Method for establishing effectiveness evaluation of tight oil reservoir based on rock physical facies

Abstract

The invention discloses a tight oil reservoir effectiveness evaluation establishment method based on a rock physical facies. The method comprises the following steps: S1, determining the rock physical facies of a tight reservoir; s2, calculating reservoir evaluation parameters; s3, quantitatively describing a reservoir pore structure; the method is suitable for the technical field of oil exploration, the diversity, heterogeneity and pore structure of lithology are comprehensively considered, various experimental data are combined, and the effective reservoir of the tight oil reservoir based on the rock physical facies is established. And accurate evaluation is carried out based on different rock physics relative compact oil reservoirs. Not only can the well logging evaluation interpretation precision of the heterogeneous reservoir be improved, but also the pore structure of the reservoir can be quantitatively described through conventional well logging data and experimental data. Besides, the relation between the rock physical phase and the pore structure can be established on the basis of core analysis and oil test and production test data analysis, and effective reservoir evaluation of the tight oil reservoir can be more accurately carried out.

Description

Technical Field

[0001] The present invention belongs to the technical field of oil exploration, and specifically relates to a method for establishing an evaluation of the effectiveness of tight reservoir based on petrophysical facies. Background Art

[0002] A tight reservoir refers to a reservoir with an original formation permeability less than or equal to 0.1×10 -3 μm 2 . There are significant differences between tight reservoir and conventional reservoir in terms of sedimentary background and environment, diagenetic evolution, pore type, pore throat structure, pore connectivity, reservoir property, etc. Due to the tightness of tight reservoir and poor physical properties, it belongs to a low-porosity and low-permeability reservoir, and it is difficult to evaluate the effectiveness of the reservoir using conventional logging data.

[0003] The main manifestations are as follows: First, the lithology is diverse and the parent rock composition is complex, which brings difficulties to reservoir division and identification of reservoir effectiveness, and it is difficult to establish an evaluation standard for tight reservoir effectiveness; Second, in tight reservoir, the rock maturity is low, the sorting is poor, the pore structure is complex, and the rock composition is diverse, which affects the accuracy of reservoir parameter determination. The conventional reservoir parameter calculation model is no longer applicable to the calculation of tight reservoir parameters; Third, the pore structure is complex and the heterogeneity is strong, resulting in a complex relationship among the four properties of tight reservoir, and it is difficult to describe and divide the pore structure. In view of the technical bottleneck of tight reservoir effectiveness evaluation technology, it is urgent to conduct special research on tight reservoir, maximize the use of conventional logging data, and establish an evaluation method for tight reservoir effectiveness.

[0004] Currently, the conventional reservoir logging evaluation method uses a single logging curve to calculate reservoir parameters and divide the reservoir based on a single model according to lithology. However, due to the influence of formation compaction, cementation and other effects, the pore structure of tight reservoir is relatively complex. If other influencing factors are not considered, using a single model to calculate reservoir parameters will result in low calculation accuracy.

[0005] At the same time, due to the influence of pore structure, there are also differences in the properties of the same lithology in tight reservoir. Modeling according to lithology will reduce the accuracy of the model. A single logging curve cannot accurately and comprehensively reflect the formation information. Therefore, it is difficult to accurately establish an evaluation standard for tight reservoir effectiveness using single-parameter information data. Summary of the Invention

[0006] The purpose of the present invention is to overcome the defects of the prior art and provide a method for establishing an evaluation of the effectiveness of tight reservoir based on petrophysical facies.

[0007] To achieve the above purpose, the present invention adopts the following technical solutions:

[0008] A method for establishing an evaluation of the effectiveness of tight reservoir based on petrophysical facies, comprising the following steps:

[0009] S1 Use logging, well logging, core sampling, and geological data, based on the multi-parameter fusion non-linear processing method, combined with well logging relative comparison analysis, to determine the petrophysical facies of tight reservoirs;

[0010] S2 Use well logging, core sampling, and geological data to classify and model the reservoir parameters of tight oil reservoirs according to petrophysical facies, and calculate reservoir evaluation parameters;

[0011] S3 Use data such as cast thin sections and scanning electron microscopes to qualitatively describe the pore structure of tight reservoirs and classify types, and quantitatively describe the pore structure of reservoirs in combination with data such as well logging and core laboratory analysis;

[0012] S4 Organize and draw the comprehensive result map based on the data obtained in the above steps S2 - S3, and establish an effective reservoir evaluation method for tight oil reservoirs based on petrophysical facies in combination with the data processing results.

