A method and system for identifying fluids in gas-bearing strata of tight sandstone

Abstract

This invention provides a method and system for fluid identification in tight sandstone gas-bearing formations. It employs a combined three-porosity logging method, a combined nuclear magnetic resonance (NMR) logging and density logging method, and a combined NMR logging and three-porosity logging method for fluid identification in tight sandstone gas-bearing formations. The method constructs multiple gas-bearing formation sensitive factors through theoretical analysis, amplifying the differences between gas-bearing formations and building fluid identification charts. In the interpretation of new target layers, fluid discrimination is performed based on each chart, and the final interpretation result is determined using the chart consistency rate method or the absolute majority voting method. The fluid sensitive factors constructed in this invention, and the cross-plots built based on these factors, can effectively distinguish fluid types. The comprehensive discrimination strategy organically combines the results of multiple methods, eliminating the limitations of any single method. The interpretation results have been verified by oil testing, showing a significantly improved consistency rate.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of oil exploration and well drilling, and particularly relates to a method and system for identifying fluid in tight sandstone gas-bearing layer. BACKGROUND

[0002] In the super-deep and super-low porosity sandstone reservoir, the lithology is tight, the porosity is small, the throat is thin, the connectivity is poor, and the heterogeneity is strong. Moreover, the pore structure is complex, and the mineral composition of clay minerals and chlorinated salts is complex. In the resistivity logging response, the contribution of the rock solid skeleton is much greater than that of the fluid. The resistivity logging response characteristics of gas layers and water layers are not obviously different. Therefore, it is difficult to identify fluid by using resistivity logging, and the original well logging evaluation method for natural gas reservoirs is no longer applicable.

[0003] In the fluid identification of tight sandstone, the commonly used method is to make a resistivity-porosity crossplot. In addition, according to the special circumstances of each region, the gas-water index method, the fluid compressibility method, the index discrimination method for identifying oil and gas layers, the saturation overlap method, the resistivity-porosity crossplot method, the lateral-inductive resistivity ratio method, and the longitudinal-transverse wave velocity ratio method are respectively proposed to reflect the differences between reservoir properties and gas, water, and dry layers from different angles. However, the tight sandstone reservoir in Kuqa Depression has ultra-low porosity, and the fluid in the pores is not sensitive to logging response. The application effect of the above methods is not good, and it is usually difficult to distinguish by resistivity logging when the physical properties are the same.

[0004] In addition to conventional logging technology, nuclear magnetic resonance logging can improve the accuracy of tight sandstone logging interpretation. Nuclear magnetic resonance logging is a new logging technology developed in the past 20 years. Nuclear magnetic T2 distribution not only reflects the pore structure, but also contains rich fluid information. The dual-TE observation mode designed for gas reservoir fluid identification considers that the diffusion coefficient of natural gas is significantly larger than that of oil and water, and spectral shift or diffusion analysis can effectively identify gas layers. However, due to the small porosity, the nuclear magnetic logging response of the fluid is not significant, and in actual exploration, only standard T2 logging, i.e. single-TE logging, is usually collected. The data obtained by this observation mode cannot be used for spectral shift or diffusion analysis.

[0005] The prior art has the following problems: for the ultra-low porosity and low permeability reservoir, the fluid is not obvious in the resistivity logging response due to the small porosity, and the reservoir fluid identification is difficult due to the influence of the pore structure. When the pore structure is good, the resistivity logging can clearly reflect the fluid property; when the pore structure is poor, the fluid type is not sensitive. Therefore, the fluid identification precision based on the resistivity is not high. Due to the low hydrogen index of natural gas, the porosity of the gas-bearing layer is seriously underestimated by the nuclear magnetic resonance logging, and the fluid identification precision is not high by using the nuclear magnetic resonance alone. The shift spectrum or diffusion analysis of the nuclear magnetic resonance double-TE logging data can effectively identify the gas layer, but in actual exploration, only the standard T2 logging, i.e. single-TE logging, is collected, and the shift spectrum or diffusion analysis cannot be performed.

[0006] For the ultra-low porosity and low permeability tight sandstone reservoir, the contribution of the fluid to the logging response is small due to the low porosity. The original logging fluid identification method, especially the resistivity identification effect, is not good, which limits the application of the logging data in the fluid identification of the gas reservoir. SUMMARY

[0007] In order to solve the problems in the prior art, the present application provides a tight sandstone gas-bearing layer fluid identification method and system, which can improve the resistivity identification effect, realize accurate identification of the reservoir fluid, eliminate the limitation of a single method, and significantly improve the coincidence rate.

[0008] To achieve the above object, the present application provides the following technical scheme:

[0009] A tight sandstone gas-bearing layer fluid identification method, comprising the following steps,

[0010] S1, a fluid identification chart is constructed:

[0011] The porosity values of the acoustic logging, the density logging and the neutron logging of the reservoir to be measured are obtained;

[0012] The difference between the apparent neutron porosity and the apparent acoustic porosity is a first porosity difference ;

[0013] The difference between the apparent neutron porosity and the apparent density porosity is a second porosity difference ;

[0014] The porosity ratio is constructed , and the expression is

[0015] ;

[0016] In the formula, , , The apparent acoustic porosity, the apparent density porosity and the apparent neutron porosity are respectively

[0017] According to the obtained first porosity difference value, second porosity difference value and porosity ratio value, crossplot and - crossplot are established respectively, and - crossplot is constructed to complete the fluid identification crossplot.

[0018] S2, fluid identification of the reservoir to be measured:

[0019] Based on the established - crossplot and - crossplot, the crossplot with high crossplot coincidence rate is selected according to the set crossplot coincidence rate to identify the fluid of the reservoir to be measured.

