Fluid type identification method and system based on nuclear magnetic resonance logging dual-acquisition mode

Abstract

The invention discloses a fluid type identification method and system based on a nuclear magnetic resonance logging dual-acquisition mode, and the method comprises the steps: obtaining dual-TW logging data and dual-TE logging number according to a combined observation mode of nuclear magnetic resonance logging; based on a nuclear magnetic resonance relaxation theory, according to nuclear magnetic resonance logging data in a double-TW acquisition mode, obtaining a differential spectrum delta T2 and a differential spectrum porosity delta phi; according to the nuclear magnetic resonance logging data in the double-TE acquisition mode, T2 distribution under the double-echo interval is obtained, and the geometric mean difference value delta T2LM of the movable fluid under the T2 distribution under the double-echo interval is calculated; and according to the differential spectrum porosity delta phi and the geometric mean value difference delta T2LM, constructing a comprehensive fluid indication factor of a reservoir fluid identification standard, and carrying out comprehensive identification on the fluid type of the reservoir. According to the invention, two observation modes of nuclear magnetic resonance double TW and double TE are integrated together, the amount of observed data is large, the amount of information is rich, and the fluid type can be rapidly and visually identified.

Description

Technical Field

[0001] The invention relates to the technical field of petroleum logging, and in particular to a fluid type identification method and system based on a nuclear magnetic resonance logging dual acquisition mode. Background Art

[0002] Nuclear magnetic resonance (NMR) logging uses the interaction between hydrogen protons and an external magnetic field to observe reservoir information. It is an important geophysical exploration method. NMR logging can provide reservoir parameters such as total formation porosity, effective porosity, movable fluid and bound fluid. The observation methods mainly include long and short waiting time (dual TW) logging and long and short echo interval (dual TE) logging.

[0003] In dual TW observation and analysis, the polarizability of the fluid at different polarization times is different, and the difference in NMR logging response at different waiting times is analyzed by differential spectrum analysis and time domain analysis (TDA). In dual TE logging observation and data analysis, according to the NMR relaxation mechanism, due to the influence of diffusion relaxation and the difference in diffusion coefficient, the T obtained at different echo acquisition times is different. 2 The distribution is different, and the long echo interval corresponds to T 2 Distribution ratio shorter echo spacing T 2 The distribution should move forward, the gas layer with a larger diffusion coefficient moves forward more obviously, and the difference between the oil layer and the water layer is not obvious. These two observation modes are usually observed separately, and the qualitative analysis method is not effective enough, and the quantitative analysis method needs to be complex and not fast enough.

[0004] In current oil and gas exploration, there are more and more cases where dual TW and dual TE observation modes are measured simultaneously, such as the DTWE2 mode of the MRIL-P instrument and the D9TWE3 mode of the MRT instrument. These data are analyzed independently and are not combined and comprehensively used for fluid identification. Summary of the invention

[0005] The purpose of the present invention is to provide a fluid type identification method and system based on the dual acquisition mode of nuclear magnetic resonance logging, which integrates the two observation modes of nuclear magnetic resonance dual TW and dual TE, has a large amount of observed data and rich information, and can quickly and intuitively identify the fluid type.

[0006] To achieve the above object, the present invention provides a fluid type identification method based on nuclear magnetic resonance logging dual acquisition mode, comprising:

[0007] According to the joint observation mode of NMR logging, dual TW logging data and dual TE logging data are obtained;

[0008] Based on the NMR relaxation theory, the difference spectrum ΔT is obtained according to the NMR logging data in the dual TW acquisition mode. 2and the difference spectrum porosity Δφ;

[0009] According to the NMR logging data in the dual TE acquisition mode, the T 2 distribution, and calculate T under double echo interval 2 The difference of the geometric mean of the distributed movable fluid ΔT 2LM ;

[0010] According to the difference spectral porosity Δφ and the geometric mean difference ΔT 2LM , construct a comprehensive fluid indicator factor for reservoir fluid identification standards, and comprehensively identify the fluid type of the reservoir.

[0011] Furthermore, the difference spectrum ΔT is obtained based on the NMR logging data in the dual TW acquisition mode. 2 and the differential porosity Δφ, including:

[0012] According to the nuclear magnetic resonance logging data in the dual TW acquisition mode, the magnetization intensity vector of the long waiting time and the magnetization intensity vector of the short waiting time when the oil and water phases are contained are obtained;

[0013] Calculate the difference between the magnetization vectors of the long waiting time and the short waiting time according to the magnetization intensity vector of the long waiting time and the magnetization intensity vector of the short waiting time;

[0014] The magnetization vector difference is subjected to multi-exponential inversion processing to obtain a difference spectrum ΔT2 and a difference spectrum porosity Δφ.

[0015] Furthermore, the magnetization intensity vector of the long waiting time and the magnetization intensity vector of the short waiting time are respectively:

[0016]

[0017]

[0018] Where M L (t) represents the magnetization intensity vector of the long waiting time at time t, T WL Indicates long waiting time, T lwater represents the longitudinal relaxation time of water, n represents the total number of pore components, j represents the jth pore component, M 0wj represents the magnetization intensity of water in the jth pore component; T 2wj represents the relaxation time of the jth pore component water, M oil represents the magnetization intensity of the oil, T loil represents the longitudinal relaxation time of the oil, T 2oil represents the transverse relaxation time of oil, M S (t) represents the magnetization intensity vector of the short waiting time at time t, T WS Indicates short waiting time;

[0019] The magnetization vector difference between the long waiting time and the short waiting time is:

[0020]

[0021] Where ΔM(t) represents the magnetization vector difference between the long waiting time and the short waiting time at time t.