[0013] Preferably, in the step S1, it specifically includes:

[0014] Based on the multi-parameter fusion non-linear processing method, establish the corresponding relationship between well logging facies and petrophysical facies.

[0015] Preferably, in the step S1, it specifically includes:

[0016] Examine the correlation between various petrophysical facies and well logging curves, and select four well logging curves of neutron porosity, acoustic travel time, spontaneous potential, and resistivity to divide petrophysical facies;

[0017] Apply the principal component analysis method to extract two principal components from the four well logging curves, establish a petrophysical facies cross-plot analysis diagram, divide lithofacies, and the calculation method is as follows:

[0018] PC 1 = 0.567CNL + 0.572AC + 0.414SP - 0.423RT (1);

[0019] PC 2 = -0.01CNL + 0.006AC + 0.719SP + 0.695RT (2);

[0020] Among them, CNL - neutron logging value, AC - acoustic logging value, SP - spontaneous potential logging value, RT - resistivity logging value.

[0021] Preferably, in the step S2, the reservoir evaluation parameters are shale content, porosity, permeability, and saturation.

[0022] Preferably, in the step S2, calculating the reservoir evaluation parameters includes:

[0023] Calculation of shale content: Two methods, spontaneous potential and resistivity, are selected to calculate the shale content, and the minimum value is taken as the final result. The calculation formula is as follows:

[0024]

[0025]

[0026] In Formulas (3) and (4): SHLG - Logging curve value; GMAX, GMIN - Logging values of pure shale and pure bottom layer; SH - Relative value of logging curve; GCUR - Empirical coefficient, 3.7 for Tertiary strata and 2 for old strata; V sh - Shale content.

[0027] Preferably, in step S2, when calculating reservoir evaluation parameters, it further includes:

[0028] Calculation of porosity: According to different petrophysical facies, the density porosity formula is used to calculate porosity. The calculation formula is as follows:

[0029]

[0030] In Formula (5): ρ b 、ρ ma 、ρ f 、ρ sh — Density logging value, rock density skeleton value, fluid density value and shale density value respectively; V sh — Shale content.

[0031] Preferably, in step S2, when calculating reservoir evaluation parameters, it further includes: Calculation of permeability: According to different petrophysical facies, regression analysis is used to establish the statistical relationship between porosity and logging values of permeability respectively, and the formula for calculating permeability using porosity is determined.

[0032] Preferably, in step S2, when calculating reservoir evaluation parameters, it further includes: Calculation of saturation: Archie's formula is selected to calculate water saturation:

[0033]

[0034] In Formula (6): S w — Water saturation; a - Proportional coefficient related to lithology; b - Constant related to lithology; m - Cementation index of rock; n - Saturation index; R w — Resistivity of formation water; R t — Resistivity of hydrocarbon-bearing pure rock.

[0035] Preferably, in step S2, a, b, m, and n are obtained based on the relationships between formation factors, porosity, water saturation, and resistivity increase factor I; the formation water resistivity is determined using the spontaneous potential method and water ion analysis data.

[0036] Preferably, in step S3, the reservoir pore structure includes pore types, throat types, and pore structure characteristics and classifications.

[0037] Preferably, in step S3, the reservoir pore structure evaluation method includes:

[0038] Based on the analysis of experimental data such as cast thin sections and scanning electron microscopes, the pore types of tight reservoirs are divided into primary intergranular pores, dissolved intergranular pores, dissolved intragranular pores, moldic pores, and fractures;

[0039] Among them, primary intergranular pores refer to the pore spaces formed during diagenesis without secondary modification; dissolved intergranular pores refer to the pore spaces formed by the dissolution of cement between grains; intragranular pores refer to primary intragranular pores, which are the pore spaces inside the grains; dissolved intragranular pores refer to the pore spaces formed by the dissolution of unstable components such as feldspar and quartz or the dissolution of the cement-filled intragranular pores; moldic pores refer to a type of pore space where unstable components are completely dissolved under strong dissolution, with a diameter greater than 0.2 mm; fractures refer to the pore spaces generated by rock fracture, which can improve the reservoir seepage capacity, and the pore space may become smaller due to the filling of later fissures.

[0040] Preferably, in step S3, the reservoir pore structure evaluation method includes:

[0041] According to the origin and morphological characteristics, it can be divided into 5 types: pore constriction throat, necking throat, sheet throat, curved sheet throat, and bundle throat;

[0042] Among them, the necking throat is the channel formed when the space between primary intergranular pores is blocked by cement, etc. Its characteristics are large pores and small throats, and the grains are mostly point-contact cemented, with relatively high porosity and low permeability; the sheet throat refers to the throat presenting a curved sheet shape due to strong compaction, with small pores, thin throats, and the grains are mostly inlaid contact.

