Improved saturation model construction method based on variable rock electrical parameters

Abstract

The invention relates to an improved saturation model construction method based on variable rock electrical parameters, and belongs to the technical field of geological exploration. The method comprises the following specific steps: determining formation water resistivity; determining values a, b, m and n of the research area; establishing a relationship between the cementation index m and different types of porosity; establishing a relation between the conductive porosity and the effective porosity; establishing an improved cementation index m model, wherein a = 1; and calculating the saturation of the reservoir. The method aims at solving the problems that in the prior art, the cementation index m change range is too large, and saturation calculation is not accurate.

Description

Technical Field

[0001] This invention relates to an improved saturation model construction method based on variable rock electrical parameters, belonging to the field of geological exploration technology. Background Technology

[0002] Saturation assessment is the core of quantitative evaluation of oil and gas reservoirs. Improving the accuracy of reservoir water saturation calculation has always been a challenge in reservoir logging evaluation. The Archie formula is the foundation for quantitatively calculating oil saturation using logging data. Based on the Archie formula, a series of saturation calculation models have been developed, such as saturation models considering the influence of clay, saturation models considering the influence of the skeleton and multiple pores, and general saturation models based on network conductivity. In the prior art, Chinese invention patent application number 202111249858.8 discloses a method for establishing a saturation model for fractured-vuggy reservoirs based on pore type subdivision. This method includes the following steps: determining the pore type of the fractured-vuggy reservoir; performing saturation model analysis based on the pore type in the fractured-vuggy reservoir; establishing a saturation model for the fractured-vuggy reservoir; determining the saturation model parameters; and calculating the saturation based on the saturation model and saturation parameters. This technology enables the study of the conductivity mechanism of different types of pores in fractured-vuggy reservoirs.

[0003] In porous reservoirs without fractures or pores, the complexity of the pore structure makes it difficult to quantitatively calculate saturation using a fixed Archie parameter. Therefore, accurately establishing a high-precision calculation model for the Archie parameter is one method for quantitatively evaluating the saturation of complex porous reservoirs, especially establishing a high-precision calculation model for the cementation index (m). The physical meaning of the m value is to characterize the degree of cementation in the rock, and it is inextricably linked to the tortuosity of the pore size and the conductive path. Compared with the a, b, and n values ​​in the Archie parameter, the m value has a greater impact on saturation. Experimental data confirm that, for the stratigraphic factors and porosity data points of 53 rock samples in the study area, the m value is variable when a=1, ranging from 1.6 to 2.0. Figure 1 Although the methods for calculating the variable m-value meet the needs of practical research or production in different regions, they do not explain the relationship between the m-value and effective porosity mechanistically, nor do they provide an answer as to why the relationship between the m-value and effective porosity varies significantly in different regions. Summary of the Invention

[0004] This invention provides an improved saturation model construction method based on variable rock electrical parameters, which aims to solve the problem of inaccurate saturation calculation due to the large variation range of the cementation index m in the prior art.

[0005] To achieve the above objectives, this invention provides an improved saturation model construction method based on variable rock electrical parameters, specifically including:

[0006] S1, determine the formation water resistivity R w ;

[0007] S2, determine the values ​​of a, b, m, and n for the study area;

[0008] S3, establish the relationship between the cementation index m and different types of porosity;

[0009] S4, Establish conductive porosity φ f With effective porosity φ e relation;

[0010] S5, Establish an improved cementation index model m, where a = 1;

[0011] S6, calculate reservoir saturation S w .

[0012] Furthermore, S1 determines the formation water resistivity R. w Specifically, the formation water resistivity is determined using the oil testing and production water analysis data from the same layer in this well or adjacent wells.

[0013] Furthermore, S1 is based on the formation water equivalent NaCl solution total salinity R provided by the oil trial production water analysis data. wn The formation water resistivity R at 24℃ was calculated using formula (1). wn Then, the formation water resistivity R at any temperature T is calculated using formula (2). w Formulas (1) and (2) are as follows:

[0014]

[0015] Furthermore, the determination of the values ​​of a, b, m, and n in the study area by S2 is specifically achieved by combining the rock electrical test data of the study area and obtaining the values ​​of a, b, m, and n through the power relationship between formation factors and porosity, resistivity index and water saturation.

