High-salinity tight reservoir fluid property identification method and system

Abstract

The invention belongs to the technical field of petroleum and natural gas geology and exploration and development engineering, and particularly relates to a high-salinity tight reservoir fluid property identification method and system. The method comprises the following steps of: calculating a theoretical value of a macroscopic capture cross section under the condition of hypersalinity formation water by utilizing mineral content, then taking a difference value between the theoretical value of the macroscopic capture cross section and a measured value of the macroscopic capture cross section as a sensitive factor for judging the oiliness, and forming a fluid property identification chart by utilizing the difference value and effective porosity, the fluid property of the tight oil reservoir under the hypersalinity background can be accurately identified; the specific value of the relative yield of the chlorine element to the effective porosity is used as a salt-containing sensitive factor, the salt-containing sensitive factor and the effective porosity are used for forming a salt-containing evaluation chart, the salt-containing degree of the dessert section can be judged, and whether oil testing is necessary or not is determined accordingly. According to the method, the fluid property under the background of the high-salinity tight reservoir can be accurately identified, and oil testing suggestions are given.

Description

Technical Field

[0001] The invention belongs to the technical field of petroleum and natural gas geology and exploration and development engineering, and particularly relates to a method and system for identifying properties of high-salinity tight reservoir fluids. Background Art

[0002] At present, there are four main types of fluid property identification methods: the first type is electrical logging. Electrical logging is the most commonly used method for fluid property identification. For sandstone reservoirs, the resistivity is often used to determine the oil content. However, for unconventional reservoirs, the resistivity logging value is a comprehensive response of lithology, physical properties, oil content, and source rock characteristics. The resistivity cannot truly reflect the changes in the properties of the formation fluid. At the same time, electrical logging will be affected by high-mineralization formation water or mud, making the resistivity of the flushing zone or even the resistivity of the invasion zone lower than the resistivity of the original formation, creating the illusion that the reservoir physical properties have improved. The second type is nuclear magnetic resonance logging. Nuclear magnetic resonance logging, especially the two-dimensional nuclear magnetic resonance logging T1-T2 domain, has a clear distinction between different fluid properties such as movable oil, movable water, bound oil, and bound water, and has good applications in the fields of shale oil and tight oil. However, nuclear magnetic resonance logging is a coupling of wettability, oil content, pore structure, and fluid viscosity, which results in the nuclear magnetic resonance logging response not being able to fully reflect the oil content. At the same time, when the mineralization of formation water is very high, it will be affected by the eddy current load formed by the high conductivity of formation water, resulting in a poor signal-to-noise ratio of nuclear magnetic logging data, affecting the morphology of the T2 spectrum, and thus resulting in great limitations in the use of nuclear magnetic logging for fluid identification. The third is secondary gamma ray spectrum logging. Secondary gamma ray spectrum can measure the yield of multiple elements in the formation, and use the ratio of the yield to construct sensitive factors (such as C / O ratio can be used as an oil-containing sensitive factor, Si / Ca can be used as a reservoir sand-containing sensitive factor) to judge the oil content of the reservoir. However, for shale oil and tight oil, the source of C element is not only oil and gas, but also source rocks and minerals containing carbon elements. The commonly used C / O cannot represent the oil content of the reservoir. The fourth is element logging. This logging method can explain the mineral content of the formation, and use the mineral content to invert characteristic curves that can characterize the oil content of the formation, such as resistivity, acoustic waves, density, etc., and thus indirectly reflect the changes in oil and gas content. Or the measured macroscopic capture cross section size can be directly used to reflect the gas content (the macroscopic capture cross section of gas-bearing formations is significantly smaller than that of water-bearing formations). This method is mainly used in gas-bearing formations and has a good application effect, but it is not effective for tight reservoirs and high-salt reservoirs. Summary of the invention

[0003] In view of the above problems, in a first aspect, the present invention proposes a method for identifying fluid properties in a high-salinity tight reservoir, comprising:

[0004] Determine the mineral content of the formation and the macroscopic capture cross section of the logging measurement based on element logging data;

[0005] Determining a theoretical value of a macroscopic capture cross section when the pores are saturated with salt water according to the mineral content and the macroscopic capture cross section of the formation water;

[0006] Intersecting the effective porosity with the difference value to form a fluid property identification chart for a high-salinity tight reservoir, wherein the difference value is the difference between the macroscopic capture cross section and a theoretical value of the macroscopic capture cross section;

[0007] A salt evaluation chart formed by intersecting effective porosity and salt sensitivity factor, wherein the salt sensitivity factor is constructed using the relative yield of chlorine extracted from element logging data;

[0008] The fluid property identification chart of the high-salinity tight reservoir is used to determine the fluid property of the formation, and the salt content evaluation chart is then used to determine whether the sweet spot section needs oil testing.

