A method and system for identifying properties of high salinity compact reservoir fluids

Abstract

The present application 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 fluid properties of high-salinity tight reservoirs. The macroscopic capture cross-section theoretical value under the condition of high-salinity formation water is calculated by using mineral content, then the difference value between the macroscopic capture cross-section theoretical value and the measured value of the macroscopic capture cross-section is used as a sensitive factor for oil-bearing property judgment, and the difference value and the effective porosity are used to form a fluid property identification chart, so that the fluid properties of tight oil reservoirs under the condition of high-salinity background can be accurately identified; the ratio of the relative yield of chlorine element to the effective porosity is used as a salt-bearing sensitive factor, and the salt-bearing sensitive factor and the effective porosity are used to form a salt-bearing evaluation chart, so that the salt-bearing degree of the sweet spot section can be judged, and it is determined whether oil testing is necessary. The method can accurately identify the fluid properties under the condition of high-salinity tight reservoir background, and give oil testing suggestions.

Description

Technical Field

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

[0002] Currently, fluid property identification methods fall into four main categories. The first is electrical logging. Electrical logging is the most commonly used method for fluid property identification. For sandstone reservoirs, resistivity is often used to determine oil content. However, for unconventional reservoirs, resistivity logging values ​​are a comprehensive reflection of lithology, physical properties, oil content, and source rock characteristics. Resistivity levels cannot truly reflect changes in formation fluid properties. Furthermore, electrical logging can be affected by highly salinized formation water or mud, causing the resistivity of flushed zones and even invaded zones to be lower than that of the undisturbed formation, creating the illusion of improved reservoir properties. The second category is nuclear magnetic resonance logging. Nuclear magnetic resonance logging, especially 2D NMR logging in the T1-T2 domain, clearly distinguishes between different fluid properties, such as movable oil, movable water, bound oil, and bound water, and has found promising applications in shale and tight oil fields. However, NMR logging couples wettability, oil content, pore structure, and fluid viscosity, resulting in NMR logging responses that cannot fully reflect oil content. Furthermore, when formation water salinity is high, the high conductivity of the formation water creates eddy current loading, which degrades the signal-to-noise ratio of the NMR logging data and affects the T2 spectrum. This significantly limits fluid identification using NMR logging. Secondary gamma spectroscopy can measure the yields of multiple elements in the formation. Using yield ratios, sensitivity factors (such as the C / O ratio as a sensitivity factor for oil content and the Si / Ca ratio as a sensitivity factor for reservoir sand content) can be constructed to assess reservoir oil content. However, for shale oil and tight oil, the carbon element originates not only from oil and gas but also from source rocks and carbon-containing minerals. Therefore, the commonly used C / O ratio is not indicative of reservoir oil content. The fourth method is elemental logging. This logging method can interpret the mineral content of the formation and use this content to invert characteristic curves that characterize formation oil content, such as resistivity, acoustic wave, and density, thereby indirectly reflecting changes in oil and gas content. Alternatively, the measured macroscopic capture cross section can be used to directly reflect the gas content (the macroscopic capture cross section of a gas-bearing formation is significantly smaller than that of a water-bearing formation). This method is mainly used in gas-bearing formations and works well, but is not very effective in tight reservoirs and high-salt reservoirs. Summary of the Invention

[0003] In response to 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 based on 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 a salt sensitivity factor constructed using the relative yield of chlorine extracted from elemental logging data;

[0008] The fluid property identification chart of the high-salinity tight reservoir is used to determine the fluid properties 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] Determine 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] Calculating a theoretical value of a 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 logged 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] Furthermore, the theoretical value of the volume photoelectric absorption cross-section index is calculated based on the mineral content as follows: the theoretical value of the volume photoelectric absorption cross-section index 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 ;

[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 the volume photoelectric absorption cross section index; U 测井 is the rock volume photoelectric absorption cross-section index measured by lithologic 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 brine is determined based on the mineral content and the macroscopic capture cross section using the following formula:

[0027]

[0028] Where Sigma 理论 Theoretical value of the macroscopic capture cross section when the pores are 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; 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;

[0029] Among them, the macroscopic capture cross section Sigma of formation water 地层水 Calculated 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; and Cw is the salinity of formation water, in mg / L.

[0032] Furthermore, the intersecting of the effective porosity and the difference value to form a fluid property identification chart for the 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 pores saturated with brine 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 system for identifying fluid properties in high-salinity tight reservoirs, comprising:

[0041] A first determining 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 determining unit is configured 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 configured to intersect the effective porosity with the difference value to form a fluid property identification plate 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;

[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 determine whether the sweet spot needs oil testing using the salt content evaluation chart.

[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. When the computer-readable program is run, the method for identifying fluid properties in a high-salinity tight reservoir is executed.