[0020] Preferably, the step S1 further comprises:

[0021] obtaining the porosity value of the nuclear magnetic resonance logging of the reservoir to be measured;

[0022] calculating the geometric mean value of the movable fluid in the nuclear magnetic resonance logging ;

[0023] calculating the apparent density porosity-nuclear magnetic porosity difference value and the irreducible fluid saturation ;

[0024] wherein, the expression of the apparent density porosity-nuclear magnetic porosity difference value is,

[0025] ;

[0026] in the formula, is the apparent density porosity, is the nuclear magnetic resonance porosity;

[0027] wherein, the expression of the irreducible fluid saturation is,

[0028] ;

[0029] in the formula, is the volume of the irreducible fluid;

[0030] According to the obtained geometric mean value , apparent density porosity-nuclear magnetic porosity difference value and irreducible fluid saturation, crossplot and - crossplot are established respectively. - crossplot.

[0031] Preferably, the geometric mean of the movable fluid The expression for calculation is,

[0032] ;

[0033] In the formula, T² is the geometric mean of the moving fluid; T 2j Let A be the T2 relaxation time constant of the j-th relaxation component. j For the corresponding T 2j The component porosity; T 2c Let T2 be the cutoff value for bound fluid and movable fluid, and c be the corresponding T value for T2 cutoff. 2j The ordinal number.

[0034] Preferably, the method is characterized in that, based on the established intersection map, the fluid of the reservoir to be tested is identified by an absolute majority voting method. If half or more of the voting results are consistent, the fluid identification result with an absolute majority is output; if less than half of the voting results are consistent, the fluid identification result of the map with the highest map conformity rate is output.

[0035] Preferably, the expression for the set graphic conformity rate is:

[0036]

[0037] In the formula, V R For the compliance rate of the illustrations; This represents the number of water layers falling within the water layer region in the diagram; This represents the number of dry layers falling within the dry layer region in the diagram; N represents the number of gas layers falling within the gas layer region in the map; N represents the total number of reservoirs in the map.

[0038] Preferably, the expression for the apparent acoustic porosity is:

[0039] ;

[0040] The expression for apparent density porosity is as follows:

[0041] ;

[0042] The expression for the apparent neutron porosity is as follows:

[0043] ;

[0044] In the formula, , , These are, respectively, the sonic transit time logging values ​​of the reservoir to be tested, the sonic transit time of the rock skeleton, and the sonic transit time of the mixture of mud filtrate and formation water;

[0045] 、 、 respectively are the density logging value of the reservoir to be measured, the density of the rock skeleton, the density of the mud filtrate and formation water mixture;

[0046] 、 、 respectively are the neutron logging value of the reservoir to be measured, the neutron logging value of the rock skeleton, the neutron logging value of the mud filtrate and formation water mixture.

[0047] A tight sandstone gas-bearing layer fluid identification system, comprising,

[0048] a fluid identification chart construction unit for constructing a fluid identification chart; the fluid identification chart construction unit comprises,

[0049] a first acquisition module for acquiring the porosity values of acoustic logging, density logging and neutron logging of the reservoir to be measured;

[0050] a first calculation module for calculating the difference between apparent neutron porosity and apparent acoustic porosity to obtain a first porosity difference ;

[0051] a second calculation module for calculating the difference between apparent neutron porosity and apparent density porosity to obtain a second porosity difference ;

[0052] a third calculation module for constructing a porosity ratio , the expression of which is,

[0053] ;

[0054] wherein, 、 、 respectively are apparent acoustic porosity, apparent density porosity and apparent neutron porosity;

[0055] a first crossplot chart establishment module for establishing - a crossplot chart and - a crossplot chart respectively according to the obtained first porosity difference, second porosity difference and porosity ratio;

[0056] and a fluid identification unit of the reservoir to be measured, comprising a first fluid identification module for establishing - a crossplot chart and - The crossplot plate is selected according to the set crossplot coincidence rate, and a crossplot plate with high crossplot coincidence rate is selected to identify the fluid of the reservoir to be detected.

[0057] Preferably, the fluid identification plate construction unit further comprises,

[0058] The second acquisition module is configured to acquire a porosity value of the nuclear magnetic resonance logging of the reservoir to be detected.

[0059] The fourth calculation module is configured to calculate a geometric mean of the movable fluid in the nuclear magnetic resonance logging. ;

[0060] The apparent density porosity-nuclear magnetic porosity difference value and the irreducible fluid saturation ;

[0061] The expression of the apparent density porosity-nuclear magnetic porosity difference value is,

[0062] ;

[0063] In the formula, is the apparent density porosity, is the nuclear magnetic resonance porosity.

[0064] The expression of the irreducible fluid saturation is,

[0065] ;

[0066] In the formula, is the volume of the irreducible fluid.

[0067] The second crossplot plate establishment module is configured to establish a crossplot plate and a crossplot plate respectively according to the obtained geometric mean , the apparent density porosity-nuclear magnetic porosity difference value, and the irreducible fluid saturation.

[0068] Preferably, the fluid identification unit of the reservoir to be detected further comprises,

[0069] The second fluid identification module is configured to identify the fluid of the reservoir to be detected based on the established crossplot plates by using an absolute majority voting method. If more than half of the voting results are consistent, an absolute majority consistent fluid identification result is output. If less than half of the voting results are consistent, a fluid identification result of the crossplot plate with the highest crossplot coincidence rate is output.

