A quantitative prediction and evaluation method for reservoir sweet spots based on geochemical indicators and lithological structures

Abstract

The present invention provides a method for quantitative prediction and evaluation of reservoir sweet spots of geochemical indicators and lithologic structures, with the following specific steps: a. On the basis of sedimentary phase research, the differences in lithology and physical properties between different microphases are analyzed to obtain the reservoir quality coefficient; b. On the basis of analytical analysis and hydrocarbon source logging evaluation, the correlation analysis between TOC and reservoir lithology and thickness is carried out in combination with the lithologic thickness distribution of seismic attribute inversion; c. Considering factors such as structure, lithology, thickness, and faults, the degree of fracture development is established; d. According to the correlation between the three core evaluation factors and the output structural profile, the weight of each evaluation factor is determined by analogy and association, and then the superposition method of external and internal factors is adopted. The present invention is based on a comprehensive evaluation method for lacustrine sedimentary reservoirs combining favorable lithologic structures, superposition of external and internal factors, seismic and geology, and point-surface combination, and solves the problem of quantitative prediction and evaluation of sweet spots in the shell limestone reservoir of the Da'anzhai section of the Lower Jurassic in the Sichuan Basin.

Description

Technical Field

[0001] The invention belongs to the technical field of petroleum exploration, and in particular relates to a method for quantitatively predicting and evaluating reservoir sweet spots of geochemical indicators and lithological structures. Background Art

[0002] The Da'anzhai section in the eastern slope of the Sichuan Basin is divided into three subsections from bottom to top: Dasan, Daer, and Dayi. The rock porosity of each subsection is mostly less than 2%, and the permeability is mainly distributed in the range of 0.01 to 0.1×10 -3 μm 2 , which belongs to the ultra-low porosity and ultra-low permeability reservoir. Mercury injection analysis shows that the platform section of various rock samples is low, the throat is small, the displacement pressure is large, and the heterogeneity is strong. The wells tested so far have shown that fractures are the key to production in the context of tight ultra-low permeability reservoirs. Therefore, the degree of development of fractures is an important factor that needs to be considered in reservoir synthesis. Research has also shown that the degree of development of hydrocarbon sources also directly affects the quality of the reservoir. By comparing the reservoir lithology of the producing wells in the study area and the territory, it is believed that the sedimentary microfacies of the Da'anzhai section controls the distribution of favorable reservoir lithology, and the matching degree between fractures and favorable lithology combinations affects the formation of high-quality reservoirs.

[0003] For the ultra-low porosity and ultra-low permeability reservoirs in the Da'anzhai section of the study area, the existing single method cannot accurately evaluate the reservoir. The existing patent CN117078110A discloses a reservoir engineering sweet spot evaluation method based on the hierarchical analysis method. It uses comprehensive rock mineral structure, fracture development, rock mechanics and geostress characteristics, and selects brittleness index, fracture toughness, horizontal geostress difference coefficient and fracture development index as the main control parameters of the target reservoir engineering sweet spot quantitative evaluation model to evaluate the reservoir engineering sweet spot. However, this method mainly evaluates and analyzes well logging data and indoor cores, and is not suitable for quantitative prediction and evaluation of sweet spots in the shell limestone reservoir of the Da'anzhai section of the Lower Jurassic in the Sichuan Basin. Summary of the invention

[0004] The purpose of the present invention is to provide a method for quantitatively predicting and evaluating reservoir sweet spots of geochemical indicators and lithological structures, and the present invention solves the problem of quantitatively predicting and evaluating reservoir sweet spots of the shell limestone in the Da'anzhai section of the Lower Jurassic in the Sichuan Basin.

[0005] In order to achieve the above purpose, the technical scheme of this scheme is as follows: A quantitative prediction and evaluation method for reservoir sweet spots of geochemical indicators and lithological structures, comprising the following steps:

[0006] a. The lithologic combination and physical property characteristics in the research area were studied and classified to obtain basic lithologic characteristics; the favorable phase belt for high oil and gas production in the Dongpo area was obtained through lithologic analysis and comparative analysis with adjacent areas; the reservoir quality index derived from a large number of rock physics experiments was introduced by analyzing the differences in lithologic and physical properties between different microfacies; the product of the corresponding lithologic thickness of the sedimentary microfacies and the reservoir quality index RQI was defined as the quality phase factor;

[0007] b. TOC evaluation of different layers is carried out through analytical analysis and hydrocarbon source logging evaluation; the analysis in step a is based on the constraint relationship between TOC and the formation or different lithology thickness, and the TOC content of different layers in the study area is predicted in plane by combining the lithology thickness obtained by seismic attribute inversion;

