Well logging modeling method for transition phase belt mixed rock

Abstract

The invention discloses a logging modeling method for transition phase belt mixed rock, and relates to the field of oil-gas exploration and development. The well logging modeling method for the transition phase belt mixed rock comprises the steps that after a mixed rock target layer section is divided, well logging indexes with high correlation are selected and subjected to standardization processing; establishing a multi-mineral well logging interpretation model to calculate the mineral content and the porosity of the target interval of the mixed rock and positively calculating a theoretical well logging curve; comparing the theoretical logging curve with the actually measured logging curve, analyzing and evaluating the model error; according to allowable error requirements, well logging parameter values are adjusted to enable the average deviation to be minimum, and an optimal multi-mineral well logging interpretation model is obtained; and the optimized multi-mineral well logging interpretation model is used to calculate target mineral components and porosity. According to the logging modeling method for the transition phase belt mixed rock, the composition of complex lithology, the mineral content and the porosity can be determined, and the defects that the drilling and coring cost is high, and errors exist between logging rock debris lithology description and depth are overcome.

Description

Technical Field

[0001] The present application relates to the field of oil and gas exploration and development, and in particular to a well logging modeling method for mixed sedimentary rocks in a transitional phase zone. Background Art

[0002] The current oil and gas exploration is mainly carried out for conventional sandstone reservoirs in clastic rock areas and inter-salt shale oil in chemical rock areas. The sedimentary transition zone between clastic rock and chemical rock (transition from clastic rock to chemical rock) is still in an exploration blank zone. The main problems in this area are unclear lithology distribution, unclear reservoir characteristics of different lithologies, and unclear transition phase zone accumulation model.

[0003] Previous studies believed that the lithology of the transitional phase zone is mainly sandstone and mudstone. The conventional mud content model was used to obtain the mud content and sandstone content, but the existence of carbonate rocks and other lithologies was ignored, which directly affected the establishment of the model of mineral content and logging parameters, resulting in large errors in the calculation results. At the same time, for parameters such as porosity, the porosity model of adjacent sandstone formations was mainly used, so that the porosity values ​​obtained were generally small.

[0004] Therefore, a logging modeling method suitable for mixed sedimentary rocks in transitional phases is needed to realize the logging interpretation of the special lithology in this phase. Summary of the invention

[0005] The purpose of the present application is to provide a logging modeling method for transitional phase mixed sedimentary rocks, which can determine the composition and mineral content of complex lithology, and make up for the defects of high drilling coring costs and errors in logging cuttings lithology description and depth.

[0006] This application is implemented as follows:

[0007] The present application provides a well logging modeling method for transitional phase mixed sedimentary rocks, and the well logging modeling method for transitional phase mixed sedimentary rocks comprises the following steps:

[0008] S1. According to the logging curve and field data, the logging response characteristics of various lithologies are clarified, and the target layer sections of the mixed rock are divided according to the logging response characteristics;

[0009] S2. According to the correlation analysis between the core measured data and the logging curve of the target layer of the mixed rock, the well logging indicators with close correlation are selected, and the selected well logging indicators are standardized;

[0010] S3. Establish a multi-mineral logging interpretation model, use the optimal mathematical calculation method and object-oriented programming, and calculate the mineral composition and porosity through the volume model;

[0011] S4, using the calculated mineral composition to perform a theoretical well logging curve;

[0012] S5. Compare and analyze the theoretical logging curve with the measured logging curve, evaluate the error of the multi-mineral logging interpretation model, adjust the logging parameter value according to the allowable error requirement, minimize the average deviation, and obtain the optimized multi-mineral logging interpretation model;

[0013] S6. Calculate the target mineral composition and porosity using the optimized multi-mineral logging interpretation model.

[0014] In some optional embodiments, the logging curves include natural gamma curves, deep lateral curves, sonic curves, and density curves.

[0015] In some optional embodiments, the field data includes well logging, gas logging, and thin section analysis.

[0016] In some optional embodiments, the well logging indicators include natural gamma, density and sonic time difference curves.

[0017] In some optional implementation schemes, the logging indicators are sampled and edited using a point-by-point sampling method.

[0018] In some alternative embodiments, the mineral components include mudstone content, sandstone content, and carbonate content.