[0070] Preferably, the fluid identification unit of the reservoir to be detected further comprises a crossplot coincidence rate calculation module configured to calculate the set crossplot coincidence rate.​​

[0071] Compared with the prior art, the present application has the following beneficial effects:

[0072] The present application provides a method for identifying fluid in tight sandstone gas-bearing reservoirs, which comprises two porosity difference values and one porosity ratio value constructed according to the porosity values of acoustic logging, density logging and neutron logging of the reservoir, and a crossplot is drawn according to the values, and the fluid in the reservoir to be measured is identified by comprehensive judgment using the coincidence rate of the crossplot.

[0073] The present application also provides another method for identifying fluid in tight sandstone gas-bearing reservoirs, which is a comprehensive fluid identification method using nuclear magnetic resonance logging and three porosity logging, and the nuclear magnetic resonance logging and density logging data are comprehensively considered on the basis of the three porosity logging joint method. In one aspect, the method is based on the response mechanism of nuclear magnetic resonance logging of natural gas reservoirs, and a fluid identification method is constructed by nuclear magnetic resonance porosity and movable fluid T2 distribution characteristics. In another aspect, effective fluid sensitive factors are constructed by combining the response differences of acoustic logging, density logging and neutron logging in gas layers and water layers, and gas layer identification is realized. A plurality of crossplots are constructed by a plurality of fluid sensitive factors, and the absolute majority voting method or the crossplot coincidence rate method is used to accurately determine the reservoir fluid.

[0074] The present application also provides another method for identifying fluid in tight sandstone gas-bearing reservoirs, which is a comprehensive fluid identification method using nuclear magnetic resonance logging and three porosity logging, and the nuclear magnetic resonance logging and density logging data are comprehensively considered on the basis of the three porosity logging joint method. In one aspect, the method is based on the response mechanism of nuclear magnetic resonance logging of natural gas reservoirs, and a fluid identification method is constructed by nuclear magnetic resonance porosity and movable fluid T2 distribution characteristics. In another aspect, effective fluid sensitive factors are constructed by combining the response differences of acoustic logging, density logging and neutron logging in gas layers and water layers, and gas layer identification is realized. A plurality of crossplots are constructed by a plurality of fluid sensitive factors, and the absolute majority voting method or the crossplot coincidence rate method is used to accurately determine the reservoir fluid.

[0075] The three methods of the present application construct a plurality of gas layer sensitive factors through theoretical analysis, amplify the differences of gas layers, and construct fluid identification crossplots. In the interpretation of new target layers, fluid is determined according to each crossplot, and the crossplot coincidence rate method or the absolute majority voting method is used to determine the final interpretation result. The fluid sensitive factors constructed by the present application can better distinguish fluid types based on the crossplots constructed by fluid sensitive factors, and the comprehensive determination strategy organically combines the results of a plurality of methods together, which can eliminate the limitations of a certain method, and the interpretation result is confirmed by oil testing, and the coincidence rate is obviously improved. BRIEF DESCRIPTION OF DRAWINGS

[0076] Figure 1 A flowchart of a comprehensive fluid type identification method for tight sandstone gas-bearing reservoirs according to an embodiment of the present application is shown;

[0077] Figure 2 a crossplot of the present application; - a crossplot of the present application;

[0078] Figure 3 a crossplot of the present application; - a crossplot of the present application;

[0079] Figure 4 a crossplot of the present application; T 2L,M -S BVI a crossplot of the present application;

[0080] Figure 5 a crossplot of the present application; T 2L,M - Δ DMR a crossplot of the present application;

[0081] Figure 6 a structural schematic diagram of a comprehensive fluid type identification device for tight sand gas-bearing reservoirs according to an embodiment of the present application;

[0082] Figure 7 a comprehensive fluid type identification result of a reservoir of a well according to an embodiment of the present application (without NMR logging data);

[0083] Figure 8 a comprehensive fluid type identification result of a reservoir of another well in the area according to an embodiment of the present application (with NMR logging data). DETAILED DESCRIPTION

[0084] The present application will be further described below in connection with specific embodiments, which are intended to explain but not to limit the present application. In order to further illustrate the technical means and effects taken by the present application to achieve the predetermined purposes, the specific embodiments, structure, features and effects of the tight sand gas-bearing reservoir fluid identification method according to the present application are described in detail as follows. In the following description, different “an embodiment” or “embodiments” do not necessarily refer to the same embodiment. In addition, the specific features, structures or characteristics in one or more embodiments can be combined in any suitable form.

[0085] One embodiment of the present application provides a tight sand gas-bearing reservoir fluid identification method, which adopts a three porosity logging joint method, and specifically includes the following steps:

[0086] S1, constructing a fluid identification crossplot;

[0087] S11, obtaining the porosity values of acoustic logging, density logging and neutron logging of the reservoir to be measured;

[0088] Subtracting the apparent sonic porosity from the apparent neutron porosity to obtain a first porosity difference, denoted as ;

[0089] Subtracting the apparent neutron porosity from the apparent density porosity to obtain a second porosity difference, denoted as ;

[0090] Constructing a porosity ratio, denoted as ;

[0091] wherein,

[0092] (1)

[0093] (2)

[0094] In formula (1) and (2), 、 、 are the apparent sonic porosity, the apparent density porosity and the apparent neutron porosity, respectively;

[0095] The apparent sonic porosity The apparent density porosity and the apparent neutron porosity are obtained by the following formulas, respectively,

[0096] 、 、

[0097] In the formulas,

[0098] 、 、 are the acoustic travel time logging value of the reservoir to be measured, the acoustic travel time of the rock skeleton, and the acoustic travel time of the mud filtrate and formation water mixture, respectively;

[0099] 、 、 are the density logging value of the reservoir to be measured, the density of the rock skeleton, and the density of the mud filtrate and formation water mixture, respectively; the theoretical value of the density of the rock skeleton is usually 2.65 g / cm3, and a more accurate value can be obtained by rock physics experiments;

[0100] 、 、 The neutron logging value of the to-be-detected reservoir, the neutron logging value of the rock skeleton, and the neutron logging value of the mixed solution of the mud filtrate and the formation water, respectively. The neutron logging value of the rock skeleton is usually -0.02, and the neutron logging value of the mixed solution of the mud filtrate and the formation water is usually 1.0. More accurate values can be obtained through rock physical experiments.