[0016] Furthermore, the different types of porosity in S3 include effective porosity, conductive porosity, and the difference between effective porosity and conductive porosity.

[0017] Furthermore, the establishment of the relationship between the cementation index m and different types of porosity in S3 specifically involves using rock electrical experimental data from rock samples in the study area to determine the effective porosity of each rock sample; according to Maxwell's conductivity equation, the relationship between formation factors and conductive porosity is given by formula (3). Substitute the rock electrical experimental data of the rock samples in the study area into formula (3) to calculate the conductive porosity of each rock sample; thereby establish the functional relationships between the m value and the effective porosity, the m value and the conductive porosity, and the m value and the difference between the effective porosity and the conductive porosity.

[0018] Furthermore, in step S3, after establishing the functional relationships between the m value and effective porosity, the m value and conductive porosity, and the m value and the difference between effective porosity and conductive porosity, the correlation between the cementing index m and different types of porosity is compared to determine the strongest correlation relationship, thereby establishing a model formula for the cementing index m.

[0019] Furthermore, S4 establishes conductive porosity φ f With effective porosity φ e Specifically, the relationship between formation factors and electrical porosity is mathematically transformed as shown in formula (5):

[0020]

[0021] In formula (5) x is the pore geometry parameter; and substitute it into formula (5) to... Formula (6) is obtained:

[0022]

[0023] Furthermore, in step S5, an improved cementation index m model is established, wherein setting a = 1 is specifically based on the rock electrical experimental data of the study area. The relationship between conductive porosity and effective porosity is established through Excel to obtain a formula expression, and this formula expression is substituted into the model formula of cementation index m to obtain the improved cementation index m model.

[0024] Furthermore, S6 specifically involves calculating the reservoir saturation by substituting the improved cementation index m into the model. Thus, the reservoir saturation S is obtained. w .

[0025] This invention discloses an improved saturation model construction method based on variable rock electrical parameters. Its beneficial effect is that it derives a general expression between the m-value and effective porosity from Maxwell's conductivity equation, and then establishes a high-precision improved cementation index m-value model, which greatly improves the calculation accuracy of saturation in sandstone and conglomerate reservoirs. Compared with the saturation calculated by Archie model formula, the saturation calculation accuracy of this invention is significantly improved. Attached Figure Description

[0026] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0027] Figure 1 This is a schematic diagram illustrating the influence range of the cementation index m on the relationship between formation factors and porosity in Embodiment 1 of the present invention;

[0028] Figure 2 This is a schematic diagram of the process of Embodiment 1 of the present invention;

[0029] Figure 3 This is a schematic diagram illustrating the relationship between stratigraphic factors of the Denglouku Formation in a certain region and porosity, resistivity index and water saturation in Embodiment 1 of the present invention.

[0030] Figure 4 This is a schematic diagram showing the relationship between stratigraphic factors of the Yingcheng Formation in a certain region and porosity, resistivity index and water saturation in Embodiment 1 of the present invention;

[0031] Figure 5 This is a schematic diagram of the pore space in a certain region in Embodiment 1 of the present invention;

[0032] Figure 6 This is a schematic diagram showing the relationship between the bonding index m and the conductive porosity and effective porosity in Embodiment 1 of the present invention;

[0033] Figure 7 This is a schematic diagram of the cementation index m model for a certain region in Embodiment 1 of the present invention;

[0034] Figure 8 This is a schematic diagram illustrating the relationship between conductive porosity and effective porosity in a certain region in Embodiment 1 of the present invention;

[0035] Figure 9 This is a schematic diagram illustrating the relationship between conductive porosity and effective porosity established using Excel in Embodiment 1 of the present invention.

[0036] Figure 10 This is a schematic diagram comparing the reservoir saturation of Embodiment 1 of the present invention with that of the Archie Classical Model. Detailed Implementation

[0037] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The following description of at least one exemplary embodiment is merely illustrative and is in no way intended to limit the present invention or its application or use. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0038] To further understand the invention, the technical solution will be further described below in conjunction with specific embodiments.