[0043] Preferably, in step S3, the reservoir pore structure evaluation method further includes:

[0044] Based on the capillary pressure curve, combined with characteristics such as mercury injection typing curve and pore throat radius distribution, the reservoir pore structure is divided.

[0045] Preferably, in step S4, establishing an effective reservoir evaluation method for tight oil reservoirs based on rock physics facies includes:

[0046] Based on the analysis of well testing and production data, combined with conventional logging, experimental analysis, and qualitative and quantitative interpretation results, considering the mutual influencing factors among various evaluation indicators, an evaluation standard for the effectiveness of tight reservoir is established.

[0047] Preferably, in step S4, an evaluation method for effective reservoirs in tight oil reservoirs based on petrophysical facies is established, including:

[0048] Based on the classification and evaluation of petrophysical facies and pore structure, combined with the fine analysis of the relationship between petrophysical facies and pore structure using well testing and production data, the effectiveness of reservoir in the demonstration area is comprehensively evaluated based on the classification and evaluation criteria of petrophysical facies and pore structure.

[0049] In summary, due to the adoption of the above technical solutions, the beneficial effects of the present invention are:

[0050] In the present invention, considering the diversity, heterogeneity, and pore structure of lithology, combined with various experimental data, the tight reservoir is accurately evaluated based on different petrophysical facies. It can not only improve the logging evaluation and interpretation accuracy of heterogeneous reservoirs, but also quantitatively describe the pore structure of reservoirs through conventional logging data and experimental data. In addition, based on core analysis and well testing and production data analysis, the present invention can establish the relationship between petrophysical facies and pore structure, which is helpful for more accurate evaluation of effective reservoirs in tight oil reservoirs. Description of the Drawings

[0051] Figure 1 is the flow chart of the evaluation of effective reservoirs in tight oil reservoirs of the present invention;

[0052] Figure 2 The petrophysical facies map determined by the principal component analysis method in the embodiment of the present invention;

[0053] Figure 3 is the evaluation result map of the effectiveness of reservoir pore structure in the embodiment of the present invention;

[0054] Figure 4 is the comprehensive evaluation result map of the effectiveness of reservoir in the embodiment of the present invention. Detailed Embodiments

[0055] The following further describes the detailed embodiments of the method for establishing the evaluation of the effectiveness of tight reservoir based on petrophysical facies of the present invention in conjunction with the attached Figures 1-4 , etc. The method for establishing the evaluation of the effectiveness of tight reservoir based on petrophysical facies of the present invention is not limited to the description of the following embodiments.

[0056] Example 1:

[0057] The method for establishing the evaluation of the effectiveness of tight reservoir based on petrophysical facies, as Figures 1-4 shown, includes the following steps:

[0058] S1 Use logging, well logging, core sampling, and geological data. Based on the multi-parameter fusion non-linear processing method, combined with well logging relative comparison analysis, determine the petrophysical facies of tight reservoirs.

[0059] S2 Use well logging, core sampling, and geological data to classify and model the reservoir parameters of tight oil reservoirs according to petrophysical facies, and calculate reservoir evaluation parameters.

[0060] S3 Use data such as cast thin sections and scanning electron microscopes to qualitatively describe the pore structure of tight reservoirs and classify types, and quantitatively describe the pore structure of reservoirs in combination with data such as well logging and core laboratory analysis.

[0061] S4 Collate and draw the comprehensive result map based on the data obtained in the above steps S2 - S3, and establish an effective reservoir evaluation method for tight oil reservoirs based on petrophysical facies in combination with the data processing results.

[0062] Further, in step S1, it specifically includes:

[0063] Based on the multi-parameter fusion non-linear processing method, establish the correspondence between well logging facies and petrophysical facies.

[0064] Further, in step S1, it specifically includes:

[0065] Examine the correlation between various petrophysical facies and well logging curves, and select four well logging curves of neutron porosity, acoustic time difference, spontaneous potential, and resistivity to divide petrophysical facies.

[0066] Apply the principal component analysis method to extract two principal components from the four well logging curves, establish a petrophysical facies crossplot analysis diagram, divide lithofacies, and the calculation method is as follows:

[0067] PC 1 = 0.567CNL + 0.572AC + 0.414SP - 0.423RT (1);

[0068] PC 2 = -0.01CNL + 0.006AC + 0.719SP + 0.695RT (2);

[0069] Where, CNL - neutron logging value, AC - acoustic logging value, SP - spontaneous potential logging value, RT - resistivity logging value.