[0022] Furthermore, the acquisition of the difference spectrum ΔT 2 And the differential spectral porosity Δφ to determine the type of reservoir, including:

[0023] Based on the nuclear magnetic resonance relaxation theory, the reservoir fluid is judged to be an oil layer or a water layer according to the difference in the difference spectrum porosity Δφ:

[0024] When the reservoir is completely water-containing, the differential spectrum porosity Δφ is the smallest; when the reservoir is completely oil-containing, the differential spectrum porosity Δφ is the largest; that is, the higher the oil saturation of the reservoir, the larger the differential spectrum porosity Δφ;

[0025] Wherein, the difference spectrum porosity Δφ is:

[0026] Δφ=∑ΔT 2j ,

[0027] In the formula, ΔT 2j Represents the porosity of the jth pore component.

[0028] Furthermore, according to the NMR logging data in the dual TE acquisition mode, the T 2 Distribution, including:

[0029] According to the nuclear magnetic resonance logging data in the dual TE acquisition mode, the magnetization intensity vector of the long echo interval and the magnetization intensity vector of the short echo interval are obtained;

[0030] Based on the magnetization intensity vector of long echo interval and the magnetization intensity vector of short echo interval, multi-index inversion processing is performed to obtain T under double echo interval. 2 distributed;

[0031] Wherein, the magnetization intensity vector of the long echo interval and the magnetization intensity vector of the short echo interval are respectively:

[0032]

[0033]

[0034] Where M TES (t) represents the magnetization intensity vector at time t under short echo interval, n represents the total number of pore components, j represents the jth pore component, M 0wjrepresents the magnetization intensity of water in the jth pore component, T WL Indicates long waiting time, T lwater represents the longitudinal relaxation time of water, T 2wj represents the transverse relaxation time of water in the jth pore component, C represents the correlation constant of 1.08, and D a represents the diffusion coefficient, G represents the magnetic field strength, γ represents the hydrogen proton gyromagnetic ratio, T ES Indicates short echo interval, M oil represents the magnetization intensity of the oil, T l,oil represents the longitudinal relaxation time of the oil, T 2,oil represents the transverse relaxation time of oil, M TEL (t) represents the magnetization intensity vector at time t under long echo interval, T EL To indicate long echo interval.

[0035] Further, calculate T under double echo interval 2 The difference in geometric means of the distribution ΔT 2LM , to identify the fluid type in the reservoir, including:

[0036] Calculate the echo interval T 2 The geometric mean T of the movable fluid distribution 2LMF According to the influence of reservoir diffusion relaxation, the relationship between reservoir water and oil saturation and T 2 The geometric mean T of the movable fluid distribution 2LMF relationship;

[0037] According to the geometric mean T 2LMF , calculate T under long and short echo intervals 2 The geometric mean difference of the distribution, that is, T 2 Geometric mean difference ΔT of the distributed movable fluid 2LM ;

[0038] Among them, the T 2 Geometric mean T of the distributed movable fluid 2LMF for:

[0039]

[0040] Where, T 2LMF Indicates T 2 Geometric mean of the distributed movable fluid, T 2c represents the T2 cutoff value of bound fluid and movable fluid, T 2j represents the T of the jth pore component 2 Relaxation time constant, A j represents the amplitude corresponding to the jth pore component; c represents T 2 The corresponding T of the cutoff value 2jThe ordinal number, A c Indicates T 2 The corresponding T of the cutoff value 2j The amplitude, A n represents the amplitude corresponding to the nth pore component, n represents the total number of pore components, and j represents the jth pore component;

[0041] The double echo interval T 2 Geometric mean difference ΔT of the distributed movable fluid 2LM for:

[0042] ΔT 2LM =T 2LMF,TES -T 2LMF,TEL ,

[0043] Where, ΔT 2LM Indicates the double echo interval T 2 Geometric mean difference of the distributed movable fluid, T 2LMF,TES Indicates T under short echo interval 2 Geometric mean of distribution, T 2LMF,TEL Indicates T under long echo interval 2 The geometric mean of the distribution.

[0044] Furthermore, before constructing the comprehensive fluid indicator factor, the difference ΔT between the difference spectrum porosity Δφ and the geometric mean is constructed. 2LM The cross plots are used to verify and determine the lower limit of the fluid type, including:

[0045] Constructing a cross plot of reservoir oil saturation and the differential spectrum porosity Δφ to verify the relationship between the reservoir oil saturation and the differential spectrum porosity Δφ, that is, the differential spectrum porosity Δφ increases with the increase of oil saturation;

[0046] Construct the difference ΔT between the reservoir oil saturation and the geometric mean 2LM The cross plot verifies the difference ΔT between the reservoir oil saturation and the geometric mean 2LM The relationship between the geometric mean difference ΔT 2LM It increases with the increase of oil saturation;

[0047] According to the cross plot of reservoir oil saturation and the difference spectrum porosity Δφ, and the difference ΔT between reservoir oil saturation and the geometric mean 2LM The cross-plot of the difference spectrum porosity Δφ and the geometric mean difference ΔT is constructed. 2LM The intersection diagram is used to generate a reservoir fluid identification plate.