[0101] S12, according to the first porosity difference value, the second porosity difference value and the porosity ratio value, respectively, cross-plot of - and cross-plot of - are established.

[0102] In the natural gas reservoir, the response characteristics of acoustic wave, density and neutron logging are different between the gas layer and the water layer. In order to analyze their differences, three porosity sensitive parameters are constructed according to the apparent acoustic wave porosity, the apparent density porosity and the apparent neutron porosity, which are the first porosity difference value , the second porosity difference value and the porosity ratio value . From the logging theory, in the water layer, the two porosity difference parameters and are close to or equal to zero; in the gas layer, the two porosity difference values are both less than zero, and the higher the gas saturation is, the greater the two porosity difference values are. If the two difference curves are symmetrically displayed, the gas layer can be more intuitively identified. In addition, in order to further amplify the gas information, the porosity ratio value parameter is constructed for indication. In the water layer, is less than or equal to 1; in the gas layer, since the calculated , value is large, and the measured result is small, therefore, will be greater than 1. Therefore, the two porosity difference values and , and the difference ratio value are all parameters sensitive to the gas layer. A series of porosity difference and ratio fluid identification charts are constructed based on the above sensitive parameters.

[0103] In some embodiments, as shown in Figure 2 is the cross-plot of - , as shown in Figure 3 is the cross-plot of - , and as can be seen from Figure 2 , when the apparent neutron porosity and the apparent acoustic wave porosity difference value are close to or less than zero, the reservoir is a gas layer. As can be seen from Figure 3 , when the apparent neutron density porosity and the apparent density porosity difference value are less than 0% and When the value is greater than 1, the reservoir is a gas layer.

[0104] S2. Fluid identification of the reservoir under test:

[0105] According to the obtained - Intersection map and - The intersection charts are used to identify the fluid in the reservoir under test by comprehensively judging the chart matching rate.

[0106] Calculations show that, Figure 2 shown - The accuracy rate of the intersection map was 88.0%; such as Figure 3 shown - The agreement rate of the intersection maps was 89.6%. This shows that... - The intersection map has a higher accuracy.

[0107] This invention targets ultra-low porosity tight sandstone reservoirs, where the contribution of fluids to well logging responses is minimal due to low porosity. Existing well logging fluid identification methods, especially resistivity identification, are ineffective, limiting the application of well logging data for fluid identification in this type of gas reservoir. Therefore, this invention, on the one hand, aims to construct a fluid identification method based on the nuclear magnetic resonance (NMR) logging response mechanism of natural gas reservoirs, utilizing NMR porosity and the T2 distribution characteristics of mobile fluids; on the other hand, it combines the response differences of acoustic, density, and neutron logging in gas and water layers to construct effective fluid-sensitive factors, achieving gas layer identification. Multiple cross-plots are constructed using various fluid-sensitive factors, and an absolute majority voting method is employed to accurately identify reservoir fluids.

[0108] This embodiment specifically establishes fluid-sensitive parameters for ultra-deep, ultra-low porosity tight gas-bearing sandstone and identifies the fluid type of the sandstone through a comprehensive discrimination method.

[0109] Preferably, another embodiment of the present invention proposes a method for identifying fluids in tight sandstone gas-bearing formations. This embodiment employs a combined nuclear magnetic resonance (NMR) logging and three-porosity logging method for fluid identification. Based on the combined three-porosity logging method, it comprehensively considers both NMR logging and density logging data. Compared to the above embodiments, this embodiment's method for identifying fluids in tight sandstone gas-bearing formations further includes:

[0110] Construction of apparent density porosity-NMR porosity difference:

[0111] Nuclear magnetic resonance (NMR) logging has a relatively shallow detection depth. For CMR logging, its detection range is within 0.15 meters of the wellbore, specifically the flushed zone rather than the original formation. In the flushed zone, the porosity response of NMR logging is:

[0112]

[0113] In the formula, Formation porosity, The hydrogen content index, The hydrogen index is the concentration of the mixture of mud filtrate and formation water. This represents the gas saturation level. For nuclear magnetic resonance logging polarization factor,

[0114]

[0115] because =0.2, therefore, the higher the gas saturation, The smaller the porosity, the less it is than the actual porosity of the formation. When the value is 0.5-0.9, the coefficient of the right-hand side of the above formula is approximately 0.28-0.6, which shows the degree to which nuclear magnetic resonance logging underestimates the actual porosity.

[0116] In the formation flushing zone, the density logging response is:

[0117]

[0118] In the formula, This is the density of the mixture of mud filtrate and formation water, approximately 1.0 g / cm³. 3 ; The density of the rock skeleton is theoretically 2.65 g / cm³. 3 More accurate values ​​can be obtained from rock physics experiments.

[0119] In well logging interpretation theory, the method for calculating apparent density porosity obtained from density logging is as follows:

[0120]

[0121] because =0.2, therefore, gas saturation The higher, It is larger than the actual porosity. When When the value is 0.5-0.9, the coefficient of the right-hand side of the above formula is approximately 1.24-1.44, which shows the degree to which density logging overestimates the actual porosity.

