the mathematical relationship between total porosity and total organic carbon content for the five regions in two cases: total organic carbon content less than or equal to 2% and total organic carbon content greater than 2%. The slope and intercept values ​​were determined (see [reference]). Figure 2 ).

[0068] Step 3: For both cases where TOC is less than or equal to 2% and greater than 2%, perform a translation based on the mathematical relationship obtained in Step 2. Specifically, shift the intercept to 0 through the origin of the coordinate system (see [reference]). Figure 3 The following relationship was obtained: In the example, when TOC is less than or equal to 2%, the relative porosity of the five regions is... The mathematical expressions for the total organic carbon content are as follows:

[0069]

[0070]

[0071]

[0072]

[0073]

[0074] Step four: Using the mathematical expressions obtained in step three, and combining them with the vitrinite reflectance of the five regions, plot the reservoir evaluation and prediction charts based on the "three parameters" of relative porosity, total organic carbon content, and vitrinite reflectance (see [reference]). Figure 4 ).

[0075] Step 5: For other shale and mudstone areas to be tested, obtain the total porosity and total organic carbon content of the shale and mudstone through well logging data. By implementing steps 2 and 3, the data relationship curve between relative porosity and total organic carbon content can be obtained. The data points on the data relationship curve between relative porosity and total organic carbon content are then plotted on the "three-parameter" reservoir evaluation and prediction chart to determine the porosity increase efficiency and maturity of organic matter, thereby realizing the evaluation of shale and mudstone reservoirs and the prediction of favorable reservoirs.

[0076] The technical solutions provided in the embodiments of the present invention have been described in detail above. Specific examples have been used to illustrate the principles and implementation methods of the embodiments of the present invention. The descriptions of the embodiments above are only for helping to understand the principles of the embodiments of the present invention. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the embodiments of the present invention. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A method of shale maturity log prediction, characterized by, The method comprises the following steps: S1, obtaining total porosity and total organic carbon content of the shale reservoir in the region to be measured through regional logging data; S2, establishing a mathematical relationship between total porosity and total organic carbon content of the shale reservoir in the region to be measured and translating the coordinate system origin to obtain a mathematical relationship between relative porosity and total organic carbon content of the shale reservoir; When the total organic carbon content is less than or equal to 2%, the mathematical relationship between total porosity and total organic carbon content is as formula (1), and when the total organic carbon content is greater than 2%, the mathematical relationship between total porosity and total organic carbon content is as formula (2): （ TOC ≤2%）（1） （ TOC ＞2%）（2） Wherein, φ is total porosity, %, TOC is total organic carbon content, %, a1, a2, b1 and b2 are regression coefficients; When the total organic carbon content is less than or equal to 2%, the mathematical relationship between relative porosity and total organic carbon content is as formula (3): （3） When the total organic carbon content is greater than 2%, the mathematical relationship between relative porosity and total organic carbon content is as formula (4): （4） wherein, φ is the relative porosity after translation; k is the defined organic matter porosity efficiency; S3, projecting the mathematical relationship between relative porosity and total organic carbon content of the shale reservoir into a three-parameter chart to predict the maturity of the shale reservoir in the region to be measured; Wherein, the three-parameter chart is obtained by the following method: obtaining total porosity, total organic carbon content and vitrinite reflectance of shale cores in multiple different regions; establishing a mathematical relationship between total porosity and total organic carbon content of the cores in each region and translating the coordinate system origin to obtain a mathematical relationship between relative porosity and total organic carbon content of the cores in each region; using the mathematical relationship between relative porosity and total organic carbon content and the vitrinite reflectance in each region to draw a three-parameter chart reflecting the maturity of shale.

2. The shale maturity log prediction method of claim 1, wherein, The multiple different regions of shale include marine deposited shale and terrestrial deposited shale.

3. The shale maturity log prediction method of claim 1, wherein, The total porosity, total organic carbon content and vitrinite reflectance of shale cores in multiple different regions are obtained from laboratory test data.

4. The shale maturity log prediction method of claim 1, wherein, The mathematical relationship between total porosity and total organic carbon content of the shale reservoir in the region to be measured is established by drawing a crossplot of total porosity and total organic carbon content of the shale reservoir in the region to be measured and establishing a mathematical relationship between total porosity and total organic carbon content according to the crossplot. The mathematical relationship between total porosity and total organic carbon content of the cores in each region is established by drawing a crossplot of total porosity and total organic carbon content of the shale cores in each region and establishing a mathematical relationship between total porosity and total organic carbon content according to the crossplot.

5. The shale maturity log prediction method of claim 4, wherein, The mathematical relationship between total porosity and total organic carbon content of the shale reservoir in the region to be measured is established by performing regression analysis on the crossplot to establish a mathematical relationship between total porosity and total organic carbon content of the shale in the region to be measured; The mathematical relationship between total porosity and total organic carbon content of the cores in each region is established by performing regression analysis on the crossplot to establish a mathematical relationship between total porosity and total organic carbon content of the cores in each region.

6. The shale maturity log prediction method of claim 5, wherein, The regression analysis is performed by using data analysis software.

7. A shale maturity log prediction system characterized by, The method comprises the following steps: The data acquisition module acquires the total porosity and total organic carbon content of the shale reservoir in the region to be measured through regional logging data; The data analysis module establishes a mathematical relationship between the total porosity and total organic carbon content of the shale reservoir in the region to be measured and makes a translation change through the coordinate system origin to obtain a mathematical relationship between the relative porosity and total organic carbon content of the shale reservoir; and projects the mathematical relationship between the relative porosity and total organic carbon content of the shale reservoir to a three-parameter chart to predict the maturity of the shale reservoir in the region to be measured. When the total organic carbon content is less than or equal to 2%, the mathematical relationship between the total porosity and total organic carbon content is as shown in equation (1), and when the total organic carbon content is greater than 2%, the mathematical relationship between the total porosity and total organic carbon content is as shown in equation (2): （ TOC ≤2%）（1） （ TOC ＞2%）（2） Wherein, φ is the total porosity, %, TOC is the total organic carbon content, %, a1, a2, b1 and b2 are regression coefficients. When the total organic carbon content is less than or equal to 2%, the mathematical relationship between the relative porosity and total organic carbon content is as shown in equation (3): （3） When the total organic carbon content is greater than 2%, the mathematical relationship between the relative porosity and total organic carbon content is as shown in equation (4): （4） wherein, φ is the relative porosity after translation; k is the defined organic matter porosity efficiency; Wherein, the three-parameter chart is obtained by the following method: acquiring the total porosity, total organic carbon content and vitrinite reflectance of shale cores in multiple different regions; establishing a mathematical relationship between the total porosity and total organic carbon content of the cores in each region and making a translation change through the coordinate system origin to obtain a mathematical relationship between the relative porosity and total organic carbon content of the cores in each region; and using the mathematical relationship between the relative porosity and total organic carbon content and the vitrinite reflectance in each region to draw a three-parameter chart reflecting the maturity of shale.

8. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, The processor implements the steps of the shale maturity logging prediction method according to any one of claims 1 to 6 when executing the computer program.

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