[0019] In some optional embodiments, the logging response characteristics of the lithology include intraclastic limestone with medium-high density and high resistivity, intraclastic sandstone with medium-low density and medium-low resistivity, and felsic micrite dolomite with high density and medium-low resistivity.

[0020] In some optional embodiments, the mineral composition positive performance theoretical logging curve is calculated using logging parameters based on the formation.

[0021] The beneficial effects of the present application are as follows: the logging modeling method for transitional phase mixed sedimentary rocks provided by the present application comprises the following steps: clarifying the logging response characteristics of various lithologies based on logging curves and field data, and dividing the mixed sedimentary rock target layer segments based on the logging response characteristics; selecting closely correlated logging indicators and standardizing the selected logging indicators based on the correlation analysis between the core measured data and the logging curves of the mixed sedimentary rock target layer segments; establishing a multi-mineral logging interpretation model, using the optimal mathematical calculation method and object-oriented programming, and calculating the mineral components and porosity through a volume model; using the calculated mineral components to perform a theoretical logging curve; comparing and analyzing the theoretical logging curve with the measured logging curve, evaluating the error of the multi-mineral logging interpretation model, adjusting the logging parameter values ​​according to the allowable error requirements, so that the average deviation is minimized, and obtaining an optimized multi-mineral logging interpretation model; using the optimized multi-mineral logging interpretation model to calculate the target mineral components and porosity. The logging modeling method for transitional phase mixed sedimentary rocks provided in the present application can determine the composition and mineral content of complex lithologies, making up for the defects of high drilling coring costs and errors in the lithology description and depth of logging cuttings. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0023] Figure 1 A schematic diagram of the flow of a well logging modeling method for transitional phase mixed sedimentary rocks provided in an embodiment of the present application;

[0024] Figure 2 A comparison diagram of a theoretical logging curve and a measured logging curve in the logging modeling method for transitional phase mixed sedimentary rocks provided in an embodiment of the present application;

[0025] Figure 3 A comparison chart of the mineral content and porosity calculated by the logging modeling method for the transitional phase zone mixed sedimentary rock provided in the embodiment of the present application and the mineral content and porosity obtained by core testing. DETAILED DESCRIPTION

[0026] In order to make the purpose, technical scheme and advantages of the embodiments of the present application clearer, the technical scheme in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all of the embodiments. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the application claimed for protection, but merely represents the selected embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0027] The characteristics and performance of the well logging modeling method for transitional phase mixed sedimentary rocks of the present application are further described in detail below in conjunction with the embodiments.

[0028] like Figure 1 As shown, the embodiment of the present application provides a well logging modeling method for transitional phase mixed sedimentary rocks, which includes the following steps:

[0029] S1. Based on the natural gamma curve, acoustic time difference curve, density curve and other logging curves, combined with logging, gas logging, thin section analysis and other data, the logging response characteristics of the three lithologies are clarified as intraclastic limestone with medium-high density and high resistivity, intraclastic sandstone with medium-low density and medium-low resistivity, and felsic micrite dolomite with high density and medium-low resistivity. The target intervals of the mixed rock are divided according to the logging response characteristics, such as Figure 3 As shown, the target intervals of the mixed sedimentary rocks are 2272.4-2276.2m and 2277.4-2282.6m;

[0030] S2. According to the correlation analysis of the core measured data and the logging curve of the target layer of the mixed rock, the mineral content and porosity of the target layer of the mixed rock are closely correlated with the natural gamma (GR), density (DEN), and acoustic transit time (AC) logging indicators. Natural gamma (GR), density (DEN), and acoustic transit time (AC) are selected as the original data for calculating the mineral content and porosity, and sampling and editing are performed in a point-by-point sampling mode (generally 8 points / 1m);

[0031] S3, based on the regional marker layer, the values ​​of the natural gamma logging curve, density logging curve, and acoustic time difference logging curve selected in step S2 are standardized;

[0032] S3. Establish a multi-mineral logging interpretation model, using the optimal mathematical calculation method and object-oriented programming. Calculate the mineral composition and porosity through the volume model. The mineral composition includes the content of mudstone, sandstone and carbonate rock;

[0033] S4, based on the formation logging parameters is a comprehensive response of multiple minerals and fluids, the mineral components calculated in step S4 are used to perform theoretical natural gamma, density and acoustic theoretical logging curves (such as Figure 2 medium blue thin dashed line);

