Shallow gas reservoir fluid property identification method, device, equipment and medium

Abstract

The invention discloses a shallow gas reservoir fluid property identification method and device, equipment and a medium, and relates to the technical field of reservoir evaluation, and the method comprises the steps: carrying out the data measurement of a shallow gas reservoir through a preset logging instrument, and obtaining the data of the shallow gas reservoir; performing parameter calculation on longitudinal and transverse wave time differences in the shallow gas reservoir data to obtain rock mechanical parameters; reservoir fluid property indication sensitivity calculation is conducted on the shallow gas reservoir data and the rock mechanical parameters, and all sensitivity parameter values are obtained; screening target sensitivity parameters from the shallow gas reservoir data and the rock mechanical parameters according to the sensitivity parameter values, and calculating a gas reservoir comprehensive indication factor of the shallow gas reservoir by using the target sensitivity parameters; the shallow gas reservoir gas layer comprehensive indication factor and the target sensitivity parameter are combined to establish the fluid property identification standard of the shallow gas reservoir, and the fluid property identification standard is utilized to perform fluid property identification on the to-be-identified shallow gas reservoir, so that the fluid property coincidence rate of the identified shallow gas reservoir can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of reservoir evaluation, and in particular to a method, device, equipment and medium for identifying fluid properties of shallow gas reservoirs. Background Art

[0002] At present, the methods and techniques for identifying reservoir fluid properties can be summarized into three categories: cross plot method, curve overlap method, and correlation analysis method. Among these three methods, the more typical techniques include porosity-resistivity cross plot technology, density-neutron or acoustic-neutron curve overlap technology, water saturation-immobile water saturation overlap technology, and porosity-resistivity correlation analysis technology. These methods have played an important role in the identification of fluid properties in conventional reservoirs and low-permeability-tight sandstone reservoirs. However, for shallow gas reservoirs, due to their shallow burial depth, short diagenetic period, and hydrostatic sedimentary environment, the rocks are loose, weakly consolidated, and the lithology is fine. On conventional well logging curves, they show high natural gamma, low resistivity contrast, and low gas saturation response characteristics. Well logging curves can only reflect the gas content of the reservoir from one or two aspects. It is difficult to accurately identify the fluid properties using them, resulting in a low compliance rate for identifying the fluid properties of shallow gas reservoirs, which brings great challenges to the evaluation of reservoir fluid properties and reserve estimation.

[0003] It can be seen from the above that how to accurately identify the fluid properties of shallow gas reservoirs and improve the compliance rate of identifying the fluid properties of shallow gas reservoirs are problems to be solved in this field. Summary of the invention

[0004] In view of this, the purpose of the present invention is to provide a method, device, equipment and medium for identifying the fluid properties of shallow gas reservoirs, which can accurately identify the fluid properties of shallow gas reservoirs and improve the compliance rate of identifying the fluid properties of shallow gas reservoirs. The specific scheme is as follows:

[0005] In a first aspect, the present application discloses a method for identifying fluid properties of a shallow gas reservoir, comprising:

[0006] Using the preset logging instrument to measure the shallow gas reservoir data to obtain the shallow gas reservoir data;

[0007] Calculating the parameters of the longitudinal and transverse wave time differences in the shallow gas reservoir data to obtain rock mechanics parameters;

[0008] Performing reservoir fluid property indication sensitivity calculation on the shallow gas reservoir data and the rock mechanics parameters to obtain various sensitivity parameter values;

[0009] Screening out target sensitivity parameters from the shallow gas reservoir data and the rock mechanics parameters according to the sensitivity parameter values, and calculating the shallow gas reservoir gas layer comprehensive indicator factor using the target sensitivity parameters;

[0010] The gas layer comprehensive indicator factor of the shallow gas reservoir and the target sensitivity parameter are combined to establish a fluid property identification standard for the shallow gas reservoir, and the fluid property identification standard is used to identify the fluid property of the shallow gas reservoir to be identified.