[0070] Further, in step S2, the reservoir evaluation parameters are shale content, porosity, permeability, and saturation.

[0071] Further, in step S2, calculating the reservoir evaluation parameters includes:

[0072] Calculation of shale content: Two methods, spontaneous potential and resistivity, are selected to calculate the shale content, and the minimum value is taken as the final result. The calculation formula is as follows:

[0073]

[0074]

[0075] In Formulas (3) and (4): SHLG - logging curve value; GMAX, GMIN - logging values of pure shale and pure bottom formation; SH - relative value of logging curve; GCUR - empirical coefficient, which is 3.7 for Tertiary formation and 2 for old formation; V sh - shale content.

[0076] Furthermore, in step S2, when calculating reservoir evaluation parameters, it also includes:

[0077] Calculation of porosity: According to different rock physical phases, the density porosity formula is used to calculate porosity. The calculation formula is as follows:

[0078]

[0079] In Formula (5): ρ b 、ρ ma 、ρ f 、ρ sh — density logging value, rock density skeleton value, fluid density value and shale density value respectively; V sh — shale content.

[0080] Furthermore, in step S2, when calculating reservoir evaluation parameters, it also includes: Calculation of permeability: According to different rock physical phases, regression analysis is used to establish the statistical relationship between the logging values of porosity and permeability respectively, and the formula for calculating permeability using porosity is determined.

[0081] Furthermore, in step S2, when calculating reservoir evaluation parameters, it also includes: Calculation of saturation: Archie's formula is selected to calculate water saturation:

[0082]

[0083] In Formula (6): S w — water saturation; a - proportional coefficient related to lithology; b - constant related to lithology; m - cementation index of rock; n - saturation index; R w — formation water resistivity; R t — resistivity of hydrocarbon-bearing pure rock.

[0084] Further, in step S2, a, b, m, and n are obtained based on the relationships between formation factors and porosity, water saturation, and resistivity increase factor I; the formation water resistivity is determined using the natural potential method and water ion analysis data.

[0085] Further, in step S3, the reservoir pore structure includes pore types, throat types, and pore structure characteristics and classifications.

[0086] Further, in step S3, the reservoir pore structure evaluation methods include:

[0087] Based on the analysis of experimental data such as cast thin sections and scanning electron microscopes, the pore types of tight reservoirs are divided into primary intergranular pores, dissolved intergranular pores, dissolved intragranular pores, moldic pores, and fractures;

[0088] Among them, primary intergranular pores refer to the pore spaces formed during diagenesis without secondary modification; dissolved intergranular pores refer to the pore spaces formed by the dissolution of the cement between grains; intragranular pores refer to the primary intragranular pores, which are the pore spaces inside the grains; dissolved intragranular pores refer to the pore spaces formed by the dissolution of unstable components such as feldspar and quartz or the dissolution of the pore spaces filled with cement in the intragranular pores; moldic pores refer to a type of pore space where unstable components are completely dissolved under strong dissolution, leaving only the outer shape, with a diameter greater than 0.2 mm; fractures refer to the pore spaces generated by rock fracture, which can improve the reservoir seepage capacity, and the pore spaces may become smaller due to the filling of later fissures.

[0089] Further, in step S3, the reservoir pore structure evaluation methods include:

[0090] According to the origin and morphological characteristics, it can be divided into 5 types: pore constricted throat, necked throat, sheet throat, curved sheet throat, and bundle throat;

[0091] Among them, the necked throat is the channel formed when the space between primary intergranular pores is blocked by cement, etc. Its characteristics are large pores and narrow throats, and the grains are mostly point-contact cemented, with high porosity and low permeability; the sheet throat refers to the throat showing a curved sheet shape due to strong compaction, with small pores, narrow throats, and the grains are mostly inlaid contact.

[0092] Further, in step S3, the reservoir pore structure evaluation methods also include:

[0093] Based on the capillary pressure curve, combined with characteristics such as mercury injection typing curves and pore throat radius distributions, the reservoir pore structure is divided.

[0094] Further, in step S4, an effective reservoir evaluation method for tight oil reservoirs based on rock physics facies is established, including:

[0095] Based on the analysis of well testing and production data, combined with conventional logging, experimental analysis, and qualitative and quantitative interpretation results, considering the mutual influencing factors among various evaluation indicators, an evaluation standard for the effectiveness of tight reservoir is established.

[0096] Furthermore, in step S4, an evaluation method for effective reservoirs in tight oil reservoirs based on petrophysical facies is established, including:

[0097] Based on the classification and evaluation of petrophysical facies and pore structure, combined with the fine analysis of the relationship between petrophysical facies and pore structure using well testing and production data, the effectiveness of the reservoir in the demonstration area is comprehensively evaluated based on the classification and evaluation criteria of petrophysical facies and pore structure.