[0039] Example 1: This example uses a project in a certain region as an example. Figure 1 The experimental data shown confirms that, for the stratigraphic factors and porosity data points of the 53 rock samples in the study area, the value of m is variable when a = 1, ranging from 1.6 to 2.0. Figures 1-10 As shown, this embodiment provides an improved saturation model construction method based on variable rock electrical parameters, specifically including: S1, determining the formation water resistivity R. w S1 determines the formation water resistivity R. w Specifically, the formation water resistivity is determined using production water analysis data from the same formation in this well or adjacent wells. That is, S1 is based on the formation water equivalent NaCl solution total salinity P provided by the production water analysis data. wn The formation water resistivity R at 24℃ was calculated using formula (1). wn Then, the formation water resistivity R at any temperature T is calculated using formula (2). w Formulas (1) and (2) are as follows:

[0040]

[0041] This embodiment collected and organized water analysis data from 9 wells in 7 locations in a certain region, and selected the Yingcheng Formation and Denglouku Formation as representative water analysis data to calculate the formation water resistivity at formation temperature. The formation water resistivity R of the Denglouku Formation is shown in the figure. w The resistivity of the water in the Yingcheng Formation is 0.25 Ω·m. w It is 0.37 Ω·m.

[0042] S2, determine the values ​​of a, b, m, and n for the study area; based on the rock electrical test data of 53 rock samples in the study area, and considering the different lithologies of the Denglouku Formation and Yingcheng Formation within the study area, establish the relationship between stratigraphic factor F and porosity. Resistivity index I and water saturation S wThe power relation, such as Figure 3 and Figure 4 As shown, the corresponding lithology-related coefficients a, b, cementation index m, and saturation index n were obtained. The value of m needs to be recalculated based on S3 to S7, and a = 1 is set.

[0043] S3, establish the relationship between the cementation index m and different types of porosity; such as Figure 5 In the figure shown, C represents a connected pore space, T represents a semi-closed pore space, and S represents a fully closed pore space. C and T participate in the flow of current in the pore space, corresponding to the conductive porosity of the connected pore space, while S does not participate in the flow of current in the pore space, corresponding to the non-conductive porosity. Using the rock electrical experimental data of rock samples in the study area, the effective porosity of each rock sample was calculated; according to Maxwell's conductivity equation, the relationship between formation factors and conductive porosity is given by formula (3). Substitute the rock electrical experimental data of the rock samples in the study area into formula (3) to calculate the electrical conductivity porosity of each rock sample; for example Figure 6 As shown, the differences (φ) between the m value and effective porosity, the m value and conductive porosity, and the m value and both effective porosity and conductive porosity are established respectively. e -φ f The functional relationship between ).

[0044] Subsequently, the correlation between the cementation index *m* and different types of porosity was compared. The strongest correlation was found to be between the *m* value and the difference between effective porosity and conductive porosity. Based on this, a model for the cementation index *m* in a certain region was established, such as... Figure 7 As shown, the model formula (4) for the cementation index m is established:

[0045]

[0046] S4, Establish conductive porosity φ f With effective porosity φ e Relationship: Specifically, S4 involves a mathematical transformation of the relationship between formation factors and conductive porosity, as shown in formula (5):

[0047] In formula (5) x is the pore geometry parameter; and substitute it into formula (5) to... Formula (6) is obtained:

[0048]

[0049] As can be seen from formula (6), the functional relationship between conductive porosity and effective porosity is not a simple linear or power function, such as... Figure 8 When the value of a is 1, the value of G is 2, and the values ​​of m are 1.5, 2.0, and 2.5 respectively, the functional relationship between conductive porosity and effective porosity gradually changes from linear to exponential. When the value of a is 1, the value of m is 2, and the values ​​of G are 1.0, 2.0, and 3.5 respectively, the functional relationship between conductive porosity and effective porosity gradually changes from exponential to linear. Therefore, the optimal functional form between conductive porosity and effective porosity varies depending on the values ​​of G and m, exhibiting diversity.

[0050] S5, establish an improved cementation index model m, where a = 1; based on the rock electrical experimental data of the study area, and based on the above understanding, as follows... Figure 9 The relationship between conductive porosity and effective porosity was established using Excel to obtain the formula expression (7). This formula expression was then substituted into the model formula (4) of the cementation index m to obtain the model formula (8) of the improved cementation index m.

[0051]

[0052] S6, calculate reservoir saturation S w Substituting the model of the improved cementation index m into Archie's formula In the given formation resistivity R t Effective porosity φ e and b, n values, formation water resistivity value R w Thus, the reservoir saturation S is obtained. w .