[0048] Furthermore, the comprehensive fluid indicator factor is:

[0049] F=ΔT 2LM ·Δφ=(T2LMF,TES -T 2LMF,TEL )·∑ΔT 2j ,

[0050] Where F represents the comprehensive fluid indicator factor, ΔT 2LM Indicates the double echo interval T 2 The difference in the geometric mean of the distribution, Δφ, represents the difference spectral porosity, T 2LMF,TES Indicates T under short echo interval 2 Geometric mean of distribution, T 2LMF,TEL Indicates T under long echo interval 2 Geometric mean of the distribution, ΔT 2j Represents the difference spectrum porosity size of the jth pore component.

[0051] Based on the same inventive concept, the present invention also provides a fluid type identification system based on the dual acquisition mode of nuclear magnetic resonance logging, comprising:

[0052] A combined unit, used to obtain dual TW logging data and dual TE logging data according to the combined observation mode of nuclear magnetic resonance logging;

[0053] The first acquisition unit is used to acquire the difference spectrum ΔT based on the nuclear magnetic resonance relaxation theory and the nuclear magnetic resonance logging data in the dual TW acquisition mode. 2 and the difference spectrum porosity Δφ;

[0054] The second acquisition unit is used to acquire T under the double echo interval according to the nuclear magnetic resonance logging data in the dual TE acquisition mode. 2 distribution, and calculate T under double echo interval 2 The difference of the geometric mean of the distributed movable fluid ΔT 2LM ;

[0055] A constructing unit is used to construct a porosity difference value ΔT according to the difference spectrum porosity Δφ and the geometric mean difference ΔT 2LM , construct a comprehensive fluid indicator factor for reservoir fluid identification standards, and comprehensively identify the fluid type of the reservoir.

[0056] Based on the same inventive concept, an embodiment of the present invention also provides an electronic device, including: a memory and a processor; the processor is used to read and execute a computer program stored in the memory to implement the aforementioned fluid type identification method based on the dual acquisition mode of nuclear magnetic resonance logging.

[0057] Based on the same inventive concept, an embodiment of the present invention further provides a computer storage medium, in which computer executable instructions are stored. When the computer executable instructions are executed, the aforementioned fluid type identification method based on the dual acquisition mode of nuclear magnetic resonance logging is implemented.

[0058] Technical effects and advantages of the present invention: The present invention extracts the fluid sensitive parameter - differential spectrum porosity Δφ for dual TW logging data, and extracts the fluid sensitive parameter - movable fluid T for dual TE logging data. 2 Geometric mean difference ΔT 2LM These two sensitive parameters provide a basis for fluid identification; based on numerical simulation or oil testing results, a differential porosity-movable fluid T 2 Geometric mean difference ΔT 2LM The intersection diagram, i.e. Δφ-ΔT 2LM Fluid identification chart; and based on two fluid sensitive parameters, a new fluid indicator factor was constructed, and a fluid identification standard was established, realizing continuous and rapid identification of reservoir fluids based on nuclear magnetic resonance logging.

[0059] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures pointed out in the description, claims and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0061] Figure 1 This is a flow chart of a method for fluid type identification based on a dual acquisition mode of nuclear magnetic resonance logging according to an embodiment of the present invention;

[0062] Figure 2 Schematic diagram of an ideal rock model with a porosity of 12.5% ​​in an embodiment of the present invention;

[0063] Figure 3 It is a schematic diagram of the comparison between the numerical simulation results of the nuclear magnetic resonance difference spectrum of rock models with different oil saturations in an embodiment of the present invention and the model;

[0064] Figure 4 is the oil saturation S of the reservoir in the embodiment of the present invention O Crossplot with the difference spectrum porosity Δφ;

[0065] Figure 5 It is a schematic diagram of numerical simulation and model comparison of nuclear magnetic resonance T2 distribution of rocks with different oil saturations at long echo intervals in an embodiment of the present invention;

[0066] Figure 6 is the oil saturation S of the reservoir in the embodiment of the present inventionO The difference ΔT from the geometric mean 2LM The intersection diagram of

[0067] Figure 7 It is a structural schematic diagram of a fluid type identification system based on a dual acquisition mode of nuclear magnetic resonance logging according to an embodiment of the present invention;

[0068] Figure 8 This is a schematic diagram of the structure of an electronic device according to an embodiment of the present invention;

[0069] Fig. 9 A schematic diagram of a reservoir fluid identification plate in an embodiment of the present invention;

[0070] Fig.10 is a distribution histogram of comprehensive fluid indicator factors in an embodiment of the present invention;

[0071] Fig.11 This is a schematic diagram of the joint rapid interpretation results of the dual TW and dual TE observation modes of nuclear magnetic resonance logging in well H75 in an embodiment of the present invention. DETAILED DESCRIPTION

[0072] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions 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 creative work are within the scope of protection of the present invention.