[0050] Beneficial effects of the present invention:

[0051] The present invention uses mineral content to calculate the theoretical value of the macroscopic capture cross section under high-mineralization formation water conditions, 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 oil content judgment, without considering the influence of lithology on resistivity logging; it can also avoid the error of C element C / O in mixed rock formations caused by source rocks and carbon-containing minerals; it can accurately identify the fluid properties of tight oil reservoirs under high-mineralization background; the porosity of the present invention can be calculated by conventional density and sonic logging, or directly by element logging, without considering changes in pore structure, wettability, and fluid viscosity, thereby solving the problem in nuclear magnetic logging that the nuclear magnetic logging response cannot fully reflect the oil content 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 in part will become apparent from the description, or will be 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 following briefly introduces the drawings required for use in the embodiments or the description of the prior art. 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 any creative work.

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

[0055] Figure 2 The following figure shows a fluid property identification chart for 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 content evaluation chart of a high-salinity tight reservoir in a block according to an embodiment of the present invention is shown; wherein the abscissa represents effective porosity and the ordinate represents 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 track is the alkaline ore layer indicator, the 8th track is the effective porosity, the 9th track is the movable oil porosity, and the 10th track 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] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only 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 making creative efforts shall fall within the scope of protection of the present invention.

[0061] The present invention aims to provide a method for identifying fluid properties in high-salinity, tight reservoirs based on elemental logging. This method addresses the difficulties encountered by conventional electrical logging methods, which cannot distinguish oil and water based on resistivity, and by nuclear magnetic resonance logging methods, which cannot distinguish fluids due to coupling effects such as surface relaxation, pore structure, and oil content. It also provides a basis for avoiding high-salinity reservoirs during oil testing.

[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] Determining a theoretical value of a macroscopic capture cross section when the pores are saturated with salt water based on 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 a salt sensitivity factor constructed using the relative yield of chlorine extracted from elemental logging data;

[0067] The fluid property identification chart of the high-salinity tight reservoir is used to determine the fluid properties 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 well logging data, element logging data, and formation water salinity data of tested wells;

[0070] Wherein, conventional logging data includes lithologic density logging information, and porosity information is obtained using conventional logging data, wherein the porosity information includes total porosity and effective porosity of the formation;

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

[0072] S2: Process the element logging data to obtain the mineral types and contents as well as the macroscopic capture cross section Sigma of the 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 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 i-th 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, which can be assigned and calculated based on the commonly used value; 总 is the total porosity of the formation, %, which can be calculated by conventional well logging.

[0077] S3: Compare the theoretical value of the volume photoelectric absorption cross-section index with the volume photoelectric absorption cross-section index logging value, and determine whether the mineral content needs to be recalculated based on 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 lithologic density logging. Lithologic 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 brine 理论 ; The macroscopic capture cross section value Sigma measured by well logging 测井 The theoretical value of the macroscopic capture cross section Sigma when the pores are saturated with brine 理论 Sigma 差异 As a sensitive parameter of oil content. 差异 Intersection with effective porosity forms 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 salinity of formation water increases significantly, the macroscopic capture cross section of water will also increase significantly. This is especially true in the sedimentary environments of salty and alkaline lakes, where the formation water has a very high salinity and the salinity of formation water can reach 200,000-350,000 mg / L. This leads to a huge difference in the macroscopic capture of formation water and oil, so the macroscopic capture cross section can be used as a 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] Where Sigma 理论 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; 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 of crude oil, cu; b is the regression coefficient; Cw is the salinity of formation water, 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 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: Use elemental logging data to extract the relative yield of chlorine and construct a salt sensitivity factor. Intersect the salt sensitivity factor with the effective porosity to form a salt evaluation chart.

[0094] For wells that require interpretation, the fluid properties of the reservoir are first determined using the fluid property identification chart for high-salinity tight reservoirs in step S4. Then, the salt content identification chart in step S5 is used to determine whether oil testing is necessary in 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, nuclear magnetic resonance logging, and formation water salinity data from tested wells, and use conventional logging to obtain porosity information.

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

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

[0099] In this example, the common minerals in the Fengcheng Formation are quartz, feldspar, dolomite, calcite, clay minerals, and pyrite. Due to the lack of core data from the target area, it is not possible to use core data to calibrate the calculated mineral content. Furthermore, the calculated mineral content will also affect the subsequent oil content evaluation, so it is necessary to determine whether the mineral content is accurate. The specific steps for determining this are as follows:

[0100] ① Using the mineral content calculated by lithologic 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 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 i-th 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 lithologic density logging. Lithologic 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%. Lithologic density logging can obtain the measured rock volume photoelectric absorption cross-section index U.

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

[0108] Since the oil-water relationship in the tight oil reservoir of this example is complex and the tight oil reservoir is non-buoyant, 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] Where 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] Where Sigma 地层水 is the macroscopic capture cross section of formation water, cu; 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, which can be obtained using the regional mean formation water salinity 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 Macroscopic 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-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 composed of 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) Extract Sigma of the tested oil 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 , we can see 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 the oil and water layer is medium to large, Sigma 差异 is close to 0. Figure 2 It can be seen that some of the points of poor oil layers overlap with the oil layers. This is because the research area of ​​the embodiment is an alkaline lake sediment, 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 the inability to obtain industrial oil flow in some reservoirs with better physical properties. 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 lithologic scanning is affected by the mineralization and porosity of the formation water, under the premise of the same mineralization of the formation water, 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 element 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 oil-tested 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 decrease in temperature. 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 , it is possible to conduct logging evaluation on wells that have not yet been tested.