[0122] Therefore, when the strata contain gas, the porosity measured by nuclear magnetic resonance is underestimated, while the calculated apparent density porosity is overestimated. To clearly indicate the fluid type, the difference between the two porosities is calculated. As a fluid indication sensitive indicator parameter, denoted as

[0123] (3)

[0124] In formula (3), is the apparent density porosity, is the nuclear magnetic resonance porosity;

[0125] Obviously, The larger the value, the better the gas-bearing property of the reservoir.

[0126] Calculation of the geometric mean of the nuclear magnetic resonance movable fluid T2:

[0127] According to the nuclear magnetic resonance relaxation mechanism, because oil, gas and water have different bulk relaxation (T 2bulk ) and diffusion coefficients (D), therefore, for the same pore structure of the rock, when saturated with different fluids, the nuclear magnetic resonance logging T2 distribution is different, and its T2 geometric mean ( T 2L,M ) is also different. Therefore, the nuclear magnetic resonance logging T2 geometric mean is a fluid-sensitive parameter, which can be used for fluid identification. The bulk relaxation of natural gas is about 40 ms, and its diffusion coefficient is significantly larger than that of oil and water. In addition, because the difference between the gas-saturated rock and the water-saturated rock is mainly in the movable fluid part of the nuclear magnetic resonance T2 distribution, therefore, calculating the geometric mean for the movable fluid part of the T2 distribution can more obviously reflect the difference of different fluids. The nuclear magnetic resonance movable fluid part T2 geometric mean T 2L,M , the calculation formula is:

[0128] (5)

[0129] In formula (5), T 2L,M is the T2 geometric mean of the movable fluid; T 2j is the T2 relaxation time constant of the jth relaxation component, A j is the component porosity corresponding to T 2j ; T 2c is the T2 cutoff value of the bound fluid and the movable fluid, and c is the ordinal number of T 2j .

[0130] The nuclear magnetic resonance logging can divide the reservoir porosity into the bound fluid volume and the movable fluid volume. The calculation method of the bound fluid saturation is

[0131] (4)

[0132] In formula (4), is the bound fluid volume.

[0133] According to the nuclear magnetic resonance logging related movable fluid T2 geometric mean T 2L,M , the apparent density porosity-nuclear magnetic porosity difference and the fluid saturation respectively T 2L,M -S BVI crossplot of T 2L,M -Δ DMR crossplot of

[0134] In some embodiments, as Figure 4 shown in FIG. 6 is T 2L,M -S BVI crossplot of Figure 5 shown in FIG. 7 is T 2L,M -Δ DMR crossplot of Figure 4 shown in FIG. 8 is T 2L,M - S BVI The coincidence rate of the crossplot of Figure 5 shown in FIG. 9 is T 2L,M -Δ DMR The coincidence rate of the crossplot of T 2L,M -Δ DMR The crossplot of

[0135] Fluid type comprehensive identification method:

[0136] In the above various fluid identification methods, their application effects are not the same. In order to evaluate the effects of each method, the concept of crossplot coincidence rate is proposed. In the crossplot, the percentage of the number of points in the region and range of different fluids divided by the total number of points is called the crossplot coincidence rate.

[0137] Specifically, the crossplot coincidence rate refers to the percentage of the sum of the number of water layers falling in the water layer area, the number of dry layers falling in the dry layer area, and the number of gas layers falling in the gas layer area in the crossplot, divided by the total number of reservoirs in the crossplot, which is calculated by formula (6),

[0138] (6)

[0139] In formula (6),

[0140] V R is the crossplot coincidence rate;

[0141] the number of water layers in the water layer region of the crossplot;

[0142] the number of dry layers in the dry layer region of the crossplot;

[0143] the number of gas layers in the gas layer region of the crossplot;

[0144] N is the total number of reservoirs in the crossplot.

[0145] In the three porosity logging comprehensive fluid identification method, Δ NA - Δ ND The coincidence rate of the crossplot is 88.0%, Δ NA -I SND The coincidence rate of the crossplot is 89.6%, and it can be seen that Δ NA -I SND The crossplot has a better identification effect. In the NMR logging identification method, T 2L,M -S BVI The coincidence rate of the crossplot is 88.9%, T 2L,M -Δ DMR The coincidence rate of the crossplot is 92.9%, T 2L,M -Δ DMR The crossplot has a better identification result. Overall, T 2L,M -Δ DMR The crossplot coincidence rate is higher than the porosity logging Δ NA -I SND The crossplot coincidence rate is high, which reflects the superiority of NMR logging in gas layer identification.

[0146] In actual data processing and interpretation, when only conventional logging data is available, the porosity difference and porosity difference ratio parameters are calculated respectively, and the Figure 2 and Figure 3When the results are consistent, the reservoir interpretation result is the judgment result; when the results are inconsistent, the result of the one with the higher coincidence rate is the interpretation conclusion. When there are both conventional logging data and nuclear magnetic resonance logging data, the apparent density porosity-nuclear magnetic porosity difference and movable fluid T2 geometric mean are calculated first, and then the Figures 2-5 four cross-plot charts are used for judgment respectively, and the absolute majority voting method is used to determine the final interpretation conclusion; when the results are inconsistent, the result of the one with the higher coincidence rate is the interpretation conclusion.

[0147] The embodiment provides a kind of ultra-low porosity and permeability tight sandstone gas-bearing layer fluid identification chart and comprehensive identification method, as shown in Figure 1 It is the flow chart of the process of the comprehensive identification method of the fluid type of tight sandstone gas-bearing layer. Its implementation steps include two parts:

[0148] The first part: constructing fluid identification chart

[0149] Step 1, collect test results, read the well data of acoustic logging, neutron logging, density logging and nuclear magnetic resonance logging porosity of different reservoirs.