[0098] Example 2:

[0099] A method for establishing an evaluation of the effectiveness of tight reservoir based on petrophysical facies, as Figures 1-4 shown, includes the following steps:

[0100] (1) Using data such as logging, well logging, core sampling, and geology, based on the multi-parameter fusion non-linear processing method, combined with well logging relative ratio analysis, determine the petrophysical facies of the tight reservoir rock.

[0101] In this step, the operation process is to select the well logging curves sensitive to the division of petrophysical facies and perform preprocessing, automatic layering, and normalization of well logging data, then obtain the characteristic parameters of each layer through principal component analysis, formulas (1) and (2). Apply cluster analysis to divide well logging facies and establish the corresponding relationship between well logging facies and petrophysical facies. Finally, obtain the discriminant formula according to the Bayesian stepwise discriminant method, and then the continuous petrophysical facies profile of the target interval can be obtained. On the basis of dividing the petrophysical facies, reservoir parameter modeling is carried out, so as to effectively weaken the influence of reservoir heterogeneity.

[0102] (2) Using data such as well logging, core sampling, and geology, classify and model the reservoir parameters of the tight oil reservoir according to petrophysical facies, and calculate the reservoir evaluation parameters.

[0103] The key objects to be explained in this step are the shale content, porosity, permeability, and saturation parameters of the tight oil reservoir.

[0104] The specific explanation and calculation methods are as follows:

[0105] ① Shale content calculation

[0106] Select two methods of spontaneous potential and resistivity to calculate the shale content, and take the minimum value as the final result.

[0107]

[0108]

[0109] In formulas (1) and (2): SHLG - logging curve value; GMAX, GMIN - logging values of pure shale and pure formation; SH - relative value of the logging curve; GCUR - empirical coefficient, 3.7 for Tertiary formations and 2 for old formations; V sh — shale content.

[0110] ② Porosity calculation

[0111] According to different petrophysical facies, select different rock density matrix values and calculate the porosity using the density porosity formula.

[0112]

[0113] In formula (3): ρ b , ρ ma , ρ f , ρ sh — density logging value, rock density matrix value, fluid density value and shale density value respectively; V sh — shale content.

[0114] ③ Permeability

[0115] According to different petrophysical facies, use regression analysis to establish the statistical relationship between the logging values of porosity and permeability respectively, and determine the formula for calculating permeability using porosity.

[0116] ④ Saturation

[0117] Select the Archie formula to calculate the water saturation:

[0118]

[0119] In formula (4): S w — water saturation; a - proportional coefficient related to lithology; b - constant related to lithology; m - cementation exponent of the rock; n - saturation exponent; R w — formation water resistivity; R t — resistivity of hydrocarbon-bearing pure rock.

[0120] a, b, m, n are obtained by establishing the relationships between formation factor and porosity, and between water saturation and resistivity increase factor I for different petrophysical facies; the formation water resistivity is determined using the spontaneous potential method and water ion analysis data.

[0121] (3) Use data such as cast thin sections and scanning electron microscopes to qualitatively describe the pore structure of tight reservoirs and classify the types, and combine data such as logging and core laboratory analysis to quantitatively describe the pore structure of reservoirs.

[0122] ① Pore type

[0123] Based on the analysis of experimental data such as thin sections of cast bodies and scanning electron microscopy, the pore types of tight reservoirs are divided into primary intergranular pores, dissolved intergranular pores, dissolved intragranular pores, moldic pores, and fractures. Primary intergranular pores refer to the pore spaces formed during diagenesis without undergoing secondary modification. Dissolved intergranular pores refer to the pore spaces formed by the dissolution of the cement between grains. Intragranular pores in this study mainly refer to primary intragranular pores, which are the pore spaces within the grains. Dissolved intragranular pores refer to the pore spaces formed by the dissolution of unstable components such as feldspar and quartz or the dissolution of the intragranular pores filled with cement. Moldic pores refer to a type of pore space where unstable components are completely dissolved under strong dissolution, leaving only the outer shape, with a diameter greater than 0.2 mm. Fractures refer to the pore spaces generated by the fracturing of rocks, which can improve the seepage capacity of the reservoir. The later fissures may be filled, reducing the pore space.