[0073] To address the deficiencies of the prior art, the present invention discloses a fluid type identification method based on a dual acquisition mode of nuclear magnetic resonance logging, such as Figure 1 As shown, including:

[0074] Step S1, combining the dual TW acquisition mode and the dual TE acquisition mode to perform nuclear magnetic resonance logging on the reservoir rock.

[0075] Step S2, based on the nuclear magnetic resonance relaxation theory, according to the nuclear magnetic resonance logging data in the dual TW acquisition mode, obtain the difference spectrum and the difference spectrum porosity to preliminarily determine whether the fluid type of the reservoir is a water layer or an oil layer; specifically includes:

[0076] Since the total magnetization signal measured in NMR is the superposition of a series of magnetization signals of pores of different sizes, when oil and water are contained in two phases, the magnetization vector with long waiting time and the magnetization vector with short waiting time in the dual TW acquisition mode are:

[0077]

[0078]

[0079] Where M L (t) represents the magnetization intensity vector of the long waiting time at time t, T WL Indicates long waiting time, T lwater represents the longitudinal relaxation time of water, n represents the total number of pore components, j represents the jth pore component, M 0wj represents the magnetization intensity of water in the jth pore component; T 2wj represents the relaxation time of the jth pore component water, M oil represents the magnetization intensity of the oil, T loil represents the longitudinal relaxation time of the oil, T 2oil represents the transverse relaxation time of oil, M S (t) represents the magnetization intensity vector of the short waiting time at time t, T WS Indicates a short wait time.

[0080] In the dual TW acquisition mode, the magnetization vector difference at different waiting times can reflect the fluid properties. Assuming that the reservoir rock is saturated with oil or completely saturated with water, the magnetization vector difference between the long waiting time and the short waiting time is calculated based on the magnetization intensity vector at the long waiting time and the magnetization intensity vector at the short waiting time:

[0081]

[0082] Where ΔM(t) represents the difference in magnetization vector between the long waiting time and the short waiting time at time t, T WL Indicates long waiting time, T lwater represents the longitudinal relaxation time of water, n represents the total number of pore components, j represents the jth pore component, M 0wj represents the magnetization intensity of water in the jth pore component; T 2wj represents the relaxation time of the jth pore component water, M oil represents the magnetization intensity of the oil, T loil represents the longitudinal relaxation time of the oil, T 2oil represents the transverse relaxation time of oil, M S (t) represents the magnetization intensity vector of the short waiting time at time t, T WS Indicates a short wait time.

[0083] Therefore, when the reservoir is completely water-containing, theoretically ΔM(t) = 0. As the oil saturation increases, the formula As ΔM(t) increases, ΔM(t) also gradually increases.

[0084] The magnetization vector difference ΔM(t) is subjected to multi-exponential inversion processing to obtain the difference spectrum ΔT2 and the difference spectrum porosity Δφ. The difference spectrum porosity Δφ is:

[0085] Δφ=∑ΔT2j

[0086] In the formula, ΔT 2j Represents the difference spectrum porosity size of the jth pore component.

[0087] Based on the nuclear magnetic resonance relaxation theory, the reservoir fluid sensitive parameter - differential spectral porosity Δφ is related to the fluid type of the reservoir. The reservoir fluid can be judged as an oil layer or a water layer based on the difference in differential spectral porosity Δφ. When the reservoir is completely water-containing, the differential spectral porosity Δφ is the smallest; when the reservoir is completely oil-containing, the differential spectral porosity Δφ is the largest; that is, the higher the oil saturation of the reservoir, the larger the differential spectral porosity Δφ.

[0088] The feasibility of the above method is verified by numerical simulation. A rock model with known pore components of different sizes is set up, with a porosity of 12.5%. Figure 2 As shown. Set the NMR long waiting time to 12.98s, the short waiting time to 2.0s, and the echo interval to 0.9ms. According to the above method, first simulate the echo train of the reservoir with long waiting time and short waiting time, and obtain the difference spectrum ΔT by inversion. 2 ; Then, assuming the oil saturation to be 20%, 50% and 80% respectively, the echo trains under the three saturation conditions are calculated. Figure 3 To construct an ideal rock model with different oil saturations, when the oil saturation is 20%, the calculated difference spectrum porosity Δφ=1.66%; when the oil saturation is 50%, the calculated difference spectrum porosity Δφ=3.93%; when the oil saturation is 80%, the calculated difference spectrum porosity Δφ=6.20%.

[0089] An interactive diagram of reservoir oil saturation and differential spectrum porosity Δφ is constructed to verify the relationship between reservoir oil saturation and the differential spectrum porosity Δφ; Figure 4 As shown in the figure, as the oil saturation increases, the calculated differential spectrum porosity increases linearly; that is, for the same reservoir, as the differential spectrum porosity increases, the oil saturation is higher, and the differential spectrum porosity value is larger when saturated with oil than when saturated with water.