[0009] Furthermore, conventional logging data, element logging data and formation water salinity data of tested wells are obtained;

[0010] Obtain the mineral types and mineral contents of the formation based on element logging data;

[0011] To judge the rationality of the mineral content;

[0012] If the mineral content is reasonable, the macroscopic capture cross section of the well logging measurement is determined using the mineral content; if the mineral content is unreasonable, the mineral content is recalculated.

[0013] Furthermore, judging the rationality of the mineral content includes the following steps:

[0014] Obtain volume photoelectric absorption cross-section index logging value;

[0015] Calculate the theoretical value of the volume photoelectric absorption cross-section index based on the mineral content;

[0016] Calculating the relative error between the theoretical value of the volume photoelectric absorption cross-section index and the logging value of the volume photoelectric absorption cross-section index;

[0017] Set the limit value of relative error;

[0018] The relative error and the limit value are judged. If the relative error is less than the limit value, the mineral content obtained is considered reasonable; if the relative error is greater than or equal to the limit value, the mineral content is considered unreasonable, and the mineral content is recalculated until the relative error is less than the limit value.

[0019] Further, the volume photoelectric absorption cross-section index theoretical value is calculated based on the mineral content as follows: the volume photoelectric absorption cross-section index theoretical value U is calculated according to the volume percentage of the mineral content in the formation, the volume photoelectric absorption cross-section index of the mineral, the volume photoelectric absorption cross-section index of the fluid in the pores and the total porosity of the formation. 理论 ;

[0020] The calculation formula is as follows:

[0021]

[0022] Among them, v i is the volume percentage of the i-th mineral content in the formation calculated by element logging; U i is the volume photoelectric absorption cross section index of the i-th mineral; U f is the volume photoelectric absorption cross-section index of the fluid in the pore; φ 总 is the total porosity of the formation, 1≤i≤j, where i is an integer and j is the type of mineral.

[0023] Furthermore, the calculation formula of the relative error is as follows:

[0024]

[0025] Where U 理论 is the theoretical value of volume photoelectric absorption cross section index; U 测井 is the rock volume photoelectric absorption cross-section index measured by lithology density logging; a is the limit value of relative error.

[0026] Furthermore, the theoretical value of the macroscopic capture cross section when the pores are saturated with salt water is determined according to the mineral content and the macroscopic capture cross section using the following formula:

[0027]

[0028] In the formula, Sigma 理论 Theoretical value of the macroscopic capture cross section when the pores are saturated with salt water; v i Sigma is the volume percentage of the i-th mineral content in the formation calculated by element logging; i is the macroscopic capture cross section of the i-th mineral; 1≤i≤j, i is an integer, j is the type of mineral; Sigma 地层水 is the macroscopic capture cross section of formation water, φ 总 is the total porosity of the formation;

[0029] Among them, the macroscopic capture cross section Sigma of formation water 地层水 The calculation is done using the following formula:

[0030] Sigma 地层水 =k+b·Cw

[0031] Where k is the macroscopic capture cross section of crude oil; b is the regression coefficient; Cw is the formation water salinity, mg / L.

[0032] Furthermore, the intersecting of the effective porosity and the difference value to form a fluid property identification chart for a high-salinity tight reservoir includes the following steps:

[0033] The difference between the macroscopic capture cross section value measured by well logging and the theoretical value of the macroscopic capture cross section under the condition of pore saturated with salt water is calculated as the difference value;

[0034] The difference value and the effective porosity are intersected to form a fluid property identification chart for high-salinity tight reservoirs.

[0035] Furthermore, the salt evaluation chart formed by intersecting the effective porosity and the salt sensitivity factor includes the following steps:

[0036] Extract the relative yield of chlorine from elemental logging data;

[0037] The salinity sensitivity factor is calculated based on the relative yield of the chlorine element and the total porosity of the formation; the calculation formula of the salinity sensitivity factor is as follows:

[0038]

[0039] Among them, SSF is the salinity sensitivity factor Y cl is the relative yield of chlorine measured by element logging, φ 总 is the total porosity of the formation.

[0040] In a second aspect, the present invention proposes a high-salinity tight reservoir fluid property identification system, comprising:

[0041] A first determination unit is used to determine the mineral content of the formation and the macroscopic capture cross section of the logging measurement based on the element logging data;

[0042] A second determination unit is used to determine a theoretical value of a macroscopic capture cross section when the pores are saturated with salt water according to the mineral content and the macroscopic capture cross section of the formation water;

[0043] A first plate forming unit is used to intersect the effective porosity with the difference value to form a fluid property identification plate of a high-salinity tight reservoir, wherein the difference value is the difference between the macroscopic capture cross section and a theoretical value of the macroscopic capture cross section;

[0044] The second plate forming unit is used to form a salt evaluation plate by intersecting the effective porosity and the salt sensitivity factor, wherein the salt sensitivity factor is constructed using the relative yield of the chlorine element extracted from the element logging data;

[0045] The identification unit is used to determine the fluid properties of the formation using the fluid property identification chart of the high-salinity tight reservoir, and then use the salt content evaluation chart to determine whether the sweet spot section needs oil testing.