[0125] In order to test 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 sediments, 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 effective porosity (the 8th track from left to right) and movable oil porosity (the 9th track from left to right) are obtained by evaluating the logging data. 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 formulas (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 The plate is located in a poor oil-bearing zone. Therefore, to prevent wellbore blockage, the 5145-5180m and 5400-5500m oil tests were abandoned. The 5040-5130m sweet spot was ultimately determined as the oil-bearing zone. The oil test results showed that the oil and water layers were in the same layer, demonstrating 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 high-salinity tight reservoir fluid property identification system, such as Figure 5 Shown, including:

[0127] The first determining unit 501 is configured 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 configured to determine a theoretical value of a macroscopic capture cross section when the pores are saturated with salt water based on the mineral content and the macroscopic capture cross section of the formation water;

[0129] A first plate forming unit 503 is configured to intersect the effective porosity with the difference value to form a fluid property identification plate 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;

[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 configured 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 requires oil testing using the salinity 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 via the communication bus 604;

[0133] Memory 603, used to store computer programs;

[0134] The processor 601 is configured to implement the method for identifying fluid properties 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 CPU, or an 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, such as at least one disk storage. The memory stores a program, and the processor calls the program stored in the memory to execute some or all of the above-mentioned method embodiments.

[0136] Based on the same inventive concept, an embodiment of the present application further provides a storage medium including a computer program, wherein when the program is executed by a processor, some or all of the above-mentioned method embodiments are implemented. Optionally, the storage medium may be a non-transitory computer-readable storage medium, for example, 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 replacements for some of the technical features therein; and these modifications or replacements do not cause the essence of the corresponding technical solutions to 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 high-salinity tight reservoirs, 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 brine based on the mineral content and the macroscopic capture cross section of the formation; Calculating the difference between the macroscopic capture cross section value measured by well logging and the theoretical value of the macroscopic capture cross section when the pores are saturated with brine as a difference value; intersecting the difference value with the effective porosity to form a fluid property identification plate for high-salinity tight reservoirs; Extracting the relative yield of chlorine from the element logging data; calculating the salinity sensitivity factor based on the relative yield of chlorine and the total porosity of the formation; A salt evaluation chart formed by intersecting effective porosity and salt sensitivity factors; The fluid property identification chart of the high-salinity tight reservoir is used to determine the fluid properties 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; Determine 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 rationality of the mineral content is judged by the following steps: Obtain volume photoelectric absorption cross-section index logging value; Calculating a theoretical value of a 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 logged 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 theoretical value of the volume photoelectric absorption cross-section index is calculated based on the mineral content as follows: the theoretical value of the volume photoelectric absorption cross-section index 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. ; The calculation formula is as follows: in, is the volume percentage of the i-th mineral content in the formation calculated by element logging; is the volume photoelectric absorption cross-section index of the i-th mineral; is the volume photoelectric absorption cross-section index of the fluid in the pore; is the total porosity of the formation, , 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, is the theoretical value of the volume photoelectric absorption cross section index; The rock volume photoelectric absorption cross-section index measured by lithologic density logging; 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: Where, Theoretical value of macroscopic capture cross section when pores are saturated with brine; is the volume percentage of the i-th mineral content in the formation calculated by element logging; is the macroscopic capture cross section of the i-th mineral; , where i is an integer and j is the type of mineral; is the macroscopic capture cross section of formation water, is the total porosity of the formation; Among them, the macroscopic capture cross section of formation water Calculated using the following formula: Where, is the macroscopic capture cross section value of crude oil; is the regression coefficient; is the mineralization of formation water.

7. The method for identifying fluid properties in a high-salinity tight reservoir according to claim 1, characterized in that: The calculation formula of the salinity sensitivity factor is as follows: in, is the salinity sensitivity factor, is the relative yield of chlorine element measured by element logging, is the total porosity of the formation.

8. A high-salinity tight reservoir fluid property identification system, characterized in that: include: A first determining 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 determining unit is configured 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; The first plate forming unit is used to calculate 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 state of pore saturated with salt water as a difference value; Intersecting the difference value and the effective porosity to form a fluid property identification chart for high-salinity tight reservoirs; The second plate forming unit is used to extract the relative yield of chlorine element from the element logging data; and calculate the salinity sensitivity factor based on the relative yield of chlorine element and the total porosity of the formation; A salt evaluation chart formed by intersecting effective porosity and salt sensitivity factors; 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 determine whether the sweet spot needs oil testing using the salt content evaluation chart.

9. An electronic device, characterized in that: The processor, the communication interface, the memory and the communication bus are connected to each other via the communication bus. memory for storing computer programs; The processor is configured to implement the method for identifying fluid properties in a high-salinity tight reservoir according to any one of claims 1 to 7 when executing a program stored in the memory.

10. 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 in a high-salinity tight reservoir according to any one of claims 1 to 7 is executed.

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