[0090] Step S3: Obtain the T value under the double echo interval according to the nuclear magnetic resonance logging data under the dual TE acquisition mode. 2 Distribution, and calculate the geometric mean difference of the distribution under the double echo interval to identify the saturation of the fluid type in the reservoir; specifically including:

[0091] According to the NMR logging data in the dual TE acquisition mode, the magnetization intensity vectors of the long echo interval and the short echo interval are obtained as follows:

[0092]

[0093]

[0094] Where M TES (t) represents the magnetization intensity vector at time t under short echo interval, n represents the total number of pore components, j represents the jth pore component, M 0wj represents the magnetization intensity of water in the jth pore component, T WL Indicates long waiting time, T lwater represents the longitudinal relaxation time of water, T 2wj represents the transverse relaxation time of water in the jth pore component, C represents the correlation constant of 1.08, and D a represents the diffusion coefficient, G represents the magnetic field strength, γ represents the hydrogen proton gyromagnetic ratio, T ES Indicates short echo interval, M oil represents the magnetization intensity of the oil, T l,oil represents the longitudinal relaxation time of the oil, T 2,oil represents the transverse relaxation time of oil, M TEL (t) represents the magnetization intensity vector at time t under long echo interval, T EL To indicate long echo interval.

[0095] Since the diffusion coefficients Do and Dw of oil and water are related to viscosity and temperature, their diffusion coefficient values ​​can be accurately measured by experiments. The diffusion coefficient of water is smaller than that of light oil.

[0096] Based on the above derivation, multi-index inversion processing is performed based on the magnetization intensity vector of the long echo interval and the magnetization intensity vector of the short echo interval to obtain T under double echo interval. 2 The distribution of T in the long waiting time and long echo interval mode under the conditions of reservoir oil saturation of 20%, 50% and 80% is obtained. 2 distributed.

[0097] like Figure 5 As shown in the figure, due to the influence of diffusion relaxation, when the oil and water content is different, T 2 The distribution forward shift degree is also different, the water peak is distributed after the oil peak. The greater the oil saturation, the longer the echo interval T 2 The distribution is closer to T 2 This means that when the oil and water content is different, the T 2 The geometric means of the distributions are different.

[0098] For the same rock, the difference between the NMR response when saturated with oil and saturated with water is mainly in T 2 The movable fluid portion of the distribution, therefore, T 2 The geometric mean of the distributed movable fluid can more clearly reflect the differences between different fluids.

[0099] Calculate T 2The geometric mean T of the movable fluid distribution 2LMF for:

[0100]

[0101] Where, T 2LMD Indicates T 2 Geometric mean of the distributed movable fluid, T 2c represents the T2 cutoff value of bound fluid and movable fluid, T 2j represents the T of the jth pore component 2 Relaxation time constant, A j represents the amplitude corresponding to the jth pore component; c represents T 2 The corresponding T of the cutoff value 2j The ordinal number, A c Indicates T 2 The corresponding T of the cutoff value 2j The amplitude, A n represents the amplitude corresponding to the nth pore component, n represents the total number of pore components, and j represents the jth pore component; Indicates exponential calculation, that is, T 2c A c Power; Same reason.

[0102] From the above verification, it can be seen that due to the influence of diffusion relaxation, A kj >A j >A Oj , obtain the reservoir water and oil saturation and the geometric mean T 2LMF Relationship: That is, when saturated with water, its movable fluid T 2 Geometric mean T 2LMF,W Maximum; when saturated with oil, its movable fluid T 2 Geometric mean T 2LMF,O The minimum saturation is between the two. j Indicates that when it is completely hydrated, it corresponds to T 2j The component porosity of Ao j Indicates that the corresponding T is when the oil is completely contained 2j Porosity of pore components.

[0103] According to the geometric mean T 2LMF , calculate T under long and short echo intervals 2 The geometric mean difference of the distribution, that is, T 2 The difference in geometric means of the distribution ΔT 2LM , used to identify the fluid type.

[0104] Among them, T 2The difference in geometric means of the distribution ΔT 2LM for:

[0105] ΔT 2LM =T 2LMF,TES -T 2LMF,TEL ,

[0106] Where, ΔT 2LM Indicates the double echo interval T 2 Difference in geometric means of distributions, T 2LMF,TES Indicates T under short echo interval 2 Geometric mean of distribution, T 2LMF,TEL Indicates T under long echo interval 2 The geometric mean of the distribution.

[0107] Construct reservoir oil saturation S O The difference ΔT from the geometric mean 2LM Cross plot, verify oil saturation S O The difference ΔT from the geometric mean 2LM The relationship between Figure 6 As shown in Figure 2, as the oil saturation increases, the geometric mean difference ΔT 2LM increases linearly; therefore, if ΔT 2LM The larger the value, the higher the oil saturation. 2LM The smaller the value, the greater the water saturation.

[0108] According to the interaction diagram of the reservoir oil saturation and the difference spectrum porosity Δφ, and the difference ΔT between the reservoir oil saturation and the geometric mean 2LOM The interaction diagram of the difference spectrum porosity Δφ and the geometric mean difference ΔT is constructed 2LM The intersection diagram is used to generate a reservoir fluid identification plate.

[0109] Step S4: Due to the two reservoir fluid sensitive parameters - the difference spectrum porosity Δφ and the geometric mean difference ΔT 2LM The oil saturation S O In order to further amplify the difference between the oil layer and the water layer, according to the difference spectrum porosity Δφ and the geometric mean difference ΔT 2LM , construct a comprehensive fluid indicator factor for reservoir fluid identification standards, and comprehensively identify the fluid type of the reservoir.

