Lithology correction-based oil-bearing potential discrimination method for oil reservoir and application

Abstract

The invention provides a lithologic correction-based oil-containing potential discrimination method for an oil reservoir, which comprises the following steps of: acquiring shale content of a logging reservoir by using a core calibration logging method, and performing secondary environment correction on the acquired shale content by using a support vector machine; carrying out shale correction on the reservoir deep exploration resistivity by utilizing the shale content after the secondary environment correction, wherein the corrected resistivity value is the resistivity value of the pure sandstone reservoir without shale; according to the method, the theoretical correlation between the porosity and the resistivity of the pure sandstone reservoir under different oil saturation conditions is solved by combining regional formation water cognition and utilizing an Archie formula, so that an oil-containing potential evaluation chart of a porosity-corrected resistivity value is obtained, and the oil-containing potential of the reservoir can be evaluated by utilizing the chart; the method has good practicability and wide popularization and application prospects.

Description

Technical Field

[0001] The invention relates to the technical field of geophysical exploration well logging data evaluation, in particular to a method for distinguishing the oil potential of a reservoir based on lithology correction and its application. Background Art

[0002] Under the control of the structural sedimentary background, oil and gas in Daganggangxi Oilfield have undergone multiple long-distance migrations from deep to shallow. During the migration process, affected by formation water scouring, surface water infiltration and oxidation, oil and gas are preferentially saturated in the larger pore throats in the high-porosity and high-permeability reservoirs, and the degree of oil-water displacement is low, which makes it easier to develop low-saturation oil and gas reservoirs. Such reservoirs are often not obvious in the electrical response of well logging and are easily missed during the interpretation and evaluation process.

[0003] Traditional low-saturation oil and gas reservoir evaluation methods mainly rely on systematic rock physics experiments and the establishment of water production rate calculation models; this method has high requirements for regional basic data, which makes it impossible to promote it on a large scale and has low efficiency; in order to improve the identification accuracy of reservoir oil potential and the efficiency of interpretation and development, it is necessary to establish a field rapid reservoir oil potential identification method to achieve rapid evaluation of reservoir fluid properties and guide the formulation of subsequent development and construction plans. Summary of the invention

[0004] The present invention proposes a method for quickly distinguishing the oil potential of low-saturation reservoirs based on lithology correction. The method avoids the necessary step of using water production rate to grade and evaluate low-saturation reservoirs in current well logging by establishing a porosity-corrected resistivity oil potential evaluation chart that reflects the change in formation oil saturation, and distinguishes potential layers by using oil saturation instead of water production rate, so that the accuracy of reservoir oil and gas identification is high.

[0005] The method for determining the oil potential of a reservoir based on lithology correction includes the following steps:

[0006] The core calibration logging method is used to obtain the reservoir shale content, and the support vector machine is used to perform secondary environmental correction on the obtained shale content.

[0007] The shale content after secondary environmental correction is used to correct the deep reservoir resistivity for shale content. The corrected resistivity value is the resistivity value of pure sandstone reservoir without shale.

[0008] Combined with the knowledge of regional formation water, the Archie formula is used to obtain the theoretical correlation between porosity and resistivity of pure sandstone reservoirs under different oil saturations, thereby obtaining an oil potential evaluation chart of porosity-corrected resistivity values, which can be used to evaluate the oil potential of the reservoir.

[0009] Furthermore, the method for evaluating the oil potential of the reservoir using the chart is as follows:

[0010] Obtain the water saturation S of the oil and gas layer w , for S w <40%, the reservoir is interpreted as an oil layer; when 40% w <60%, the reservoir is Class I oil-water co-layer; when 60% w <80%, the reservoir is a Class II oil-water layer; when 80% w When , the reservoir is the water layer.

[0011] Furthermore, the method for performing shale correction on the deep detection resistivity of the reservoir using the shale content after secondary environmental correction is as follows:

[0012]

[0013] Where: Rtn is the lateral resistivity after mud correction; Rt is the measured value of deep detection resistivity; Rsh is the resistivity of pure mudstone; Vsh is the mud content.

[0014] Furthermore, the method of obtaining the mud content of the logging reservoir using the core calibration logging method is as follows:

[0015] The shale content of the logging reservoir is obtained by establishing the correlation between the natural gamma response characteristics and the shale content of the core:

[0016]

[0017] Where: GR is the natural gamma logging response value; GR min is the natural gamma logging response characteristic value of pure sandstone; GR max is the characteristic value of natural gamma logging response of pure mudstone; a and b are model coefficients respectively.