[0053] like Figure 10 As shown in the figure, the reservoir saturation of the present invention is compared with that of the Archie model. It can be seen from the figure that, compared with layers 55 and 56, layers 53 and 54 in a certain well in a certain area show obvious water-bearing characteristics in the three-porosity curves of layers 55 and 56. The gas detection anomalies of layers 55 and 56 are also significantly worse than those of layers 53 and 54. The gas saturation calculated by the Archie model for layers 55 and 56 is similar to that of layers 53 and 54. The gas saturation calculated by the embodiment of the present invention for layers 53 and 54 is significantly higher than that for layers 55 and 56. Moreover, the gas test of layers 53 and 54 shows that they are gas layers. Therefore, the present invention has better applicability in this study area.

[0054] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for constructing an improved saturation model based on variable rock electrical parameters, characterized in that, S1, determine the formation water resistivity R w ; S2, determine the lithology coefficient a, the lithology constant b, the cementation index m, and the saturation index n related to the lithology of the study area; S3, establish the relationship between the cementation index m and different types of porosity; S4, Establish conductive porosity φ f With effective porosity φ e relation; S5, Establish an improved cementation index model m, where a = 1; S6, calculate reservoir saturation S w .

2. The improved saturation model construction method based on variable rock electrical parameters according to claim 1, characterized in that, S1 determines the formation water resistivity R w Specifically, the formation water resistivity is determined using the oil testing and production water analysis data from the same layer in this well or adjacent wells.

3. The improved saturation model construction method based on variable rock electrical parameters according to claim 2, characterized in that, S1 is based on the formation water equivalent NaCl solution total salinity P provided by the oil trial production water analysis data. wn The formation water resistivity R at 24℃ was calculated using formula (1). wn Then, the formation water resistivity R at any temperature T is calculated using formula (2). w Formulas (1) and (2) are as follows:

4. The improved saturation model construction method based on variable rock electrical parameters according to claim 1, characterized in that, S2 determines the lithology coefficient a, the lithology constant b, the cementation index m, and the saturation index n related to the lithology of the study area. Specifically, by combining the rock electrical test data of the study area, the values ​​of a, b, m, and n are obtained through the power relationship between formation factors and porosity, and between resistivity index and water saturation.

5. The improved saturation model construction method based on variable rock electrical parameters according to claim 1, characterized in that, The different types of porosity in S3 include effective porosity, conductive porosity, and the difference between effective porosity and conductive porosity.

6. The improved saturation model construction method based on variable rock electrical parameters according to claim 5, characterized in that, S3 establishes the relationship between the cementation index m and different types of porosity by using rock electrical experimental data of rock samples from the study area to calculate the effective porosity of each rock sample; according to Maxwell's conductivity equation, the relationship between formation factors and conductive porosity is given by formula (3). Substitute the rock electrical experimental data of the rock samples in the study area into formula (3) to calculate the electrical porosity of each rock sample. Therefore, functional relationships were established between the m value and the effective porosity, the m value and the conductive porosity, and the m value and the difference between the effective porosity and the conductive porosity.

7. The improved saturation model construction method based on variable rock electrical parameters according to claim 6, characterized in that, S3 establishes the functional relationships between the m value and effective porosity, the m value and conductive porosity, and the m value and the difference between effective porosity and conductive porosity, respectively. It also compares the correlation between the cementation index m and different types of porosity, determines the strongest correlation, and establishes the model formula for the cementation index m.

8. The improved saturation model construction method based on variable rock electrical parameters according to claim 7, characterized in that, S4 establishes conductive porosity φ f With effective porosity φ e Specifically, the relationship between formation factors and electrical porosity is mathematically transformed as shown in formula (5): In formula (5) x is the pore geometry parameter; and substitute it into formula (5) to... Formula (6) is obtained:

9. The improved saturation model construction method based on variable rock electrical parameters according to claim 1, characterized in that, S5 establishes a model for an improved cementation index m, where a = 1 is specifically based on rock electrical experimental data from the study area. The relationship between conductive porosity and effective porosity is established using Excel, and this formula expression is substituted into the model formula for cementation index m to obtain the model for the improved cementation index m.

10. A method for constructing an improved saturation model based on variable rock electrical parameters according to claim 1 or 9, characterized in that, S6 calculates reservoir saturation by substituting the improved cementation index m into the model. Thus, the reservoir saturation S is obtained. w .

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