[0046] In a third aspect, the present invention provides an electronic device, comprising a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other via the communication bus;

[0047] Memory for storing computer programs;

[0048] The processor is used to implement the method for identifying the properties of fluid in a high-salinity tight reservoir when executing the program stored in the memory.

[0049] In a fourth aspect, the present invention proposes a computer-readable storage medium storing a computer-readable program, which, when executed, executes the method for identifying fluid properties of a high-salinity tight reservoir.

[0050] Beneficial effects of the present invention:

[0051] The present invention calculates the theoretical value of the macroscopic capture cross section under the condition of high-mineralization formation water by using the mineral content, and then uses the difference between the theoretical value of the macroscopic capture cross section and the measured value of the macroscopic capture cross section as a sensitive factor for judging the oil content, and the influence of lithology on resistivity logging can be ignored; the error of C / O element in mixed rock formation caused by source rock and carbon-containing minerals can be avoided; the fluid properties of tight oil reservoirs under the background of high mineralization can be accurately identified; the porosity of the present invention can be calculated by conventional density and sonic logging, or directly calculated by element logging, and the changes in pore structure, wettability and fluid viscosity do not need to be considered, so as to solve the problem that the nuclear magnetic logging response cannot fully reflect the oil content in the nuclear magnetic logging method because the nuclear magnetic logging is the coupling of wettability, oil content, pore structure and fluid viscosity.

[0052] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures pointed out in the description, claims and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0054] Figure 1 A flow chart of a method for identifying fluid properties of a high-salinity tight reservoir based on element logging proposed in an embodiment of the present invention is shown;

[0055] Figure 2 The following is a diagram showing the identification of fluid properties of a high-salinity tight reservoir in a block according to an embodiment of the present invention. The horizontal axis is the effective porosity, and the vertical axis is the calculated Sigma 差异 ;

[0056] Figure 3 A salt evaluation chart of a high-salinity tight reservoir in a block according to an embodiment of the present invention is shown; wherein the abscissa is the effective porosity, and the ordinate is the salinity sensitivity factor;

[0057] Figure 4 The figure shows an example well of a high-salinity tight reservoir in the study area. From left to right, the 7th channel is the alkaline ore layer indicator channel, the 8th channel is the effective porosity, the 9th channel is the movable oil porosity, and the 10th channel is the Sigma 差异 The 11th channel is the salt sensitivity factor channel, the 12th channel is the logging interpretation sweet spot channel, the 13th channel is the perforation channel, and the 14th channel is the oil test conclusion channel;

[0058] Figure 5 A schematic diagram of a high-salinity tight reservoir fluid property identification system proposed by the present invention is shown;

[0059] Figure 6 A schematic diagram of the structure of an electronic device for a method for identifying fluid properties in a high-salinity tight reservoir proposed by the present invention is shown. DETAILED DESCRIPTION

[0060] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. 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.

[0061] The purpose of the present invention is to provide a method for identifying fluid properties in high-salinity tight reservoirs based on element logging, which can solve the problem that conventional electrical logging cannot identify oil and water due to high or low resistivity, and nuclear magnetic logging cannot identify fluids due to surface relaxation, pore structure, and oil content coupling. At the same time, it provides a basis for avoiding high-salinity reservoirs for oil test layers.

[0062] In order to achieve the above-mentioned purpose, the main steps of the technical solution adopted by the present invention are as follows: Figure 1 As shown:

[0063] Determine the mineral content of the formation and the macroscopic capture cross section of the logging measurement based on element logging data;

[0064] Determine the theoretical value of the macroscopic capture cross section when the pores are saturated with salt water according to the mineral content and the macroscopic capture cross section;

[0065] Intersecting the effective porosity with the difference value to form a fluid property identification chart for a high-salinity tight reservoir, wherein the difference value is the difference between the macroscopic capture cross section and a theoretical value of the macroscopic capture cross section;

[0066] A salt evaluation chart formed by intersecting effective porosity and salt sensitivity factor, wherein the salt sensitivity factor is constructed using the relative yield of chlorine extracted from element logging data;

[0067] The fluid property identification chart of the high-salinity tight reservoir is used to determine the fluid property of the formation, and the salt content evaluation chart is then used to determine whether the sweet spot section needs oil testing.