[0018] Furthermore, the method of obtaining the water saturation of pure sandstone formation using Archie formula is:

[0019]

[0020] Where: S w is the water saturation of the oil and gas layer, dimensionless; Rt is the measured resistivity value of deep detection; is the porosity, dimensionless; R w is the formation water resistivity; n is the saturation index, dimensionless; m is the cementation index, dimensionless; a is the lithology coefficient, dimensionless; b is the coefficient related to lithology, dimensionless.

[0021] The application of the above-mentioned method for determining the oil potential of oil reservoirs based on lithology correction can realize the evaluation of the oil potential of low-saturation oil and gas reservoirs.

[0022] ​​​The advantages and positive effects of the present invention are:

[0023] 1. Based on the conventional calculation of mud content, the present invention uses support vector machine to perform secondary correction on the errors caused by environmental factors, so that the mud content evaluation is more accurate, and mud correction is performed on the measured resistivity of the reservoir accordingly, so that the accuracy of the reservoir fluid property discrimination is higher;

[0024] 2. This invention not only realizes the conventional identification of formation fluid properties, but also conducts fine classification evaluation of oil and water layers; under the current situation of oil fields that have entered the middle and late stages of development, it can fully explore the oil potential of the oil fields and help improve the oil field recovery rate;

[0025] 3. This invention uses saturation instead of water production rate to evaluate low-saturation oil reservoirs, avoiding the necessary steps of accurate evaluation of water production rate by current well logging, reducing the work of basic data construction, and is easy and fast to use, with a high compliance rate, good practicality and broad prospects for promotion and application. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 This is the basic idea of ​​the secondary correction of the support vector machine in Embodiment 1 of the present invention;

[0027] Figure 2 This is a comparison chart of the mud content evaluation accuracy before and after the secondary correction in Example 1 of the present invention;

[0028] Figure 3 It is the interactive interpretation chart of porosity and resistivity in Example 1 of the present invention;

[0029] Figure 4 It is the interactive interpretation chart of porosity and lithology-corrected electrical resistance in Example 1 of the present invention;

[0030] Figure 5 It is the oil potential evaluation chart reflecting the formation saturation change in Example 2 of the present invention;

[0031] FIG6(a) is a well logging interpretation diagram in Example 2 of the present invention;

[0032] FIG6( b ) is the reservoir mudstone related data in Example 2 of the present invention;

[0033] FIG6(c) is an oil potential evaluation chart reflecting the change in formation saturation in Example 2 of the present invention. DETAILED DESCRIPTION

[0034] In order to make the purpose, technical scheme and advantages of the implementation of the present invention clearer, the technical scheme in the embodiment of the present invention will be described in more detail below in conjunction with the drawings in the embodiment of the present invention. In the drawings, the same or similar reference numerals throughout represent the same or similar elements or elements with the same or similar functions. The described embodiments are part of the embodiments of the present invention, not all of the embodiments. The embodiments described below with reference to the drawings are exemplary and are intended to be used to explain the present invention, and should not be construed as limitations on the present invention. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0035] The retail package pricing method considering price-type demand response constructs a demand response model, analyzes the cost-benefit function of electricity retailers including electricity sales revenue, electricity purchase expenditure, response income, etc., and builds a retail package pricing model to provide decision support for retailers from the perspective of optimizing pricing.

[0036] The embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0037] Example 1

[0038] The inventor provides a method for determining the oil potential of an oil reservoir based on lithology correction, comprising the following steps:

[0039] The core calibration logging method is used to obtain the reservoir shale content, and the support vector machine is used to perform secondary environmental correction on the obtained shale content.

[0040] The shale content after secondary environmental correction is used to correct the deep reservoir resistivity for shale content. The corrected resistivity value is the resistivity value of pure sandstone reservoir without shale.

[0041] Combined with the regional formation water knowledge, the Archie formula is used to obtain the theoretical correlation between porosity and pure sandstone reservoir resistivity under different oil saturations, so as to obtain the oil potential evaluation chart of porosity-corrected resistivity value, and the oil potential of the reservoir can be evaluated by using the chart; wherein, the method for evaluating the oil potential of the reservoir by using the chart is:

[0042] Obtain the water saturation S of the oil and gas layer w , for S w <40%, the reservoir is interpreted as an oil layer; when 40% w <60%, the reservoir is interpreted as Type I oil-water co-layer; when 60% w <80%, the reservoir is interpreted as Type II oil-water co-layer; when 80% w When , the reservoir is interpreted as a water layer.