[0008] c. Fracture development degree: Using factors such as structure, lithology, thickness, faults, etc., the relative density of fractures is established as one of the indicators for comprehensive reservoir evaluation research;

[0009] d. According to the correlation between the three core evaluation factors obtained in steps a, b, and c and the output structure profile, the weight of each evaluation factor is determined by analogy and correlation method, and the data of the three evaluation factors are normalized. The comprehensive reservoir evaluation is performed by superposition of external and internal factors according to the order of genesis of high-quality reservoirs;

[0010] e. Weaving a comprehensive reservoir evaluation map through step d. The evaluation coefficients in the evaluation map are all relative values. Since a trade-off is made in the value assignment process, comparisons are made between layers. Combined with the results of comprehensive reservoir evaluation, comprehensive evaluation standards for different types of reservoirs are established.

[0011] Furthermore, the reservoir quality index RQI in step a is expressed as follows:

[0012]

[0013] In formula (1): K is the permeability, μm 2 ; Φ e - is the effective porosity, %; F s - is the shape factor, dimensionless; τ- the curvature of the capillary tube, dimensionless; r- the radius of the capillary tube, μm;

[0014] Furthermore, the reservoir evaluation calculation formula in step d is:

[0015] CEI=a3*FR*(a1*CJ_RQI+a2*TOC) (Formula 2)

[0016] In formula (2), a1 represents the weight coefficient of the internal quality phase factor, a2 represents the TOC weight coefficient, a3 represents the fracture relative density weight coefficient, FR represents the fracture development degree, which is one of the indicators for comprehensive reservoir evaluation research, and CJ_RQI represents the reservoir quality phase factor.

[0017] Furthermore, the comprehensive evaluation standard for different types of reservoirs in step e is to divide the reservoirs into four categories according to the single well production profile and production capacity characteristics, namely, A high-quality reservoir, B sub-high-quality reservoir, C general reservoir and D poor reservoir; the reservoir sweet spot index QI of A high-quality reservoir is higher than 0.43; the reservoir sweet spot index QI of B sub-high-quality reservoir is between 0.28 and 0.43; the reservoir sweet spot index QI of C general reservoir is between 0.20 and 0.28; the reservoir sweet spot index QI of D poor reservoir is less than 0.20.

[0018] Beneficial effects:

[0019] The present invention proposes a quantitative evaluation method for the sweet spots of the shell limestone reservoir in the Da'anzhai section of the Lower Jurassic in the Sichuan Basin, establishes quantitative evaluation indicators and quantitative evaluation formulas, and carries out prediction and evaluation of the reservoir sweet spots in the Da'anzhai section of the Lower Jurassic based on actual drilling data in the Dongpo area of ​​the Western Sichuan Depression in the Sichuan Basin. The results are highly consistent with the actual drilling test results. The reservoir sweet spot prediction results obtained by applying the evaluation method provide reliable geological support for subsequent well site deployment adjustment and reserve and production increase in the study area. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 It is a flow chart of the reservoir sweet spot quantitative prediction and evaluation method provided by the present invention;

[0021] Figure 2 This is a relationship diagram between the thickness of a large section of the stratum and the TOC content in the study area provided by the embodiment of the present invention;

[0022] Figure 3 is a relationship diagram between the thickness of a large section of the stratum and the thickness of the limestone in the study area provided by an embodiment of the present invention;

[0023] Figure 4 is a graph showing the relationship between the thickness of the second section of limestone and the TOC content in the study area provided by the embodiment of the present invention;

[0024] Figure 5 is a relationship diagram between the thickness of the second limestone and the thickness of the shale in the study area provided by the embodiment of the present invention;

[0025] Figure 6 This is a graph showing the relationship between the thickness of the second and third limestone sections and TOC in the study area provided by the embodiment of the present invention;

[0026] Figure 7 is a relationship diagram between the thickness of the third section of the stratum and the thickness of the shale in the study area provided by the embodiment of the present invention;

[0027] Figure 8a It is a comprehensive evaluation map of the reservoir of the first section of the study area provided by the embodiment of the present invention;

[0028] Figure 8b It is a comprehensive evaluation map of the second section of the reservoir in the study area provided by the embodiment of the present invention;

[0029] Figure 8c It is a comprehensive evaluation map of the reservoir of the third section of the study area provided by the embodiment of the present invention;

[0030] Figure 9a It is a relationship diagram between daily gas production in the study area and the weighted sweet spot index provided by the present invention;