[0011] Optionally, the method of measuring data of the shallow gas reservoir using a preset logging instrument to obtain shallow gas reservoir data includes:

[0012] Conventional logging instruments, array acoustic logging instruments and gas logging instruments are used to measure data of shallow gas reservoirs to obtain shallow gas reservoir data including volume density, deep resistivity, longitudinal and shear wave time difference and gas logging total hydrocarbon data.

[0013] Optionally, an array acoustic logging instrument is used to measure data of shallow gas reservoirs to obtain the time difference between longitudinal and shear waves, including:

[0014] The array acoustic logging instrument is used to measure data of a shallow gas reservoir to obtain longitudinal and transverse wave velocities, and the longitudinal and transverse wave velocities are converted using a longitudinal wave time difference calculation formula and a transverse wave time difference calculation formula to obtain longitudinal and transverse wave time differences, respectively;

[0015] Or, using the array acoustic logging instrument to measure data of shallow gas reservoirs to obtain the time difference between longitudinal and shear waves;

[0016] The longitudinal wave time difference calculation formula is:

[0017] ;

[0018] The shear wave time difference calculation formula is:

[0019] ;

[0020] in, is the longitudinal wave time difference, , is the longitudinal wave velocity, , is the shear wave time difference, , is the shear wave velocity, .

[0021] Optionally, a gas logging instrument is used to measure data of shallow gas reservoirs to obtain gas logging full hydrocarbon data, including:

[0022] Use gas logging instruments to measure data on shallow gas reservoirs to obtain gas logging full hydrocarbon curves;

[0023] Correcting the gas-tested total hydrocarbon curve to obtain gas-tested total hydrocarbon data including corrected gas-tested total hydrocarbon values;

[0024] The calculation formula for the correction is:

[0025] ;

[0026] in, is the corrected total hydrocarbon value of gas measurement, %, is the total hydrocarbon value of the measured gas, %, is the actual rock crushing volume per unit time, min / m, is the average rock crushing volume per unit time, min / m, is the standard drill diameter, mm, The diameter of the drill bit used to drill through the formation, mm, is the actual displacement of drilling fluid, L / min, is the average displacement of drilling fluid, L / min, is the core diameter, cm, is the volume density, .

[0027] Optionally, the parameter calculation of the P-wave and S-wave time differences in the shallow gas reservoir data to obtain rock mechanics parameters includes:

[0028] The longitudinal and transverse wave time differences in the shallow gas reservoir data are calculated using the Lame coefficient calculation formula and the bulk modulus calculation formula to obtain the Lame coefficient and the bulk modulus; the rock mechanics parameters include the Lame coefficient and the bulk modulus;

[0029] The Lame coefficient calculation formula is:

[0030] ;

[0031] The bulk modulus calculation formula is:

[0032] ;

[0033] in, is the Lame coefficient, dimensionless, is the volume density, , is the shear wave time difference, , is the longitudinal wave time difference, , K is the bulk modulus, dimensionless.

[0034] Optionally, the step of selecting target sensitivity parameters from the shallow gas reservoir data and the rock mechanics parameters according to the sensitivity parameter values ​​includes:

[0035] Sorting the sensitivity parameter values ​​and determining the number of parameters according to business requirements;

[0036] Determine the sensitivity parameter value with the largest value from the sorted sensitivity parameter values ​​based on the number of parameters;

[0037] A target sensitivity parameter corresponding to the sensitivity parameter value with the largest numerical value is selected from the shallow gas reservoir data and the rock mechanics parameters.

[0038] Optionally, the calculating of a comprehensive indicator factor of a shallow gas reservoir using the target sensitivity parameter includes:

[0039] obtaining a pre-selected standard sensitivity parameter corresponding to the target sensitivity parameter;

[0040] The target sensitivity parameter and the standard sensitivity parameter are used to calculate the comprehensive indicator factor of the shallow gas reservoir.