[0110] Among them, the comprehensive fluid indicator factor is:

[0111] F=ΔT 2LM ·Δφ=(T 2LMF,TES -T 2LMF,TEL )·∑ΔT 2j ,

[0112] Where F represents the comprehensive fluid indicator factor, ΔT 2LM Indicates the double echo interval T 2 The difference in the geometric mean of the distribution, Δφ, represents the difference spectral porosity, T 2LMF,TES Indicates T under short echo interval 2 Geometric mean of distribution, T 2LMF,TEL Indicates T under long echo interval 2 Geometric mean of the distribution, ΔT 2j Represents the porosity size of the difference spectrum of the jth component.

[0113] Based on the same inventive concept, the embodiment of the present invention also discloses a fluid type identification system based on the dual acquisition mode of nuclear magnetic resonance logging, such as Figure 7 As shown, including:

[0114] Combined unit, used to combine dual TW acquisition mode and dual TE acquisition mode to perform nuclear magnetic resonance logging on reservoir rocks;

[0115] The first acquisition unit is used to acquire the difference spectrum ΔT based on the nuclear magnetic resonance relaxation theory and the nuclear magnetic resonance logging data in the dual TW acquisition mode. 2 and the differential spectrum porosity Δφ, to preliminarily determine whether the fluid type of the reservoir is a water layer or an oil layer;

[0116] The second acquisition unit is used to acquire T under the double echo interval according to the nuclear magnetic resonance logging data in the dual TE acquisition mode. 2 distribution, and calculate T under double echo interval 2 The difference in geometric means of the distribution ΔT 2LM , to identify the saturation of the fluid type in the reservoir;

[0117] A constructing unit is used to construct a porosity difference value ΔT according to the difference spectrum porosity Δφ and the geometric mean difference ΔT 2LM , construct a comprehensive fluid indicator factor for reservoir fluid identification standards, and comprehensively identify the fluid type of the reservoir.

[0118] Regarding the system in the above embodiment, the specific manner in which each unit module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0119] Based on the same inventive concept, an embodiment of the present invention further provides an electronic device, whose structure is as follows: Figure 8 As shown, it includes: a memory and a processor, wherein the processor is used to read and execute the computer program stored in the memory to implement the aforementioned fluid type identification method based on the dual acquisition mode of nuclear magnetic resonance logging.

[0120] Based on the same inventive concept, an embodiment of the present invention further provides a computer storage medium, in which computer executable instructions are stored. When the computer executable instructions are executed, the aforementioned fluid type identification method based on the dual acquisition mode of nuclear magnetic resonance logging is implemented.

[0121] Specific implementation example - experimental application in the Chang 8 oil and gas reservoir of the Yanchang Group in the Ordos Basin:

[0122] The Yanchang Formation in the western part of the Ordos Basin is an important oil and gas target layer. The MRT instrument is used for nuclear magnetic resonance logging, and the observation mode is D9TWE3. According to the above methods and steps, the difference spectrum ΔT is inverted based on the nuclear magnetic resonance logging data in the dual TW mode. 2 Based on the NMR logging data in dual TE mode, the T of dual TE is calculated. 2 Distribute the geometric mean of the movable fluid and calculate the difference between the two ΔT 2LM .

[0123] Based on two fluid sensitive parameters (difference spectrum porosity Δφ and T 2 Difference of geometric mean value of distributed movable fluid ΔT 2LM ) construct Δφ-ΔT 2LM Intersection diagram, such as Fig. 9 As shown in the figure, the oil layer, oil-water layer, and water layer are located in different areas on the cross-plot and can be clearly distinguished. The identification standard is obtained, oil layer: ΔT 2LM Value>55ms, Δφ>6%, F>330; oil and water in the same layer: ΔT 2LM Between 50-70ms, Δφ between 2% and 6%, and F between 100 and 330; water layer: Δφ is less than 2%, △T2LM<50ms, and F is less than 100.

[0124] According to the oil testing results in the study area, a comprehensive fluid indicator factor distribution histogram is constructed, such as Fig.10 It can be seen that when there is a water layer: F is distributed between 0-100; when there is oil and water in the same layer: F is distributed between 100-300; when there is an oil layer: F is greater than 300, which is consistent with the above calculation results.

[0125] Well H75 is an exploration well in this area, and its acquisition mode and parameters are MRT type D9TWE3 mode. The above method is used to calculate the difference spectrum porosity Δφ based on the dual TW mode and the T of the movable fluid based on the dual TE mode. 2 Difference of geometric means ΔT 2LM and its indicating parameter F, and the reservoir fluid was identified according to the standards established on the plate.

[0126] like Fig.11 As shown in the figure, the fourth track is T under long waiting time and short echo interval2 The fifth track is T under short waiting time and short echo interval. 2 The sixth track is T under long waiting time and long echo interval. 2 The seventh track is the difference spectrum, the eighth track is the calculated difference spectrum porosity Δφ, and the ninth track is the fluid indicator factor. At a depth of 2521-2525m, the natural gamma value is low, the calculated difference spectrum porosity Δφ is about 8%, ΔT 2LM The time is about 85ms, and the fluid indicator factor F is about 400, which is interpreted as an oil layer. The test was conducted at 2521-2525m, with a daily oil production of 118.66t and water production of 0t. The oil test conclusion is an oil layer, which verifies the correctness of this method.