[0124] ② Throat types

[0125] According to their genesis and morphological characteristics, they can be mainly divided into five types: pore constriction throat, necking throat, sheet throat, curved sheet throat, and pipe bundle throat. The necking throat is the channel formed when the primary intergranular pores are blocked by cement, etc. It is characterized by large pores and narrow throats, with point-contact cementation between grains, having a relatively high porosity and a relatively low permeability. The sheet throat refers to the throat presenting a curved sheet shape due to strong compaction. It is characterized by small pores, narrow throats, and mostly interlocking contacts between grains.

[0126] ③ Pore structure characteristics and classification

[0127] Pore structure refers to the geometric shape, size, distribution, and connectivity of pores and throats in the reservoir, which is an important content for the effectiveness evaluation of tight reservoirs. The mercury injection curve characteristics and pore-throat radius provided by mercury injection experiments can reflect the microscopic physical properties of rocks and objectively show the storage and seepage capacities of the reservoir. Based on the capillary pressure curve, combined with characteristics such as the mercury injection classification curve and pore-throat radius distribution, the pore structure of the reservoir is divided.

[0128] (4) The comprehensive result diagram is drawn based on the data obtained from the above steps (2)-(3). Combining the data processing results, a method for evaluating the effectiveness of tight oil reservoir reservoirs based on petrophysical facies is established.

[0129] The evaluation of effective reservoirs is usually based on the analysis of well testing data, combined with conventional logging, experimental analysis and qualitative and quantitative interpretation results, considering the mutual influencing factors among various evaluation indicators, and establishing an evaluation standard for the effectiveness of tight oil reservoir reservoirs. The effectiveness of tight oil reservoir reservoirs is mainly affected by lithology, pore throat structure, porosity, permeability, etc. Therefore, these factors need to be comprehensively considered during the evaluation of effective reservoirs. When the lithology and physical properties are good, a good pore structure will surely result in higher oil and gas production; when the lithology and physical properties are average, if the pore structure is good, high production may still be achieved after acid fracturing. Therefore, based on the classification evaluation of rock physics facies and pore structure, the mutual relationship between rock physics facies and pore structure is carefully analyzed in combination with well testing data, and finally the evaluation standard of effective reservoirs in the demonstration area is comprehensively evaluated based on the classification evaluation criteria of rock physics facies and pore structure.

[0130] In order to introduce the logging evaluation method for the effectiveness of tight oil reservoir reservoirs based on rock physics facies provided by the embodiments of the present invention more clearly and in detail, the following will be described in combination with specific embodiments.

[0131] According to steps (1)-(4) for analysis and calculation, the process is shown in Figure 1 , and well A in a certain block is processed. Well A determines the rock physics facies based on the principal component analysis method as Figure 2 , the logging response characteristics of various rock physics facies are shown in Table 1, and the evaluation results of the effectiveness of the reservoir pore structure are shown in Figure 3 , and the comprehensive evaluation results of the reservoir effectiveness are shown in Figure 4 .

[0132] Table 1 is the logging response characteristic table of various rock physics facies in the embodiments of the present invention

[0133]

[0134]

[0135] Figure 3 is the evaluation result diagram of the effectiveness of the reservoir pore structure of Well A. According to the capillary pressure curve, mercury injection fractal curve and pore throat characteristic parameters, the reservoir pore structure is comprehensively classified into four major types of pore structures. As shown in Table 2.

[0136] Table 2 is the classification result table of the reservoir pore structure in the embodiments of the present invention

[0137] Mercury injection curve type Ⅰ Ⅱ Ⅲ Ⅳ Porosity (%) >15 10-15％ <10 <10 <![CDATA[Permeability / 10 -3 μm 2 > >20 3-20 0.5-3 ＜0.5 Average pore throat radius / 12.14 6.54 1.27 0.19 Pore structure coefficient >3 0.8-3 0.3-0.8 <0.3 Pore structure Medium pores and medium throats Low porosity and relatively fine throats Extra-low porosity and fine throats Extra-low porosity and micro-fine throats Physical property characteristics Good Fairly good Average Poor Lithology Siltstone and fine sandstone Fine sandstone and siltstone Coarse sandstone and calcareous sandstone Argillaceous sandstone, etc. Number of samples 1 3 6 5