[0041] In a second aspect, the present application discloses a shallow gas reservoir fluid property identification device, comprising:

[0042] The data measurement module is used to measure the shallow gas reservoir data using a preset logging instrument to obtain the shallow gas reservoir data;

[0043] A parameter calculation module is used to perform parameter calculation on the P-wave and S-wave time differences in the shallow gas reservoir data to obtain rock mechanics parameters;

[0044] A sensitivity parameter value calculation module, used for performing reservoir fluid property indication sensitivity calculation on the shallow gas reservoir data and the rock mechanics parameters to obtain various sensitivity parameter values;

[0045] An indicator factor calculation module, used to select target sensitivity parameters from the shallow gas reservoir data and the rock mechanics parameters according to the sensitivity parameter values, and calculate the comprehensive indicator factor of the shallow gas reservoir gas layer using the target sensitivity parameters;

[0046] The fluid property identification module is used to combine the comprehensive indicator factor of the shallow gas reservoir and the target sensitivity parameter to establish the fluid property identification standard of the shallow gas reservoir, and use the fluid property identification standard to identify the fluid property of the shallow gas reservoir to be identified.

[0047] In a third aspect, the present application discloses an electronic device, comprising:

[0048] Memory, used to store computer programs;

[0049] A processor is used to execute the computer program to implement the aforementioned shallow gas reservoir fluid property identification method.

[0050] In a fourth aspect, the present application discloses a computer storage medium for storing a computer program; wherein, when the computer program is executed by a processor, the steps of the aforementioned method for identifying fluid properties of shallow gas reservoirs disclosed above are implemented.

[0051] It can be seen that the present application provides a method for identifying fluid properties of shallow gas reservoirs, including using a preset logging instrument to measure data on a shallow gas reservoir to obtain shallow gas reservoir data; performing parameter calculations on the longitudinal and transverse wave time differences in the shallow gas reservoir data to obtain rock mechanical parameters; performing reservoir fluid property indication sensitivity calculations on the shallow gas reservoir data and the rock mechanical parameters to obtain values ​​of various sensitivity parameters; screening out target sensitivity parameters from the shallow gas reservoir data and the rock mechanical parameters according to the values ​​of various sensitivity parameters, and calculating a comprehensive indicator factor of a shallow gas reservoir gas layer using the target sensitivity parameters; combining the comprehensive indicator factor of a shallow gas reservoir gas layer with the target sensitivity parameter to establish a fluid property identification standard for the shallow gas reservoir, and using the fluid property identification standard to identify the fluid properties of the shallow gas reservoir to be identified. In order to improve the accuracy of distinguishing the fluid properties of such reservoirs, the present application comprehensively considers the lithology, physical properties, electrical properties and gas content, and innovatively proposes to integrate the logging and logging data based on the analysis of the sensitivity of conventional, array acoustic logging and gas logging data to gas layer indication, and use preset logging and logging instruments to measure the data of shallow gas reservoirs to obtain shallow gas reservoir data, calculate the rock mechanical parameters reflecting the mechanical properties of the reservoir, calculate the reservoir fluid property indication sensitivity of the shallow gas reservoir data and rock mechanical parameters, screen out the target sensitivity parameters that are most sensitive to the indication of the fluid properties of the shallow gas reservoir from the shallow gas reservoir data and rock mechanical parameters according to the values ​​of each sensitivity parameter, calculate the comprehensive indication factor of the shallow gas reservoir gas layer, establish the fluid property identification standard of the shallow gas reservoir, realize the identification of the fluid properties of the shallow gas reservoir to be identified, accurately identify the fluid properties of the shallow gas reservoir, and improve the compliance rate of identifying the fluid properties of the shallow gas reservoir. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0053] Figure 1 A flow chart of a method for identifying fluid properties of a shallow gas reservoir disclosed in the present application;

[0054] Figure 2A comparison diagram of conventional logging response characteristics of high-resistance gas layers and low-contrast gas layers in shallow gas reservoirs in the Baiyun Depression of a certain basin disclosed in this application;

[0055] Figure 3 This is a flow chart of a method disclosed in the present application for fusing measurement and logging data to identify fluid properties of shallow gas reservoirs;

[0056] Figure 4 This is an analysis and comparison diagram of the low-contrast gas layer indication sensitivity parameters of the shallow gas reservoir in the Baiyun Depression of a certain basin disclosed in this application;

[0057] Figure 5 A diagram for identifying fluid properties of shallow gas reservoirs using gas layer comprehensive indicator factors and volume density crossplots disclosed in the present application;

[0058] Figure 6 This is an application example of a discrimination standard disclosed in this application for identifying the fluid properties of a shallow gas reservoir in the Baiyun Depression of a certain basin;

[0059] Figure 7 This is a schematic diagram of the structure of a shallow gas reservoir fluid property identification device disclosed in this application;

[0060] Figure 8 A structural diagram of an electronic device provided for this application. DETAILED DESCRIPTION

[0061] 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.