[0068] The specific steps include:

[0069] S1: Obtain conventional logging data, element logging data, and formation water salinity data of tested wells;

[0070] The conventional logging data includes lithology density logging information, and the porosity information is obtained by using the conventional logging data, and the porosity information includes the total porosity and effective porosity of the formation;

[0071] Element logging uses a combination of natural gamma ray logging, neutron activation logging, inelastic scattering gamma ray logging and thermal neutron capture gamma ray logging to obtain the formation mineral content and convert it into formation mineral abundance.

[0072] S2: Process the element logging data to obtain the type and content of minerals and the macroscopic capture cross section Sigma of formation water measured by logging 测井 , and calculate the theoretical value of volume photoelectric absorption cross-section index;

[0073] Among them, the types of minerals obtained include clay minerals, quartz, feldspar, dolomite, calcite, etc.

[0074] The theoretical volume photoelectric absorption cross-section index is calculated based on the volume percentage of mineral content, the volume photoelectric absorption cross-section index of the mineral, the volume photoelectric absorption cross-section index of the fluid in the pores, and the total porosity of the formation. The specific calculation formula is as follows:

[0075]

[0076] Among them, U 理论 It is the theoretical value of the rock volume photoelectric absorption cross-section index calculated using the mineral content, b / cm-3 ;v i is the volume percentage of the i-th mineral content in the formation calculated by element logging, %; U i is the volume photoelectric absorption cross-section index of the ith mineral, b / cm -3 ; U f is the volume photoelectric absorption cross-section index of the fluid in the pore, b / cm -3 Among them, U i and U f is a known value, and can be assigned and calculated based on the commonly used value; φ 总 is the total porosity of the formation, %, which can be calculated by conventional well logging.

[0077] S3: Compare the theoretical value of volume photoelectric absorption cross-section index with the logging value of volume photoelectric absorption cross-section index, and judge whether it is necessary to recalculate the mineral content according to the relative error between the two;

[0078] If the relative error between the two is within a reasonable range, that is, less than a, the mineral content calculation result is considered reasonable; otherwise, the mineral content calculation result is considered unreasonable, and the mineral content is recalculated until the relative error between the two reaches a reasonable range.

[0079] The relative error needs to satisfy the following formula:

[0080]

[0081] Among them, U 测井 It is the rock volume photoelectric absorption cross-section index measured by lithology density logging. Lithology density logging is a type of conventional logging, b / cm -3 ; a is the maximum relative error allowed between the two, that is, the limit value.

[0082] S4: Calculate the theoretical value of the macroscopic capture cross section Sigma when the pores are saturated with salt water 理论 ; The macroscopic capture cross section value Sigma measured by logging 测井 The theoretical value of the macroscopic capture cross section Sigma when the pores are saturated with salt water 理论 The difference Sigma 差异 As a sensitive parameter of oil content. 差异 Intersecting with effective porosity to form a fluid property identification chart for high-salinity tight reservoirs;

[0083] Since the macroscopic capture cross section of crude oil is generally 22 c.u., and the macroscopic capture cross section of fresh water is generally 22 c.u., the difference between the two is very small. However, when the mineralization of formation water increases significantly, the macroscopic capture cross section of water will increase significantly, especially in the sedimentary environment of salty lakes and alkaline lakes, which leads to high salt content in formation water. The mineralization of formation water can reach 200,000-350,000 mg / L, which makes the macroscopic capture of formation water and oil very different. Therefore, the macroscopic capture cross section can be used as the basic parameter for identifying fluid properties.

[0084] The theoretical value of the macroscopic capture cross section when the pores are saturated with brine is calculated using the following formula:

[0085]

[0086] In the formula, Sigma 理论 is the theoretical value of the macroscopic capture cross section of the formation, cu, under the assumption that the formation is saturated with brine; v i Sigma is the volume percentage of the i-th mineral content in the formation calculated by element logging, %; i is the macroscopic capture cross section of the i-th mineral, cu; 1≤i≤j, where i is an integer and j is the type of mineral; Sigma 地层水 is the macroscopic capture cross section of formation water, φ 总 is the total porosity of the formation, %.

[0087] The formation water is calculated using the following formula:

[0088] Sigma 地层水 =k+b·Cw

[0089] Where k is the macroscopic capture cross section value of crude oil, cu; b is the regression coefficient; Cw is the formation water salinity, mg / L;

[0090] The theoretical value of the macroscopic capture cross section Sigma when the gap is saturated with salt water 理论 and Sigma 测井 The difference Sigma 差异 As a sensitive parameter of oil content;

[0091] Sigma 差异 =Sigma 测井 -Sigma 理论

[0092] Sigma 测井 is the macroscopic capture cross section measured by well logging, cu; Sigma 差异 Sigma is the theoretical value of the macroscopic capture cross section when the pores are saturated with brine. 理论 and the macroscopic capture cross section value Sigma measured by well logging测井 The difference.