[0031] Figure 9b It is a relationship diagram between daily oil production in the study area and the weighted sweet spot index provided by the present invention;

[0032] Fig.9c It is a relationship diagram between the cumulative gas production in the study area and the weighted sweet spot index provided by the present invention;

[0033] Figure 9d It is a relationship diagram between the unimpeded flow rate of the study area and the weighted sweet spot index provided by the present invention;

[0034] Fig.9e It is a relationship diagram between the cumulative oil production in the study area and the weighted sweet spot index provided by the present invention. DETAILED DESCRIPTION

[0035] The technical solutions in the embodiments of the present invention are described clearly and completely below. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0036] The present invention provides a method for quantitatively predicting and evaluating geochemical indicators and reservoir sweet spots of favorable lithological structures. The present invention is described in detail below in conjunction with the accompanying drawings.

[0037] like Figure 1 As shown in the figure, firstly, by comparing with the adjacent areas, it is believed that the favorable phase belt for obtaining high oil and gas production in the study area is the low-energy shell beach, and the probability of high production in the high-energy shell beach is relatively low. The thin interbeds of mud shale and argillaceous shell limestone or argillaceous shell limestone in the low-energy shoal microfacies, and the black source rocks adjacent to the semi-deep lake-deep lake, have better tight-fracture type oil reservoir formation conditions than other microfacies, so the low-energy shoal microfacies is the most favorable sedimentary phase belt for tight oil exploration.

[0038] Step 1. Based on the sedimentary phase research, the differences in lithology and physical properties between different microphases were analyzed. Considering that the reservoir in the study area is relatively dense, the magnitude of porosity and permeability is large, and a single physical property parameter cannot reflect the reservoir quality characteristics of the reservoir. Therefore, the reservoir quality index (RQI) derived from a large number of rock physics experiments is introduced to characterize the quality differences of tight oil and gas reservoirs in the study area. The reservoir quality index (RQI) is derived from the Kozeny-Carman equation, where the classic permeability expression obtained by the rock electrical physics model is as follows:

[0039]

[0040] In formula (1): K is the permeability, unit is μm 2 ; Φ e is the effective porosity, unit: %; F s is the shape factor, dimensionless; τ is the curvature of the capillary, dimensionless; r is the radius of the capillary, in μm.

[0041] The reservoir quality index of different sedimentary microfacies in different layers can be calculated to characterize the quality difference between reservoirs. According to formula (1), Table 1 shows that the reservoir quality index of the low-energy shell beach in the first, second and third sections is relatively high, which are 0.6503, 0.2188 and 0.6992 respectively.

[0042] Table 1 Quality phase factor assignment basis table

[0043]

[0044] The present invention defines the product of the corresponding lithology thickness of the sedimentary microfacies and the reservoir quality index RQI as the quality phase factor (CJ_RQI). This parameter can reflect the reservoir and permeability quality under the control of sedimentary microfacies and is the most direct and reliable important evaluation index for reservoir evaluation.

[0045] Step 2: Through the analysis of Jinhua Oilfield, Langzhong area and Dongpo Da'anzhai, it is believed that the contact of source rocks has a certain control effect on reservoir development. Through the evaluation and analysis of hydrocarbon sources in the study area, it is believed that the favorable factors for the formation of Da'anzhai are: the coexistence of tight oil source and reservoir in the oil-rich depressions with oil accumulation that has not undergone large-scale long-distance migration in the tight sandstone and tight carbonate rocks interbedded with the source rock. In order to better use this indicator to carry out comprehensive reservoir evaluation, this time, based on the analysis of chemical analysis and hydrocarbon source logging evaluation, combined with the lithology thickness distribution of seismic attribute inversion, the correlation analysis of TOC with reservoir lithology and thickness was carried out. Organic carbon content (TOC) is an important indicator for quantitative evaluation of source rocks. The level of TOC directly affects the hydrocarbon generation potential of shale and the level of its adsorbed oil and gas content.

[0046] Figure 2The relationship between the TOC content of the shale in the first section and the thickness of the first section was statistically analyzed. There is an exponential relationship between the thickness of the first section and the TOC content. The thicker the formation, the higher the TOC content.

[0047] Figure 3 By establishing the relationship between the thickness of a large section of strata and the thickness of a large section of limestone, it can be seen that the greater the thickness of a large section of strata, the smaller the thickness of the limestone, and vice versa. This is also the main reason why the TOC content is positively correlated with the thickness of the strata in this section. Generally speaking, the thicker the shale, the higher the TOC content may be.