[0138] Figure 4It is the comprehensive result map for the evaluation of the reservoir effectiveness of Well A. Standards for the evaluation of reservoir effectiveness were established based on the rock physical properties, as shown in Table 3. The selected target interpreted interval is 3,785 - 3,829 m, and the thickness of the interval is 44 m. Parameters such as rock physical facies, porosity, permeability, and saturation in the figure are all obtained according to the formula methods given in steps (i) - (iii). For the interval of 3,790 - 3,797.8 m in the figure, from the logging curves, the GR curve is relatively low, the DEN curve is relatively low, the AC curve is medium, and the RT curve shows medium to high values. The lithology of the formation in this interval is mainly fine sandstone, which is consistent with the core analysis and mud logging. The logging response characteristics of the interval of 3,807 - 3,824 m in the figure are similar to those of the interval of 3,790 - 3,979.8 m, and the bottom lithology is mainly siltstone. The rock physical facies is classified as the fourth type of rock physical facies, with good physical properties. According to the rock physical facies analysis method, it can be judged as the fourth type of rock physical facies, with porosity ranging from 9.7% to 12.9% and permeability ranging from 2.8 to 8.7. It has the second type of pore structure and is a class I reservoir according to the comprehensive evaluation standard for effectiveness. The mud logging shows that the oil-bearing grade is mainly oil stain. The well test and production data show that the initial daily oil production of this interval is 5.9 tons, and the current daily oil production is 1.6 tons. The conclusion of the comprehensive evaluation of effectiveness is consistent with the mud logging description and the well test and production data, and can be preferably applied to the comprehensive evaluation of tight reservoirs.

[0139] Table 3 is the table of the reservoir effectiveness evaluation standard for the embodiment of the present invention

[0140]

[0141] The above content is a further detailed description of the present invention in combination with specific preferred embodiments. It cannot be determined that the specific implementation of the present invention is only limited to these descriptions. For those of ordinary skill in the technical field to which the present invention belongs, without departing from the concept of the present invention, several simple deductions or substitutions can be made, which should all be regarded as belonging to the protection scope of the present invention.

Claims

1. A method for evaluating the effectiveness of tight oil reservoirs based on rock physical phases, characterized in that: The following steps are involved: S1 uses logging, well logging, rock sampling and geological data, based on multi-parameter fusion nonlinear processing methods, combined with logging phase comparison analysis to determine the rock physical phase of tight reservoirs; S2 uses logging, coring and geological data to model tight oil reservoir parameters according to rock physical phase classification and calculate reservoir evaluation parameters; S3 uses cast thin sections, scanning electron microscopy and other data to qualitatively describe the pore structure of tight reservoirs and classify the types, and combines well logging and core analysis data to quantitatively describe the reservoir pore structure; S4: a comprehensive result map is drawn based on the data obtained in the above steps S2-S3, and an effective reservoir evaluation method for tight oil reservoirs based on rock physical phase is established in combination with the data processing results.

2. The method for establishing the effectiveness evaluation of tight oil reservoirs based on rock physical phases according to claim 1, characterized in that: The step S1 specifically includes: Based on the multi-parameter fusion nonlinear processing method, the corresponding relationship between logging phase and rock physical phase is established.

3. The method for establishing the effectiveness evaluation of tight oil reservoirs based on rock physical phases according to claim 2, characterized in that: The step S1 specifically includes: The correlation between various rock physical phases and well logging curves was investigated, and four well logging curves, namely neutron porosity, acoustic wave time difference, natural potential and resistivity, were used to divide the rock physical phases; Using the principal component analysis method, two principal components were extracted from the four logging curves, and a rock physics intersection analysis diagram was established to divide the lithofacies. The calculation method is as follows: PC1=0.567CNL+0.572AC+0.414SP-0.423RT (1); PC2=-0.01CNL+0.006AC+0.719SP+0.695RT ​​(2); Among them, CNL-neutron logging value, AC-acoustic logging value, SP-spontaneous potential logging value, RT-resistivity logging value.

4. The method for establishing the effectiveness evaluation of tight oil reservoirs based on rock physical phases according to claim 1, characterized in that: In step S2, the reservoir evaluation parameters are mud content, porosity, permeability and saturation.

5. The method for establishing the effectiveness evaluation of tight oil reservoirs based on rock physical phases according to claim 1, characterized in that: In step S2, calculating reservoir evaluation parameters includes: Calculation of mud content: The natural potential and resistivity methods are used to calculate the mud content, and the minimum value is taken as the final result. The calculation formula is: In formula (3) and (4), SHLG is the well logging curve value; GMAX and GMIN are the well logging values ​​of pure mudstone and pure bottom layer; SH is the relative value of the well logging curve; GCUR is the empirical coefficient, which is 3.7 for Tertiary strata and 2 for old strata; V sh — Mud content.

6. The method for establishing the effectiveness evaluation of tight oil reservoirs based on rock physical phases according to claim 1, characterized in that: In the step S2, calculating the reservoir evaluation parameters also includes: Porosity calculation: According to different rock physical phases, the porosity is calculated using the density porosity formula. The calculation formula is: In formula (5): b , ma , f , sh — respectively, density logging value, rock density skeleton value, fluid density value and mudstone density value; V sh — Mud content.