[0093] S5: Extract the relative yield of chlorine element using element logging data and construct salt sensitivity factor. Use the salt sensitivity factor to intersect with effective porosity to form a salt evaluation chart.

[0094] For the wells that need to be explained, the fluid properties of the reservoir are first determined using the fluid property identification plate of the high-salinity tight reservoir in step S4, and then the salt content identification plate in step S5 is used to determine whether it is necessary to test the sweet spot, where the sweet spot is a high-yield zone with relatively rich oil and gas.

[0095] The method for identifying fluid properties of high-salinity tight reservoirs proposed in the present invention is described by taking the tight oil formation of Fengcheng Formation in Mahu, Xinjiang Oilfield as an example. The specific steps are as follows:

[0096] (1) First, obtain conventional logging, element logging data, nuclear magnetic resonance logging, and formation water salinity data of tested wells, and use conventional logging to obtain porosity information.

[0097] Conventional logging needs to include lithology density logging information; in this embodiment, the element logging series is lithology scanning logging.

[0098] (2) Process the lithology scanning logging data to obtain the types and contents of minerals.

[0099] The common minerals of Fengcheng Formation in this example are: quartz, feldspar, dolomite, calcite, clay minerals and pyrite. Due to the lack of core data in the target area, it is impossible to use cores to calibrate the mineral content calculation results. At the same time, the mineral content calculation results will also affect the subsequent oil content evaluation, so it is necessary to judge whether the mineral content is accurate. The specific judgment steps are as follows:

[0100] ① Using the mineral content calculated by lithology scanning logging, calculate the theoretical value of the rock volume photoelectric absorption cross-section index:

[0101]

[0102] Among them, U 理论 It is the theoretical value of the rock volume photoelectric absorption cross-section index calculated using the mineral content, b / cm -3 ;v i is the volume percentage of the i-th mineral content in the formation calculated by element logging, %; U i is the volume photoelectric absorption cross-section index of the ith mineral, b / cm -3 ; U f is the volume photoelectric absorption cross-section index of the fluid in the pore, b / cm -3 ; φ 总is the total porosity of the formation, %; 1≤i≤j, and i is an integer.

[0103] ② The theoretically calculated volume photoelectric absorption cross-section index U 理论 Compared with the measured volume photoelectric absorption cross section index U 测井 For comparison; in this embodiment, the limit value is 5%,

[0104] Right now

[0105] Among them, U 测井 It is the rock volume photoelectric absorption cross-section index measured by lithology density logging. Lithology density logging is a type of conventional logging, b / cm -3 ;

[0106] If the relative error between the two is less than 5%, the mineral content calculated in the previous step is considered reasonable. Otherwise, it is considered unreasonable and the mineral content needs to be recalculated until U 理论 with U 测井 The relative error is less than 5%. Lithology density logging can obtain the measured rock volume photoelectric absorption cross-section index U.

[0107] (3) After obtaining a reasonable mineral content, the lithology scanning logging data is processed to obtain the macroscopic capture cross section Sigma measured by logging. 测井 , taking the macroscopic capture cross section as the basic parameter for identifying fluid properties.

[0108] Since the oil-water relationship in the tight oil reservoir of this example is complex, the tight oil reservoir is non-buoyant, and the water in the reservoir is often interlayer water, so there is no obvious interface between oil and water. Therefore, it can be assumed that the pores in the formation are completely water-containing, and the theoretical macroscopic capture cross section Sigma is calculated. 理论 ;

[0109]

[0110] In the formula, Sigma 理论 Sigma is the theoretical value of the macroscopic capture cross section of the formation calculated under the assumption that the formation is saturated with brine, cu; i is the macroscopic capture cross section of the i-th mineral, cu; 1≤i≤j, and i is an integer; v i is the volume percentage of the i-th mineral content in the formation calculated by element logging, %; φ 总 is the total porosity of the formation, %.

[0111] Among them, the macroscopic capture cross section Sigma of formation water 地层水 It can be obtained from formula (4):

[0112] Sigma 地层水=k+b·Cw=22+3.4*Cw (4)

[0113] In the formula, Sigma 地层水 is the macro capture cross section of formation water, cu; k is the macro capture cross section value of crude oil, cu; b is the regression coefficient; Cw is the formation water salinity, mg / L, which can be obtained using the regional formation water salinity mean of the well to be interpreted (i.e., the total salinity in Table 1), as shown in Table 1.