[0150] Step 2, according to formula (1) (2), three porosity difference values and difference ratio parameters are obtained; and using formula (3) (4) (5), movable fluid T2 geometric mean, irreducible water saturation and apparent density porosity-nuclear magnetic porosity difference parameters related to nuclear magnetic resonance logging are calculated;

[0151] Step 3, four fluid identification charts are respectively established - 、 - , T 2L,M -S BVI and T 2L,M -Δ DMR are calculated respectively.

[0152] The second part: fluid identification of the well or reservoir to be evaluated

[0153] Step 4, the logging data of the well reservoir to be evaluated are substituted into the formula, and the fluid identification factor of the horizontal axis and the vertical axis in each chart is calculated respectively;

[0154] Step 5, according to the position of the calculated fluid sensitive parameter on each chart, the interpretation result is obtained by using the absolute majority voting method and the coincidence rate of the chart.

[0155] The embodiment constructs a gas indicating factor, a gas layer is recorded as 3, a dry layer is recorded as 2, a water layer is recorded as 1, a continuous fluid indicating curve is formed, and a fluid type rectangular indicating curve directly shows the fluid type.

[0156] Yet another embodiment of the present application provides a method for identifying fluids in tight sandstone gas-bearing layers, which adopts a combined fluid identification method of nuclear magnetic resonance logging and density logging, and specifically comprises the following steps:

[0157] S1, constructing a fluid identification chart:

[0158] Obtaining the porosity value of the density logging and the porosity value of the nuclear magnetic resonance logging of the reservoir to be measured;

[0159] Calculating the movable fluid T2 geometric mean value related to the nuclear magnetic resonance logging T 2L,M , apparent density porosity-nuclear magnetic porosity difference , and bound fluid saturation ;

[0160] respectively establishing the crossplot of T 2L,M -S BVI and the crossplot of T 2L,M - Δ DMR ;

[0161] S2, fluid identification of the reservoir to be measured:

[0162] According to the obtained crossplot, the fluid of the reservoir to be measured is identified by using the chart coincidence rate comprehensive judgment.

[0163] The apparent density porosity-nuclear magnetic porosity difference is calculated by formula (3),

[0164] (3)

[0165] In formula (3), is the apparent density porosity, is the nuclear magnetic resonance porosity;

[0166] The bound fluid saturation is calculated by formula (4),

[0167] (4)

[0168] In formula (4), is the bound fluid volume.

[0169] The geometric mean T of the movable fluid T2 2L,M Calculated from equation (5),

[0170] (5)

[0171] In equation (5), T 2L,M T² is the geometric mean of the moving fluid; T 2j Let A be the T2 relaxation time constant of the j-th relaxation component. j For the corresponding T 2j The component porosity; T 2c Let T2 be the cutoff value for bound fluid and movable fluid, and c be the corresponding T value for T2 cutoff. 2j The ordinal number.

[0172] Since equations (3), (4) and (5) are the same as those in the previous embodiment, they can be referred to the previous embodiment and will not be repeated here.

[0173] Based on the geometric mean T2 of movable fluids from nuclear magnetic resonance logging 2L,M Apparent density porosity - NMR porosity difference and confined fluid saturation Establish T respectively 2L,M -S BVI Intersection map and T 2L,M -Δ DMR Intersection diagram;

[0174] In some embodiments, such as Figure 4 The figure shows T 2L,M -S BVI The intersection chart, such as Figure 5 As shown T 2L,M -Δ DMR The two intersection charts can accurately distinguish between gas and water layers. Figure 4 It can be seen that when T 2L,M Between 150-700 ms and When the content is less than 65%, the reservoir is a gas layer; when T 2L,M Between 150-700 ms and If less than 65%, the reservoir is an aquifer; when T 2L,M Less than 150 ms and When the content is greater than 65%, the reservoir is considered a dry reservoir. Figure 5 It can be seen that when ≥5% and T 2L,MWhen 150-700 ms, the reservoir is a gas layer; when Less than 5% and T 2L,M More than 700 ms, the reservoir is a water layer; when Less than 5% and T 2L,M Less than 150 ms, the reservoir is a dry layer.

[0175] It is calculated that, Figure 4 As shown in the figure, T 2L,M - S BVI The coincidence rate of the crossplot of the gas layer is 88.9%; Figure 5 As shown in the figure, T 2L,M -Δ DMR The coincidence rate of the crossplot of the gas layer is 92.9%. It can be seen that, T 2L,M -Δ DMR The crossplot of the gas layer has higher accuracy.

[0176] The beneficial effects brought by the technical scheme of the present application: the present application constructs a plurality of gas layer sensitive factors through theoretical analysis, amplifies the differences of the gas layer, and constructs a fluid identification chart. In the interpretation of a new target layer, fluid discrimination is carried out according to each chart, and the final interpretation result is determined by using the strategy of absolute majority voting. The fluid sensitive factor constructed by the present application can better distinguish the fluid type based on the fluid sensitive factor, and the comprehensive discrimination strategy can organically combine the results of a plurality of methods together, which can eliminate the limitations of a certain method, and the interpretation result is proved by oil testing, and the coincidence rate is obviously improved.