7. The method for establishing tight oil reservoir effectiveness evaluation based on rock physical phase according to claim 1, characterized in that: In the step S2, the reservoir evaluation parameters are calculated, which also includes: permeability calculation: according to different rock physical phases, using regression analysis, respectively establish the statistical relationship between the logging values ​​of porosity and permeability, and determine the formula for calculating permeability using porosity.

8. The method for establishing tight oil reservoir effectiveness evaluation based on rock physical phase according to claim 1, characterized in that: In step S2, the reservoir evaluation parameters are calculated, which also includes: saturation calculation: using Archie's formula to calculate water saturation: In formula (6): S w —water saturation; a—proportional coefficient related to lithology; b—constant related to lithology; m—cementation index of rock; n—saturation index; R w — formation water resistivity; R t —Resistivity of pure rock containing oil and gas.

9. The method for establishing tight oil reservoir effectiveness evaluation based on rock physical phase according to claim 8, characterized in that: In step S2, a, b, m, and n are obtained through the relationship between formation factors and porosity, water saturation, and resistivity increase coefficient I; the formation water resistivity is determined using the natural point method and water ion analysis data.

10. The method for establishing tight oil reservoir effectiveness evaluation based on rock physical phase according to claim 1, characterized in that: In step S3, the reservoir pore structure includes pore type, throat type and pore structure characteristics and classification.

11. The method for establishing tight oil reservoir effectiveness evaluation based on rock physical phase according to claim 1, characterized in that: In step S3, the reservoir pore structure evaluation method includes: Based on the analysis of experimental data such as casting thin sections and scanning electron microscopy, the pore types of tight reservoirs are divided into primary intergranular pores, dissolved intergranular pores, dissolved intragranular pores, mold pores and fractures. Among them, primary intergranular pores refer to the pore spaces formed during the diagenesis process without secondary transformation; dissolved intergranular pores refer to the pore spaces formed by the dissolution of cement between particles; intragranular pores refer to primary intragranular pores, which are the pore spaces inside particles; dissolved intragranular pores refer to the pore spaces formed by the dissolution of unstable components such as feldspar and quartz or the dissolution of cement after filling the intragranular pores; mold pores refer to a type of pore space in which unstable components are completely dissolved under strong dissolution and only the outer shape is left, with a diameter greater than 0.2 mm; cracks refer to the pore spaces generated by rock fracturing, which can improve the seepage capacity of the reservoir, and the cracks may be filled in the later stage to make the pore space smaller.

12. The method for establishing tight oil reservoir effectiveness evaluation based on rock physical phase according to claim 1, characterized in that: In step S3, the reservoir pore structure evaluation method includes: According to the causes and morphological characteristics, it can be divided into five types: pore-reduced roaring channel, neck-constricted roaring channel, lamellar roaring channel, curved lamellar roaring channel and tubular roaring channel. Among them, the neck-type throat is a channel formed when the primary intergranular pores are blocked by cementing materials, etc., which is characterized by large pores and fine throats, point contact cementation between particles, high porosity and low permeability; the lamellar throat refers to the throat that becomes curved and lamellar due to strong compaction, which is characterized by small pores, fine throats, and mosaic contact between particles.

13. The method for establishing tight oil reservoir effectiveness evaluation based on rock physical phase according to claim 1, characterized in that: In step S3, the reservoir pore structure evaluation method further includes: The pore structure of the reservoir is divided based on the capillary pressure curve combined with the mercury injection typing curve, pore throat radius distribution and other characteristics.

14. The method for establishing tight oil reservoir effectiveness evaluation based on rock physical phase according to claim 1, characterized in that: In step S4, a method for evaluating an effective reservoir of a tight oil reservoir based on rock physical phase is established, comprising: Based on the analysis of test oil and production data, combined with conventional logging, experimental analysis and qualitative and quantitative interpretation results, and considering the mutual influence factors among various evaluation indicators, an evaluation standard for the reservoir effectiveness of tight oil reservoirs is established.

15. The method for establishing tight oil reservoir effectiveness evaluation based on rock physical phase according to claim 1, characterized in that: In step S4, a method for evaluating an effective reservoir of a tight oil reservoir based on rock physical phase is established, comprising: On the basis of the classification and evaluation of rock physical phases and pore structures, the relationship between rock physical phases and pore structures was analyzed in detail in combination with the test oil and production data, and finally the reservoir effectiveness of the demonstration area was comprehensively evaluated based on the standards of rock physical phases and pore structure classification and evaluation.

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