[0043] ​​​The specific method for determining the oil potential of a reservoir based on lithology correction is as follows:

[0044] Step 1: Conventional reservoir shale content logging evaluation;

[0045] Generally, sedimentary rocks do not contain radioactive minerals, and their radioactivity is mainly caused by the adsorption of mud in the reservoir. Therefore, conventional logging reservoir mud content evaluation is carried out by using the core calibration logging method to establish the correlation between the natural gamma response characteristics and the core mud content, as shown in Formula 1:

[0046]

[0047] Where: GR is the natural gamma logging response value; GR min is the natural gamma logging response characteristic value of pure sandstone; GR max is the characteristic value of natural gamma logging response of pure mudstone; a and b are model coefficients respectively.

[0048] Step 2: Introduce support vector machine to perform secondary environmental correction on the calculated mud content;

[0049] The natural gamma logging response characteristics of the reservoir not only depend on the mud content of the reservoir, but also on the well conditions, drilling fluid type, formation thickness, thin interlayer distribution, etc., so it is a comprehensive indicator displayed by the reservoir. In view of the fact that it is related to many factors and it is very difficult to determine the quantitative analysis relationship, the present invention introduces a support vector machine to perform secondary correction on the mud content calculated in the reservoir and the mud content analyzed in the core rock physics experiment. The support vector machine can seek the best relationship between the dependent variable and the independent variable in a complex model based on limited sample information. It has unique advantages in solving the determination of nonlinear relationships in high-dimensional models and has good generalization ability. Figure 1 The basic idea of ​​the invention's support vector machine secondary correction is to input various parameters reflecting the formation characteristics into the processing unit, and then output the core shale content; Figure 2 The comparison of the evaluation accuracy of mud content before and after the introduction of support vector machine secondary correction is shown. It can be seen that the accuracy is greatly improved after the use of support vector machine secondary correction.

[0050] Step 3: Perform lithology correction on deep detection resistivity;

[0051] In order to characterize the effect of mud content on reservoir resistivity and make corrections, according to the principle of parallel circuit, the conductivity of sandstone can be simplified as the weighted average of the resistivity of the mudstone part and the sandstone part, as shown in Formula 2. Formula 2 is used to perform mud correction on the resistivity of deep reservoir detection, and it is believed that the corrected resistivity value is the resistivity value of a pure sandstone reservoir without mud.

[0052] The invention firstly establishes the fluid property identification chart of porosity-deep detection resistance and the fluid property identification chart of porosity-corrected deep detection resistance based on the conclusion of oil field test production and the response characteristics of small layer logging, such as Figure 3 , Figure 4 As shown in Figure 2, it can be seen that the latter is more effective in distinguishing the properties of different fluids.

[0053]

[0054] Where: Rtn is the lateral resistivity after mud correction, Ω·m; Rt is the measured value of deep detection resistivity, Ω·m; Rsh is the resistivity of pure mudstone, read from the logging curve, Ω·m; Vsh is the mud content, %.

[0055] Step 4: Establish an oil potential evaluation chart of porosity-rectified resistivity reflecting the change of formation oil saturation;

[0056] On the fluid property identification chart of porosity-corrected deep detection resistance, combined with the regional formation water knowledge, the Archie formula was used to obtain the theoretical correlation between porosity and pure sandstone formation resistivity under different oil saturations.

[0057] The Archie formula links the resistivity of reservoir rocks with the oil and gas saturation, thus laying the geological foundation for logging interpretation of oil and gas layers. The specific formula is shown in Formula 3. This formula is suitable for calculating the water saturation of pure sandstone formations where the rock has no skeleton-added conductivity and the pores are all filled with electrolytes. The parameters a, b, m, and n are called Archie parameters, which are determined by the core sampling laboratory in key wells in the region.

[0058]

[0059] Where: S w is the water saturation of the oil and gas layer, dimensionless; Rt is the measured resistivity value of deep detection, Ω·m; is the porosity, dimensionless; R w is the formation water resistivity, Ω·m; n is the saturation index, dimensionless; m is the cementation index, dimensionless; a is the lithology coefficient, dimensionless; b is the coefficient related to lithology, dimensionless.

[0060] The application of the above-mentioned method for determining the oil potential of oil reservoirs based on lithology correction can realize the evaluation of the oil potential of low-saturation oil and gas reservoirs.

[0061] Example 2

[0062] In this embodiment, the Gangxi Oilfield is taken as an example. In the middle and shallow layers of this oilfield, low-saturation oil and gas layers controlled by sedimentary rhythm are relatively easy to develop. Using the method in Embodiment 1 to introduce shale correction resistivity for the reservoir, first, shale correction is performed on the deep resistivity value measured by logging. The corrected resistivity can be approximately considered as the resistivity reflection of the pure sandstone in the reservoir. At this time, the rock-electric relationship between oil and gas and porosity satisfies Archie's formula; as Figure 5 shown, different oil saturation curves are represented as parallel curves in the chart. Using this chart, the oil-bearing potential of the reservoir can be evaluated.