[0114] Table 1 Formation water information and key salt parameters of the tight reservoir test section in the study area

[0115] hashtag Layer number Total mineralization / mg·L-1 Macro capture cross section / cu MY2 S1 289333.77 120.5 MY2 S2 378740.21 150.9 MH48 S2 254165.81 108.5 MH52 S1 284099.57 118.7 MH281 S1 266203.67 112.6 MH52 S1 284099.57 118.7 MH52 S3 279283.52 117.1 MH52 S3-1 267621.63 113.1 MH54 S1 345359.76 139.5

[0116] Using well logging to measure the macroscopic capture cross section Sigma 测井 The macroscopic capture cross section Sigma of the formation is calculated theoretically. 理论 Make a difference and construct the oil content sensitive parameter:

[0117] Sigma 差异 =Sigma 测井 -Sigma 理论 (5)

[0118] Among them, Sigma 理论 Sigma is the theoretical value of the macroscopic capture cross section of the formation calculated under the assumption that the formation is saturated with brine, cu; 测井 is the macroscopic capture cross section value measured by well logging, cu; Sigma 差异 is the theoretically calculated Sigma 理论 and Sigma measured by well logging 测井 The difference.

[0119] Since the macroscopic capture cross section of crude oil is much smaller than that of high-salinity formation water (i.e., the total salinity in Table 1), when the formation is mainly oil, Sigma 差异 When the stratum is mainly water, Sigma 差异 Should be equal to 0 or greater than 0. When there is both water and oil in the formation, Sigma 差异 It is a value close to 0 and fluctuates around 0.

[0120] (4) Extracting Sigma of the Tested Layer 差异 The effective porosity is intersected to form a high-salinity tight reservoir fluid property identification plate. The plate obtained in this embodiment is as follows Figure 2 As shown, the horizontal axis is the effective porosity and the vertical axis is Sigma 差异 It can be seen that the effective porosity of the oil layer is large, Sigma 差异Obviously less than 0, the effective porosity of the poor oil layer is small, Sigma 差异 Significantly less than 0, the effective porosity of oil and water in the same layer is medium to large, Sigma 差异 is close to 0. Figure 2 It can be seen that some points of poor oil layers overlap with oil layers. This is because the research area of ​​the embodiment is alkaline lake sediments, and the reservoir contains salt substances. During oil testing, salt substances flow into the wellbore with the fracturing fluid. Since the temperature of the wellbore is lower than that of the formation, the solubility of the salt substances decreases, and then the salt substances precipitate and block the wellbore, resulting in that some reservoirs with better physical properties cannot obtain industrial oil flow. Therefore, in the application Figure 2 On the basis of identifying the reservoir fluid properties, salinity evaluation is also required.

[0121] (5) The salt sensitivity factor is constructed using the ratio of chloride ion yield to the total porosity of the formation. Since the chloride ion yield measured by lithology scanning is affected by the mineralization and porosity of the formation water, under the premise of the same formation water mineralization, the greater the porosity, the higher the chloride ion yield. Therefore, the use of chloride ion yield requires eliminating the influence of porosity. The specific formula is as follows:

[0122]

[0123] Among them, SSF is Y cl is the relative yield of chlorine measured by element logging, kg / kg, φ 总 is the total porosity of the formation, %.

[0124] Extract the salt sensitivity factor and effective porosity of the tested oil layer and intersect them to form a salt evaluation chart for high-salinity tight reservoirs. The chart obtained in this embodiment is as follows: Figure 3 As shown, the horizontal axis is the effective porosity, and the vertical axis is the salt sensitivity factor. It can be seen that the salt sensitivity factor of the poor oil layer is significantly greater than that of the oil-water layer and the oil layer. This is because the salt substances crystallize and block the wellbore due to the temperature drop. The salt sensitivity factor of the oil-water layer is generally greater than that of the oil layer. This is because salt substances are dissolved in the formation water but the concentration is low. When the formation water flows into the wellbore, it will not block the wellbore. Figure 3 , well logging evaluation can be carried out on wells that have not yet been tested for oil.

[0125] In order to verify the application effect of the present invention, a typical example well is described below. Figure 4As shown. Since the area where the example well is located is alkaline lake sedimentation, conventional logging is first used to identify an alkaline mineral layer in the formation, which is a non-valuable layer (the 7th track from left to right). The alkaline mineral layer should be avoided first when selecting layers for oil testing. Then, the logging data is used to evaluate the effective porosity (the 8th track from left to right) and the movable oil porosity (the 9th track from left to right). These two types of information are used to determine the sweet spot (the 12th track from left to right, the black filled layer). Sigma is calculated using equations (3) to (5) 差异 , in general, Sigma 差异 It shows the characteristics of positive and negative difference swing, and the positive value accounts for a large proportion (grey filling is positive value, white filling is negative value), indicating that the sweet spot segment has obvious water content. 差异 With effective porosity data points to Figure 2 The salinity is mainly located in the oil-water layer. Then, using formula (6), we evaluate the salinity and find that the salt sensitivity factor values ​​of the sweet spots of 5145-5180m and 5400-5500m are 6-10, indicating that the salinity of the above formations is high and the oil test is likely to block the wellbore. Figure 3 Therefore, in order to prevent wellbore blockage, the oil tests at 5145-5180m and 5400-5500m were abandoned, and the sweet spot at 5040-5130m was finally determined as the oil test layer. The oil test results showed that the oil and water were in the same layer, which shows the practicality and correctness of this method.