[0127] In addition, the method was applied to 27 layers in 22 wells in the study area, with a compliance rate of 81.5%, which shows that the method of the present invention is accurate and feasible, and the effect is very significant.

[0128] Finally, it should be noted that the above is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, it is still possible for those skilled in the art to modify the technical solutions described in the aforementioned embodiments or to make equivalent substitutions for some of the technical features therein. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A fluid type identification method based on the dual acquisition mode of nuclear magnetic resonance logging, characterized in that: include: According to the joint observation mode of NMR logging, dual TW logging data and dual TE logging data are obtained; Based on the NMR relaxation theory, the difference spectrum ΔT2 and the difference spectrum porosity Δφ are obtained according to the NMR logging data in the dual TW acquisition mode; According to the NMR logging data in the dual TE acquisition mode, the T2 distribution under the double echo interval is obtained, and the movable fluid geometric mean difference ΔT of the T2 distribution under the double echo interval is calculated. 2LM ; According to the difference spectral porosity Δφ and the geometric mean difference ΔT 2LM , construct a comprehensive fluid indicator factor for reservoir fluid identification standards, and comprehensively identify the fluid type of the reservoir.

2. The fluid type identification method based on the dual acquisition mode of nuclear magnetic resonance logging according to claim 1 is characterized in that: According to the NMR logging data in the dual TW acquisition mode, the difference spectrum ΔT2 and the difference spectrum porosity Δφ are obtained, including: According to the nuclear magnetic resonance logging data in the dual TW acquisition mode, the magnetization intensity vector of the long waiting time and the magnetization intensity vector of the short waiting time when the oil and water phases are contained are obtained; Calculate the difference between the magnetization vectors of the long waiting time and the short waiting time according to the magnetization intensity vector of the long waiting time and the magnetization intensity vector of the short waiting time; The magnetization vector difference is subjected to multi-exponential inversion processing to obtain a difference spectrum ΔT2 and a difference spectrum porosity Δφ.

3. The fluid type identification method based on the dual acquisition mode of nuclear magnetic resonance logging according to claim 2 is characterized in that: The magnetization intensity vector of the long waiting time and the magnetization intensity vector of the short waiting time are respectively: Where M L (t) represents the magnetization intensity vector of the long waiting time at time t, T WL Indicates long waiting time, T lwater represents the longitudinal relaxation time of water, n represents the total number of pore components, j represents the jth pore component, M 0wj represents the magnetization intensity of water in the jth pore component; T 2wj represents the relaxation time of the jth pore component water, M oil represents the magnetization intensity of the oil, T loil represents the longitudinal relaxation time of the oil, T 2oil represents the transverse relaxation time of oil, M S (t) represents the magnetization intensity vector of the short waiting time at time t, T WS Indicates short waiting time; The magnetization vector difference between the long waiting time and the short waiting time is: Where ΔM(t) represents the magnetization vector difference between the long waiting time and the short waiting time at time t.

4. The fluid type identification method based on the dual acquisition mode of nuclear magnetic resonance logging according to claim 1 or 3, characterized in that: The obtaining of the difference spectrum ΔT2 and the difference spectrum porosity Δφ to determine the type of reservoir includes: Based on the nuclear magnetic resonance relaxation theory, the reservoir fluid is judged to be an oil layer or a water layer according to the difference in the difference spectrum porosity Δφ: When the reservoir is completely water-containing, the differential spectrum porosity Δφ is the smallest; when the reservoir is completely oil-containing, the differential spectrum porosity Δφ is the largest; that is, the higher the oil saturation of the reservoir, the larger the differential spectrum porosity Δφ; Wherein, the difference spectrum porosity Δφ is: Δφ=ΣΔT 2j , In the formula, ΔT 2j Represents the porosity of the jth pore component.

5. The fluid type identification method based on the dual acquisition mode of nuclear magnetic resonance logging according to claim 1 is characterized in that: Based on the NMR logging data in the dual TE acquisition mode, the T2 distribution under the dual echo interval is obtained, including: According to the nuclear magnetic resonance logging data in the dual TE acquisition mode, the magnetization intensity vector of the long echo interval and the magnetization intensity vector of the short echo interval are obtained; Based on the magnetization intensity vectors of long echo interval and short echo interval, multi-index inversion processing is performed to obtain T2 distribution under double echo interval; Wherein, the magnetization intensity vector of the long echo interval and the magnetization intensity vector of the short echo interval are respectively: ， Where M TES (t) represents the magnetization intensity vector at time t under short echo interval, n represents the total number of pore components, j represents the jth pore component, M 0wj represents the magnetization intensity of water in the jth pore component, T WL Indicates long waiting time, T lwater represents the longitudinal relaxation time of water, T 2wj represents the transverse relaxation time of water in the jth pore component, C represents the correlation constant of 1.08, and D a represents the diffusion coefficient, G represents the magnetic field strength, γ represents the hydrogen proton gyromagnetic ratio, T ES Indicates short echo interval, M oil represents the magnetization intensity of the oil, T l,oil represents the longitudinal relaxation time of the oil, T 2,oil represents the transverse relaxation time of oil, M TEL (t) represents the magnetization intensity vector at time t under long echo interval, T EL To indicate long echo interval.