[0063] Combined with the regional understanding, when Sw < 40%, the reservoir is interpreted as an oil layer; when 40% < Sw < 60%, the reservoir is interpreted as a Class I oil-water coexistence layer; when 60% < Sw < 80%, the reservoir is interpreted as a Class II oil-water coexistence layer; when 80% < Sw, the reservoir is interpreted as a water layer.

[0064] Such as Figure 6(a) 、 6(b) 、6(c), Well Zhongxi A, the natural gamma value of Well 22# is low, the average shale content is 0.05, the porosity is 0.341, the deep resistivity is 4 Ω·m, and it shows a flat shape, which is the characteristic of the standard water layer in the area; the average shale content of Well 15# is 0.08, the porosity is 0.335, and the deep resistivity is 8.3 Ω·m; the average shale content of Well 18# is 0.08, the porosity is 0.341, and the deep resistivity is 8.4 Ω·m; the average shale content of Well 19# is 0.06, the porosity is 0.35, and the deep resistivity is 7 Ω·m. The deep resistivities of Well 15#, Well 18# and Well 19# are all greater than the resistivity of the regional standard water layer, but less than 3 times its resistivity. Therefore, they are interpreted as oil-water coexistence layers. Using the method of this invention for projection on the chart, Well 15# and Well 18# fall within the Class I oil-water coexistence layer area with a water saturation near 0.6 and have high development value. Well 19# falls within the Class II oil-water coexistence layer area with a water saturation near 0.7 and has low development value. Well 15# and Well 18# are perforated and put into production by means of a pumping well pump, with a daily oil production of 4.76 tons, water production of 2.45 m³, and a water production rate of 34%. The production effect is good, verifying the correctness of the analysis of this invention patent.

[0065] Finally, it should be pointed out that: the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for determining the oil potential of a reservoir based on lithology correction, characterized in that: The steps include: The core calibration logging method is used to obtain the reservoir shale content, and the support vector machine is used to perform secondary environmental correction on the obtained shale content. The shale content after secondary environmental correction is used to correct the deep reservoir resistivity for shale content. The corrected resistivity value is the resistivity value of pure sandstone reservoir without shale. Combined with the knowledge of regional formation water, the Archie formula is used to obtain the theoretical correlation between porosity and resistivity of pure sandstone reservoirs under different oil saturations, thereby obtaining an oil potential evaluation chart of porosity-corrected resistivity values, which can be used to evaluate the oil potential of the reservoir.

2. The method for determining oil potential of oil reservoirs based on lithology correction according to claim 1, characterized in that: The method for evaluating the oil-bearing potential of the reservoir using the above-mentioned chart is as follows: Obtain the water saturation S of the oil and gas layer w , for S w When <40%, the reservoir is interpreted as an oil layer; When 40% w <60%, the reservoir is interpreted as Type I oil-water co-layer; when 60% w <80%, the reservoir is interpreted as Type II oil-water co-layer; when 80% w When , the reservoir is interpreted as a water layer.​​​ 3. The method for determining oil reservoir oil potential based on lithology correction according to claim 1, characterized in that: The method of using the shale content after secondary environmental correction to perform shale correction on the deep detection resistivity of the reservoir is: Where: Rtn is the lateral resistivity after mud correction; Rt is the measured value of deep detection resistivity; Rsh is the resistivity of pure mudstone; Vsh is the mud content.

4. The method for determining oil potential of oil reservoirs based on lithology correction according to claim 1, characterized in that: The method of obtaining the mud content of the logging reservoir using the core calibration logging method is: The shale content of the logging reservoir is obtained by establishing the correlation between the natural gamma response characteristics and the shale content of the core: Where: GR is the natural gamma logging response value; GR min is the natural gamma logging response characteristic value of pure sandstone; GR max is the characteristic value of natural gamma logging response of pure mudstone; a and b are model coefficients respectively.

5. The method for determining oil potential of oil reservoirs based on lithology correction according to claim 1, characterized in that: The method of obtaining the water saturation of pure sandstone formation using Archie formula is: Where: S w is the water saturation of the oil and gas layer, dimensionless; Rt is the measured resistivity value of deep detection; is the porosity, dimensionless; R w is the formation water resistivity; n is the saturation index, dimensionless; m is the cementation index, dimensionless; a is the lithology coefficient, dimensionless; b is the coefficient related to lithology, dimensionless.

6. Application of the method for determining oil potential of oil reservoirs based on lithology correction according to any one of claims 1 to 5, characterized in that: The method can realize the evaluation of the oil potential of low-saturation oil and gas reservoirs.

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