[0048] Figure 4 It is classified according to the limestone-to-shale ratio (ratio of limestone to shale) and limestone-to-ground ratio (ratio of limestone to stratum thickness) of the second section. TOC is functionally related to limestone thickness: when the limestone-to-shale ratio is less than 1 and the limestone-to-ground ratio is less than 0.5, the limestone thickness and TOC content are exponentially positively correlated; when the limestone-to-shale ratio is greater than 1 and the limestone-to-ground ratio is greater than 0.5, the limestone thickness and TOC content are linearly positively correlated.

[0049] Figure 5 The thickness of the shale in the upper part of the second member is positively correlated with the thickness of the limestone in a power exponential manner. The thicker the shale is, the thicker the limestone is, which reflects the geological characteristics of the interbedded shale and limestone in the second member.

[0050] Figure 6 It shows that the TOC content of the third section is exponentially positively correlated with the thickness of the limestone of the second and third sections. The greater the thickness of the second and third sections of limestone, the higher the TOC content.

[0051] Figure 7 The thickness of the limestone in the third and second sections is significantly positively correlated with the thickness of the mudstone in the upper part of the second section. This rule is similar to that in the second section. The third section is also a layer mainly characterized by interbedded mudstone and limestone.

[0052] Based on the constraint relationship between TOC and strata or different lithology thicknesses, the TOC content of different layers in the study area is predicted in plane by combining the lithology thickness obtained by seismic attribute inversion. The well points are corrected by the logging interpretation results, and the constraints outside the well points are extrapolated.

[0053] The extrapolation constraint relationship of TOC in each layer is as follows:

[0054] Large section: TOC = 0.0803*exp(0.073*large section formation thickness)R 2 =0.5079, where R represents the correlation degree of the fitting formula;

[0055] Thickness of the first section of limestone = 24.0558*exp(-0.019*thickness of the first section of stratum)R2 =0.2959;

[0056] The second section of the Dali Formation: ash-to-sheet ratio <1 and ash-to-ground ratio less than 0.5: TOC = 0.1172*exp(0.0987*the thickness of the second section of the Dali Formation)R 2 =0.5347;

[0057] Ash-to-sheet ratio>1 and ash-to-ground ratio greater than 0.5: TOC=0.0803*thickness of the second limestone section-0.5467R 2 =0.6744;

[0058] The thickness of the top shale of the second section = 4.27 * the thickness of the third section 0.4412R 2 =0.2472;

[0059] The third section: TOC = 0.1487*exp(0.1093*the second section + the third section limestone thickness)R 2 =0.4423;

[0060] The thickness of the top shale of the second section = 3.9028*the thickness of the second section + the thickness of the third section limestone 0.4762R 2 =0.0.2461;

[0061] Step 3: The fracture development degree mainly uses the fracture relative density of the Da'anzhai section of the Dongpo contiguous work area, which is established by considering factors such as structure, lithology, thickness, and faults, as one of the indicators for comprehensive reservoir evaluation research, the fracture development degree (FR).

[0062] Step 4: According to the correlation between the three core evaluation factors and the output structure profile, the weight of each evaluation factor is determined by analogy and association, and the data of the three evaluation factors are normalized. This comprehensive reservoir evaluation uses the superposition method of external and internal factors to evaluate the reservoir according to the order of high-quality reservoir genesis. The calculation formula is as follows:

[0063] CEI=a3*FR*(a1*CJ_RQI+a2*TOC) (Formula 2)

[0064] a1, a2, and a3 represent the weight coefficients of the internal quality phase factor, TOC, and fracture relative density, respectively; CJ_RQI represents the reservoir quality phase factor.

[0065] According to formula (2), a comprehensive reservoir evaluation map was compiled for the three sub-members of Da'anzhai in the Dongpo area. The evaluation coefficients in each evaluation map are relative values. Since a balance was made during the assignment process, the layers can be compared. Figure 8a , Figure 8b and Figure 8cThis is a comprehensive reservoir evaluation map of the Da'anzhai section in the Dongpo contiguous work area. The reservoir of the second section is relatively the best, the reservoir of the first section is relatively poor, and the third section is between the second and first sections.

[0066] According to the single well production profile and productivity characteristics, the reservoirs are divided into three categories: A high-quality reservoirs (yellow + red chromatographic area, reservoir sweet spot index QI higher than 0.43); B sub-high-quality reservoirs (green chromatographic area, reservoir sweet spot index QI between 0.28 and 0.43); C general reservoirs (cyan-blue chromatographic area, reservoir sweet spot index QI between 0.20 and 0.28); D poor reservoirs (cyan-purple chromatographic area, reservoir sweet spot index QI less than 0.20). Combined with the results of comprehensive reservoir evaluation, the comprehensive evaluation standards for different types of reservoirs in the Da'anzhai section of the East Slope Continuous Work Area in the Western Sichuan Depression were established, as shown in Table 2.