[0034] S5, such as Figure 2 As shown, the theoretical logging curve performed in step S4 is compared and analyzed with the measured logging curve to evaluate the error of the multi-mineral logging interpretation model, and the logging parameter value is adjusted according to the allowable error requirement to minimize the average deviation, thereby obtaining an optimized multi-mineral logging interpretation model, as shown in FIG. Figure 2 It can be seen that the forward synthetic curve ( Figure 2 The thin blue dashed line) and the measured curve ( Figure 2 The middle red thick solid line) is in good agreement, indicating that the optimized multi-mineral logging interpretation model and the calculation results are accurate and reliable;

[0035] S6. Use the optimized multi-mineral logging interpretation model to calculate the target mineral component content and porosity. Figure 3 As shown, the target layer section is 2272.4-2276.2m, with a thickness of 3.8m, a clay content of 20.2%, a sand content of 38.4%, a carbonate content of 40.4%, and a porosity of 3.7%. It is comprehensively interpreted as a dry layer (containing oil); the target layer section is 2277.4-2281.8m, with a thickness of 4.4m, a clay content of 21.6%, a sand content of 31.6%, a carbonate content of 42.6%, and a porosity of 2.6%. It is comprehensively interpreted as a dry layer (containing oil); the target layer section is 2281.8-2282.6m, with a thickness of 0.8m, a clay content of 36.8%, a sand content of 22.4%, a carbonate content of 41.7%, and a porosity of 8.8%. It is comprehensively interpreted as an oil layer.

[0036] The logging modeling method for transitional phase mixed sedimentary rocks provided in the embodiment of the present application uses the most optimized mathematical method to evaluate and adjust the established multi-mineral model, which can effectively break through the limitations of the fixed interpretation model, provide a reliable lithology model and skeleton parameters for logging parameter interpretation, give full play to the comprehensive effect of formation logging response on fluids and minerals, and minimize the calculation error of logging parameters.

[0037] The embodiments described above are part of the embodiments of the present application, rather than all of the embodiments. The detailed description of the embodiments of the present application is not intended to limit the scope of the present application for protection, but merely represents the selected embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present application.

Claims

1. A logging modeling method for transitional phase mixed sedimentary rocks, characterized in that: The following steps are involved: S1. Determine the logging response characteristics of various lithologies based on the logging curves and field data, and divide the target layer sections of the mixed rock based on the logging response characteristics; S2. According to the correlation analysis between the core measured data and the logging curve of the mixed rock target layer, the well logging index with close correlation is selected, and the selected well logging index is standardized; S3. Establish a multi-mineral logging interpretation model, use the optimal mathematical calculation method and object-oriented programming, and calculate the mineral composition and porosity through the volume model; S4, using the calculated mineral composition to perform a theoretical well logging curve; S5. Compare and analyze the theoretical logging curve with the measured logging curve, evaluate the error of the multi-mineral logging interpretation model, adjust the logging parameter value according to the allowable error requirement, minimize the average deviation, and obtain the optimized multi-mineral logging interpretation model; S6. Calculate the target mineral composition and porosity using the optimized multi-mineral logging interpretation model.

2. The well logging modeling method for transitional phase mixed rock according to claim 1, characterized in that: The logging curves include natural gamma curves, deep lateral curves, sonic curves, and density curves.

3. The well logging modeling method for transitional phase mixed rock according to claim 1, characterized in that: The field data include well logging, gas logging, and thin section analysis.

4. The well logging modeling method for transitional phase mixed rock according to claim 1, characterized in that: The logging indicators include natural gamma, density and acoustic time difference curves.

5. The well logging modeling method for transitional phase mixed rock according to claim 1, characterized in that: The logging index is sampled and edited by point-by-point sampling.

6. The well logging modeling method for transitional phase mixed rock according to claim 1, characterized in that: The mineral components include mudstone content, sandstone content, and carbonate rock content.

7. The well logging modeling method for transitional phase mixed rock according to claim 1, characterized in that: The logging response characteristics of the lithology include intraclastic limestone with medium-high density and high resistivity, intraclastic sandstone with medium-low density and medium-low resistivity, and felsic micrite dolomite with high density and medium-low resistivity.

8. The well logging modeling method for transitional phase mixed rock according to claim 1, characterized in that: The theoretical logging curve of mineral composition is calculated using the logging parameters based on the formation.

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