[0177] As Figure 6 shown, one embodiment of the present application also proposes a tight sandstone gas-bearing layer fluid identification device, which comprises:

[0178] The fluid identification chart construction unit 21 comprises:

[0179] The first acquisition module 211 is used for acquiring the porosity values of the acoustic logging, the density logging and the neutron logging of the reservoir to be measured;

[0180] The first calculation module 212 is used for obtaining the first porosity difference value by subtracting the acoustic porosity from the neutron porosity, which is denoted as ;

[0181] The second calculation module 213 is used for obtaining the second porosity difference value by subtracting the density porosity from the neutron porosity, which is denoted as ;

[0182] The third calculation module 214 is configured to construct a porosity ratio value, denoted as ;

[0183] wherein,

[0184] (1)

[0185] (2)

[0186] In formula (1) and (2), 、 、 are apparent acoustic porosity, apparent density porosity and apparent neutron porosity, respectively.

[0187] The first crossplot establishing module 215 is configured to establish crossplots of - and - according to the first porosity difference value, the second porosity difference value and the porosity ratio value, respectively.

[0188] The fluid identification unit 22 of the reservoir to be measured is configured to identify the fluid of the reservoir to be measured by using a comprehensive judgment of the crossplots according to the crossplots of - and - .

[0189] Further, the fluid identification crossplot constructing unit further comprises:

[0190] The second acquisition module is configured to acquire the porosity value of the nuclear magnetic resonance logging of the reservoir to be measured.

[0191] The fourth calculation module is configured to calculate the T2 geometric mean T 2L,M of the movable fluid related to the nuclear magnetic resonance logging, the apparent density porosity-nuclear magnetic porosity difference value and the irreducible fluid saturation .

[0192] The second crossplot establishing module is configured to establish crossplots of T 2L,M -S BVI and T 2L,M -Δ DMR .

[0193] The apparent density porosity-nuclear magnetic porosity difference value is calculated by formula (3),

[0194] (3)

[0195] In formula (3), is the apparent density porosity, is the nuclear magnetic resonance porosity;

[0196] The irreducible fluid saturation is calculated by formula (4),

[0197] (4)

[0198] In formula (4), is the irreducible fluid volume.

[0199] Further, the fluid identification unit of the reservoir to be measured comprises:

[0200] The first fluid identification module is configured to identify the fluid of the reservoir to be measured according to the crossplot with the highest crossplot coincidence rate.

[0201] Further, the fluid identification unit of the reservoir to be measured comprises:

[0202] The second fluid identification module is configured to identify the fluid of the reservoir to be measured according to the crossplot, and if the voting results are consistent, the absolute majority consistent fluid identification result is output; if the voting results are different, the crossplot fluid identification result of the crossplot with the highest coincidence rate is output.

[0203] Further, the fluid identification unit of the reservoir to be measured comprises:

[0204] The crossplot coincidence rate calculation module is configured to calculate the crossplot coincidence rate according to formula (6),

[0205] (6)

[0206] In formula (6),

[0207] V R is the crossplot coincidence rate;

[0208] is the number of water layers in the water layer region in the crossplot;

[0209] is the number of dry layers in the dry layer region in the crossplot;

[0210] is the number of gas layers in the gas layer region in the crossplot;

[0211] N is the total number of reservoirs in the crossplot.

[0212] The present invention will be further described below with reference to specific embodiments, but this should not be construed as a limitation on the scope of protection of the present invention. Some non-essential improvements and adjustments made by those skilled in the art based on the above description of the present invention still fall within the scope of protection of the present invention.

[0213] Example

[0214] The above method was applied to tight sandstone in the Kuqa area of ​​the Tarim Basin, identifying 16 wells without nuclear magnetic resonance logging data. Comparison with test results showed an interpretation accuracy of 87.32%. Figure 7 The image shows the comprehensive identification results of reservoir fluid type from conventional logging of a well in this area. This well did not undergo nuclear magnetic resonance logging. The porosity difference and porosity difference ratio parameters were calculated separately. Figure 2 and Figure 3 The two intersection plots in the diagram are judged separately, using... Figure 1 The method generates fluid indicator curves, enabling reservoir fluid identification. Furthermore, it was applied to eight wells with nuclear magnetic resonance logging data. Figure 1 The flowchart describes the method for identification, interpreting 16 layers. Compared with the test results, the interpretation accuracy rate reaches 90%. Figure 8 The image shows the comprehensive logging results for reservoir fluid type identification of another well in the area. This well has nuclear magnetic resonance logging data, therefore, according to... Figures 2-5 The four intersection plates and Figure 1 The method shown generates fluid indicator curves, ultimately achieving comprehensive fluid identification.

[0215] The above applications demonstrate that the fluid-sensitive parameters and comprehensive discrimination method constructed in this invention have good effects in the application of fluid identification in the Kuqa Depression reservoir.

[0216] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any simple modifications, equivalent changes, and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope of the present invention.

[0217] To achieve the above objectives, the main technical means adopted in this invention are described clearly, completely, and accurately, and the substantive content of the invention is explained. The degree of disclosure is such that it is sufficient for a person skilled in the art to understand and implement the invention.

Claims

1. A method of identifying fluids in tight sand gas bearing formations, comprising: The method comprises the following steps, S1, constructing a fluid identification crossplot: obtaining the porosity values of acoustic logging, density logging and neutron logging of the reservoir to be measured; wherein the difference between the apparent neutron porosity and the apparent sonic porosity is a first porosity difference ; The difference between the apparent neutron porosity and the apparent density porosity is a second porosity difference ; Constructing porosity ratio whose expression is, ； wherein , , are the apparent sonic porosity, the apparent density porosity and the apparent neutron porosity, respectively; According to the obtained first porosity difference, second porosity difference and porosity ratio, respectively establish - The crossplot board and - The crossplot board, build fluid identification board is completed; S2, fluid identification of the reservoir to be measured: Based on the established - The crossplot and - The crossplot, according to the set crossplot coincidence rate, selects the crossplot with high crossplot coincidence rate to identify the fluid of the reservoir to be measured.