[0067] Table 2 Comprehensive evaluation criteria for different types of reservoirs in the Da'anzhai section of the eastern slope of the western Sichuan Depression

[0068]

[0069] In order to verify the above comprehensive reservoir evaluation results, the cumulative production and test production of Da'anzhai in the entire Dongpo area were statistically analyzed, and the reservoir sweet spot index (QI) of each sub-section single well was evaluated, and the correlation between QI and production was established. Since some wells were tested in multiple sections, the CEI value of the wells tested in multiple sections was taken as the weighted average of the perforation thickness of each sub-section (because the value of each sub-section was weighed when evaluating, the evaluation index value can be compared between layers). Figure 9a-9e The results show that the correlation between production and reservoir sweet spot indicators is significant, which confirms the accuracy of the comprehensive reservoir evaluation method and the reliability of the evaluation results.

[0070] Although the content of the present invention has been described in detail through the above preferred embodiments, it should be appreciated that the above description should not be considered as a limitation of the present invention. After reading the above content, it will be apparent to those skilled in the art that various modifications and substitutions of the present invention will occur. Therefore, the protection scope of the present invention should be limited by the appended claims.

Claims

1. A method for quantitative prediction and evaluation of reservoir sweet spots based on geochemical indicators and lithological structures, characterized in that: The following steps are involved: a. The lithologic combination and physical property characteristics in the research area were studied and classified to obtain basic lithologic characteristics; the favorable phase belt for high oil and gas production in the Dongpo area was obtained through lithologic analysis and comparative analysis with adjacent areas; the reservoir quality index derived from a large number of rock physics experiments was introduced by analyzing the differences in lithologic and physical properties between different microfacies; the product of the corresponding lithologic thickness of the sedimentary microfacies and the reservoir quality index RQI was defined as the quality phase factor; b. TOC evaluation of different layers is carried out through analytical analysis and hydrocarbon source logging evaluation; the analysis in step a is based on the constraint relationship between TOC and the formation or different lithology thickness, and the TOC content of different layers in the study area is predicted in plane by combining the lithology thickness obtained by seismic attribute inversion; c. Fracture development: Fracture relative density is established using structural, lithological, thickness and fault factors as one of the indicators for comprehensive reservoir evaluation research; d. According to the correlation between the three core evaluation factors obtained in steps a, b, and c and the output structure profile, the weight of each evaluation factor is determined by analogy and correlation method, and the data of the three evaluation factors are normalized. The comprehensive reservoir evaluation uses the superposition method of external and internal factors to evaluate the reservoir according to the order of high-quality reservoir genesis; the reservoir evaluation calculation formula is: ; In formula (2), a1 represents the weight coefficient of the internal quality phase factor, a2 represents the TOC weight coefficient, a3 represents the fracture relative density weight coefficient, FR represents the fracture development degree, one of the indicators of comprehensive reservoir evaluation research, CJ_RQI represents the reservoir quality phase factor, TOC organic carbon content; e. Weaving a comprehensive reservoir evaluation map through step d. The evaluation coefficients in the evaluation map are all relative values. Since a trade-off is made in the value assignment process, comparisons are made between layers. Combined with the results of comprehensive reservoir evaluation, comprehensive evaluation standards for different types of reservoirs are established.

2. The method for quantitative prediction and evaluation of reservoir sweet spots based on geochemical indicators and lithological structures according to claim 1, characterized in that: The reservoir quality index RQI in step a is expressed as follows: ; In formula (1): is the permeability, μm 2 ; is the effective porosity, %; is the shape factor, dimensionless; The curvature of the capillary tube, dimensionless; Capillary radius, μm.

3. The method for quantitative prediction and evaluation of reservoir sweet spots of geochemical indicators and lithological structures according to claim 1, characterized in that: The comprehensive evaluation standard for different types of reservoirs in step e is to divide the reservoirs into four categories according to the single well production profile and productivity characteristics, namely, A high-quality reservoir, B sub-high-quality reservoir, C general reservoir and D poor reservoir; the reservoir sweet spot index QI of A high-quality reservoir is higher than 0.43; the reservoir sweet spot index QI of B sub-high-quality reservoir is between 0.28 and 0.43; the reservoir sweet spot index QI of C general reservoir is between 0.20 and 0.28; the reservoir sweet spot index QI of D poor reservoir is less than 0.20.

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