[0126] Based on the same concept as the embodiment of the method of the present invention, the embodiment of the present invention also provides a system for identifying the properties of fluids in a high-salinity tight reservoir, such as Figure 5 As shown, including:

[0127] A first determination unit 501 is used to determine the mineral content of the formation and the macroscopic capture cross section of the logging measurement based on the element logging data;

[0128] A second determining unit 502 is used to determine a theoretical value of a macroscopic capture cross section when the pores are saturated with salt water according to the mineral content and the macroscopic capture cross section of the formation water;

[0129] A first plate forming unit 503 is used to intersect the effective porosity with the difference value to form a fluid property identification plate of a high-salinity tight reservoir, wherein the difference value is the difference between the macroscopic capture cross section and a theoretical value of the macroscopic capture cross section;

[0130] The second plate forming unit 504 is used to form a salt evaluation plate by intersecting the effective porosity and the salt sensitivity factor, wherein the salt sensitivity factor is constructed using the relative yield of the chlorine element extracted from the element logging data;

[0131] The identification unit 505 is used to determine the fluid properties of the formation using the fluid property identification chart of the high-salinity tight reservoir, and then determine whether the sweet spot needs oil testing using the salt content evaluation chart.

[0132] Based on the same inventive concept, another exemplary embodiment of the present invention provides an electronic device. Figure 6 As shown, the electronic device includes at least one processor 601, at least one communication interface 602, at least one memory 603 and at least one communication bus 604; wherein the processor 601, the communication interface 602 and the memory 603 communicate with each other through the communication bus 604;

[0133] Memory 603, used for storing computer programs;

[0134] The processor 601 is used to implement the method for identifying the properties of fluid in a high-salinity tight reservoir when executing the program stored in the memory 603.

[0135] Optionally, the communication interface may be an interface of a communication module, such as an interface of a GSM module; the processor may be a processor CPU, or an application specific integrated circuit ASIC (Application Specific Integrated Circuit), or one or more integrated circuits configured to implement the embodiments of the present invention. The memory may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory. The memory stores a program, and the processor calls the program stored in the memory to execute some or all of the above method embodiments.

[0136] Based on the same inventive concept, the embodiment of the present application further provides a storage medium, including a computer program, which implements part or all of the above method embodiments when executed by a processor. Optionally, the storage medium may be a non-temporary computer-readable storage medium, for example, the non-temporary computer-readable storage medium may be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, etc.

[0137] Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent substitutions for some of the technical features therein; and these modifications or substitutions 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 identifying fluid properties in a high-salinity tight reservoir, characterized in that: include: Determine the mineral content of the formation and the macroscopic capture cross section of the logging measurement based on element logging data; Determining a theoretical value of a macroscopic capture cross section when the pores are saturated with salt water according to the mineral content and the macroscopic capture cross section of the formation water; Intersecting the effective porosity with the difference value to form a fluid property identification chart for a high-salinity tight reservoir, wherein the difference value is the difference between the macroscopic capture cross section and a theoretical value of the macroscopic capture cross section; A salt evaluation chart formed by intersecting effective porosity and salt sensitivity factor, wherein the salt sensitivity factor is constructed using the relative yield of chlorine extracted from element logging data; The fluid property identification chart of the high-salinity tight reservoir is used to determine the fluid property of the formation, and the salt content evaluation chart is then used to determine whether the sweet spot section needs oil testing.

2. The method for identifying fluid properties in a high-salinity tight reservoir according to claim 1, characterized in that: Obtain conventional logging data, element logging data and formation water salinity data of tested wells; Obtain the mineral types and mineral contents of the formation based on element logging data; To judge the rationality of the mineral content; If the mineral content is reasonable, the macroscopic capture cross section of the well logging measurement is determined using the mineral content; if the mineral content is unreasonable, the mineral content is recalculated.

3. The method for identifying fluid properties in a high-salinity tight reservoir according to claim 2, characterized in that: The determination of the rationality of the mineral content includes the following steps: Obtain volume photoelectric absorption cross-section index logging value; Calculate the theoretical value of the volume photoelectric absorption cross-section index based on the mineral content; Calculating the relative error between the theoretical value of the volume photoelectric absorption cross-section index and the logging value of the volume photoelectric absorption cross-section index; Set the limit value of relative error; The relative error and the limit value are judged. If the relative error is less than the limit value, the mineral content obtained is considered reasonable; if the relative error is greater than or equal to the limit value, the mineral content is considered unreasonable, and the mineral content is recalculated until the relative error is less than the limit value.