2. The method of claim 1, wherein, The step S1 further comprises: obtaining the porosity values of nuclear magnetic resonance logging of the reservoir to be measured; Computing geometric mean of movable fluids in nuclear magnetic resonance logging ; Computed difference between apparent density porosity and NMR porosity and irreducible fluid saturation ; wherein the difference between the apparent density porosity and the NMR porosity is the expression for the difference between the apparent density porosity and the NMR porosity is, ； wherein is the visual density porosity, is the nuclear magnetic resonance porosity; where the expression for the bound fluid saturation is given by, ； wherein is a volume of bound fluid; According to the obtained geometric mean , the difference between the apparent density porosity and the nuclear magnetic porosity and the irreducible fluid saturation are respectively established - crossplot chart and - crossplot chart.

3. The method of claim 2, wherein, Geometric mean of the movable fluid The expression for the calculation is ； wherein T2 is the geometric mean of the T2 values of the mobile fluid; T 2j T2 is the T2 relaxation time constant of the jth relaxation component, A j T2 is the T2 relaxation time constant of the jth relaxation component, A 2j T2 is the T2 relaxation time constant of the jth relaxation component, A 2c T2 is the T2 cutoff value of the bound fluid and the mobile fluid, c is the ordinal number of the corresponding T 2j T2 is the T2 cutoff value of the bound fluid and the mobile fluid, c is the ordinal number of the corresponding T 4. The method of claim 1 or 2, wherein, The established crossplot is used to identify the fluid of the reservoir to be measured by using the absolute majority voting method, if the voting result is consistent for more than half, the absolute majority consistent fluid identification result is output, if the voting result is less than half, the crossplot with the highest coincidence rate is output.

5. The method of claim 1, wherein, The expression of the set crossplot coincidence rate is, where V R is the plot conformance; is the number of water layers in the plot that fall in the water layer region; is the number of dry layers in the plot that fall in the dry layer region; is the number of gas layers in the plot that fall in the gas layer region; and N is the total number of reservoirs in the plot.

6. The method of claim 1, wherein, The expression of the apparent acoustic porosity is, ； The expression of the apparent density porosity is, ； The expression of the apparent neutron porosity is, ； In the formula, , , are the acoustic traveltime log value of the reservoir to be measured, the acoustic traveltime of the rock skeleton, and the acoustic traveltime of the mixture of the mud filtrate and the formation water, respectively. , , respectively are the density logging value of the reservoir to be measured, the density of the rock skeleton, and the density of the mixture of mud filtrate and formation water. , , , and are respectively the neutron logging value of the reservoir to be measured, the neutron logging value of the rock skeleton, and the neutron logging value of the mixture of mud filtrate and formation water.

7. A tight sand gas-bearing zone fluid identification system characterized by, Comprise, The fluid identification crossplot construction unit is used to construct a fluid identification crossplot; the fluid identification crossplot construction unit comprises, The first acquisition module is used to obtain the porosity values of acoustic logging, density logging and neutron logging of the reservoir to be measured; The first calculating module is configured to calculate a difference between the apparent neutron porosity and the apparent sonic porosity to obtain a first porosity difference ; A second computing module is configured to calculate a difference between the apparent neutron porosity and the apparent density porosity to obtain a second porosity difference ; a third calculation module configured to construct a porosity ratio with the expression ； wherein , , are the apparent sonic porosity, apparent density porosity and apparent neutron porosity, respectively. The first cross-plotting chart establishing module is configured to establish, respectively, a first cross-plotting chart, a second cross-plotting chart and a third cross-plotting chart according to the obtained first porosity difference, the second porosity difference and the porosity ratio - cross-plotting charts and - cross-plotting charts And a fluid identification unit of the to-be-tested reservoir, comprising a first fluid identification module, configured to identify the fluid of the to-be-tested reservoir based on the established - The crossplot and - The crossplot, and the crossplot with high crossplot coincidence rate is selected according to the set crossplot coincidence rate to identify the fluid of the to-be-tested reservoir.

8. The tight sand gas-bearing layer fluid identification system according to claim 7, characterized in that, The fluid identification crossplot construction unit further comprises, The second acquisition module is used to obtain the porosity values of nuclear magnetic resonance logging of the reservoir to be measured; A fourth calculating module is configured to calculate the geometric mean of the movable fluid in the nuclear magnetic resonance logging ; Computed difference between apparent density porosity and NMR porosity and fluid saturation ; wherein the difference between the apparent density porosity and the NMR porosity is The expression for the difference between the apparent density porosity and the NMR porosity is, ； wherein is the visual density porosity, is the nuclear magnetic resonance porosity; where the expression for the bound fluid saturation is given by, ； wherein is a volume of bound fluid; A second crossplot charting module for charting the obtained geometric mean , apparent density porosity-nuclear magnetic porosity difference and irreducible fluid saturation respectively - crossplot chart and - crossplot chart.

9. The tight sand gas-bearing layer fluid identification system according to claim 7, characterized in that, The fluid identification unit of the reservoir to be measured further comprises, The second fluid identification module is used to identify the fluid of the reservoir to be measured based on the established crossplot by using the absolute majority voting method, if the voting result is consistent for more than half, the absolute majority consistent fluid identification result is output, if the voting result is less than half, the crossplot with the highest coincidence rate is output.

10. The tight sand gas-bearing layer fluid identification system according to claim 7, characterized in that, The fluid identification unit of the reservoir to be measured further comprises a crossplot coincidence rate calculation module for calculating the set crossplot coincidence rate.

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