6. The fluid type identification method based on the dual acquisition mode of nuclear magnetic resonance logging according to claim 1 or 5, characterized in that: Calculate the geometric mean difference ΔT of T2 distribution under double echo interval 2LM , to identify the fluid type in the reservoir, including: Calculate the movable fluid geometric mean T of T2 distribution under echo spacing 2LMF According to the influence of reservoir diffusion relaxation, the geometric mean value T of the movable fluid of reservoir water and oil saturation and T2 distribution is obtained. 2LMi relationship; According to the geometric mean T 2LMF , calculate the geometric mean difference of T2 distribution under long and short echo intervals, that is, the geometric mean difference ΔT of T2 distribution movable fluid under the double echo interval 2LM ; Wherein, the geometric mean value T of the movable fluid of the T2 distribution is 2LMF for: Where, T 2LMF represents the geometric mean of the T2 distribution of the movable fluid, T 2c represents the T2 cutoff value of bound fluid and movable fluid, T 2j represents the T2 relaxation time constant of the jth pore component, A j represents the amplitude corresponding to the jth pore component; c represents the T corresponding to the T2 cutoff value 2j The ordinal number, A c The corresponding T represents the T2 cutoff value 2j The amplitude, A n represents the amplitude corresponding to the nth pore component, n represents the total number of pore components, and j represents the jth pore component; The geometric mean difference ΔT of the T2 distribution movable fluid under the double echo interval 2LM for: ΔT 2LM =T 2LMF,TES -T 2LMF,TEL , In the formula, ΔT 2LM represents the geometric mean difference of T2 distribution movable fluid under double echo interval, T 2LMF,TES represents the geometric mean of T2 distribution under short echo interval, T 2LMF,TEL It represents the geometric mean of T2 distribution under long echo interval.

7. The fluid type identification method based on the dual acquisition mode of nuclear magnetic resonance logging according to claim 1 is characterized in that: Before constructing the comprehensive fluid indicator factor, construct the difference spectral porosity Δφ and the geometric mean difference ΔT 2LM The cross plots are used to verify and determine the lower limit of the fluid type, including: Constructing a cross plot of reservoir oil saturation and the differential spectrum porosity Δφ to verify the relationship between the reservoir oil saturation and the differential spectrum porosity Δφ, that is, the differential spectrum porosity Δφ increases with the increase of oil saturation; Construct the difference ΔT between the reservoir oil saturation and the geometric mean 2LM The cross plot verifies the difference ΔT between the reservoir oil saturation and the geometric mean 2LM The relationship between the geometric mean difference ΔT 2LM It increases with the increase of oil saturation; According to the cross plot of reservoir oil saturation and the difference spectrum porosity Δφ, and the difference ΔT between reservoir oil saturation and the geometric mean 2LM The cross-plot of the difference spectrum porosity Δφ and the geometric mean difference ΔT is constructed. 2LM The intersection diagram is used to generate a reservoir fluid identification plate.

8. The fluid type identification method based on the dual acquisition mode of nuclear magnetic resonance logging according to claim 1 is characterized in that: The comprehensive fluid indicator factor is: F=ΔT 2LM ·Δφ=(T 2LMF,TES -T 2LMF,TEL )·∑ΔT 2j , Where F represents the comprehensive fluid indicator factor, ΔT 2LM represents the geometric mean difference of T2 distribution under double echo interval, Δφ represents the difference spectrum porosity, T 2LMF,TES represents the geometric mean of T2 distribution under short echo interval, T 2LMF,TEL represents the geometric mean of T2 distribution under long echo interval, ΔT 2j Represents the difference spectrum porosity size of the jth pore component.

9. Fluid type identification system based on nuclear magnetic resonance logging dual acquisition mode, characterized in that: include: A combined unit, used to obtain dual TW logging data and dual TE logging data according to the combined observation mode of nuclear magnetic resonance logging; The first acquisition unit is used to acquire the difference spectrum ΔT2 and the difference spectrum porosity Δφ according to the nuclear magnetic resonance logging data in the dual TW acquisition mode based on the nuclear magnetic resonance relaxation theory; The second acquisition unit is used to acquire the T2 distribution under the double echo interval according to the nuclear magnetic resonance logging data in the dual TE acquisition mode, and calculate the movable fluid geometric mean difference ΔT of the T2 distribution under the double echo interval 2LM ; A constructing unit is used to construct a porosity difference value ΔT according to the difference spectrum porosity Δφ and the geometric mean difference ΔT 2LM , construct a comprehensive fluid indicator factor for reservoir fluid identification standards, and comprehensively identify the fluid type of the reservoir.

10. An electronic device, characterized in that: include: Memory, processor; The processor is used to read and execute the computer program stored in the memory to implement the fluid type identification method based on the dual acquisition mode of nuclear magnetic resonance logging as described in any one of claims 1-9.

11. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, which, when executed, implement the fluid type identification method based on the dual acquisition mode of nuclear magnetic resonance logging as described in any one of claims 1-9.

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