4. The method for identifying fluid properties in a high-salinity tight reservoir according to claim 3, characterized in that: The volume photoelectric absorption cross-section index theoretical value is calculated based on the mineral content as follows: the volume photoelectric absorption cross-section index theoretical value U is calculated based on the volume percentage of the mineral content in the formation, the volume photoelectric absorption cross-section index of the mineral, the volume photoelectric absorption cross-section index of the fluid in the pores, and the total porosity of the formation. 理论 ; The calculation formula is as follows: Among them, v i is the volume percentage of the i-th mineral content in the formation calculated by element logging; U i is the volume photoelectric absorption cross section index of the i-th mineral; U f is the volume photoelectric absorption cross-section index of the fluid in the pore; φ 总 is the total porosity of the formation, 1≤i≤j, where i is an integer and j is the type of mineral.

5. The method for identifying fluid properties in a high-salinity tight reservoir according to claim 3, characterized in that: The calculation formula of the relative error is as follows: Where U 理论 is the theoretical value of volume photoelectric absorption cross section index; U 测井 is the rock volume photoelectric absorption cross-section index measured by lithology density logging; a is the limit value of relative error.

6. The method for identifying fluid properties in a high-salinity tight reservoir according to claim 1, characterized in that: The theoretical value of the macroscopic capture cross section when the pores are saturated with brine is determined based on the mineral content and the macroscopic capture cross section using the following formula: In the formula, Sigma 理论 Theoretical value of the macroscopic capture cross section when the pores are saturated with salt water; v i Sigma is the volume percentage of the i-th mineral content in the formation calculated by element logging; i is the macroscopic capture cross section of the i-th mineral; 1≤i≤j, i is an integer, j is the type of mineral; Sigma 地层水 is the macroscopic capture cross section of formation water, φ 总 is the total porosity of the formation; Among them, the macroscopic capture cross section Sigma of formation water 地层水 The calculation is done using the following formula: Sigma 地层水 =k+b·Cw Where k is the macroscopic capture cross section of crude oil; b is the regression coefficient; Cw is the salinity of formation water.

7. The method for identifying fluid properties in a high-salinity tight reservoir according to claim 1, characterized in that: The method of intersecting the effective porosity with the difference value to form a fluid property identification chart for a high-salinity tight reservoir comprises the following steps: The difference between the macroscopic capture cross section value measured by well logging and the theoretical value of the macroscopic capture cross section under the condition of pore saturated with salt water is calculated as the difference value; The difference value and the effective porosity are intersected to form a fluid property identification chart for high-salinity tight reservoirs.

8. The method for identifying fluid properties in a high-salinity tight reservoir according to claim 1, characterized in that: The salt evaluation chart formed by intersecting the effective porosity and salt sensitivity factor includes the following steps: Extract the relative yield of chlorine from elemental logging data; The salinity sensitivity factor is calculated according to the relative yield of the chlorine element and the total porosity of the formation; the calculation formula of the salinity sensitivity factor is as follows: Among them, SSF is the salinity sensitivity factor, Y cl is the relative yield of chlorine measured by element logging, φ 总 is the total porosity of the formation.

9. A high-salinity tight reservoir fluid property identification system, characterized in that: include: A first determination unit is used to determine the mineral content of the formation and the macroscopic capture cross section of the logging measurement based on the element logging data; A second determination unit is used to determine a theoretical value of a macroscopic capture cross section when the pores are saturated with salt water according to the mineral content and the macroscopic capture cross section of the formation water; A first plate forming unit is used to intersect the effective porosity with the difference value to form a fluid property identification plate of a high-salinity tight reservoir, wherein the difference value is the difference between the macroscopic capture cross section and a theoretical value of the macroscopic capture cross section; The second plate forming unit is used to form a salt evaluation plate by intersecting the effective porosity and the salt sensitivity factor, wherein the salt sensitivity factor is constructed using the relative yield of the chlorine element extracted from the element logging data; The identification unit is used to determine the fluid properties of the formation using the fluid property identification chart of the high-salinity tight reservoir, and then use the salt content evaluation chart to determine whether the sweet spot section needs oil testing.

10. An electronic device, characterized in that: It includes a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other via the communication bus; Memory for storing computer programs; The processor is used to implement the method for identifying the properties of high-salinity tight reservoir fluids according to any one of claims 1 to 8 when executing the program stored in the memory.

11. A computer-readable storage medium, characterized in that: A computer-readable program is stored, and when the computer-readable program is run, the method for identifying fluid properties of a high-salinity tight reservoir as described in any one of claims 1 to 8 is executed.

Images