[0062] At present, the methods and techniques for identifying reservoir fluid properties can be summarized into three categories: cross plot method, curve overlap method, and correlation analysis method. Among these three methods, the more typical techniques include porosity-resistivity cross plot technology, density-neutron or acoustic-neutron curve overlap technology, water saturation-immobile water saturation overlap technology, and porosity-resistivity correlation analysis technology. These methods have played an important role in the identification of fluid properties in conventional reservoirs and low-permeability-tight sandstone reservoirs. However, for shallow gas reservoirs, due to their shallow burial depth, short diagenetic period, and hydrostatic sedimentary environment, the rocks are loose, weakly consolidated, and the lithology is fine. On conventional well logging curves, they show high natural gamma, low resistivity contrast, and low gas saturation response characteristics. Well logging curves can only reflect the gas content of the reservoir from one or two aspects. It is difficult to accurately identify the fluid properties using them, resulting in a low compliance rate for identifying the fluid properties of shallow gas reservoirs, which brings great challenges to the evaluation of reservoir fluid properties and reserve estimation. It can be seen from the above that how to accurately identify the fluid properties of shallow gas reservoirs and improve the compliance rate of identifying the fluid properties of shallow gas reservoirs are problems to be solved in this field.

[0063] See also Figure 1 As shown, the embodiment of the present invention discloses a method for identifying fluid properties of a shallow gas reservoir, which may specifically include:

[0064] Step S11: Use a preset logging instrument to measure data on the shallow gas reservoir to obtain shallow gas reservoir data.

[0065] In this embodiment, conventional logging instruments, array acoustic logging instruments and gas logging instruments are used to measure data of shallow gas reservoirs to obtain shallow gas reservoir data including volume density, deep resistivity, longitudinal and shear wave time differences and gas logging total hydrocarbon data.

[0066] The method comprises: using the array acoustic logging instrument to measure data on the shallow gas reservoir to obtain longitudinal and transverse wave time differences, and converting the longitudinal and transverse wave velocities using a longitudinal wave time difference calculation formula and a transverse wave time difference calculation formula to obtain longitudinal and transverse wave time differences, respectively;

[0067] Or, using the array acoustic logging instrument to measure data of shallow gas reservoirs to obtain the time difference between longitudinal and shear waves;

[0068] The longitudinal wave time difference calculation formula is:

[0069] ;

[0070] The shear wave time difference calculation formula is:

[0071] ;

[0072] in, is the longitudinal wave time difference, , is the longitudinal wave velocity, , is the shear wave time difference, , is the shear wave velocity, .

[0073] The method comprises: measuring data of the shallow gas reservoir using the gas logging instrument to obtain gas logging total hydrocarbon data, comprising: measuring data of the shallow gas reservoir using the gas logging instrument to obtain a gas logging total hydrocarbon curve; correcting the gas logging total hydrocarbon curve to obtain gas logging total hydrocarbon data including a corrected gas logging total hydrocarbon value;

[0074] The calculation formula for the correction is:

[0075] ;

[0076] in, is the corrected total hydrocarbon value of gas measurement, %, is the total hydrocarbon value of the measured gas, %, is the actual rock crushing volume per unit time, min / m, is the average rock crushing volume per unit time, min / m, is the standard drill diameter, mm, The diameter of the drill bit used to drill through the formation, mm, is the actual displacement of drilling fluid, L / min, is the average displacement of drilling fluid, L / min, is the core diameter, cm, is the volume density, .

[0077] Step S12: Calculate the parameters of the P-wave and S-wave time differences in the shallow gas reservoir data to obtain rock mechanics parameters.

[0078] In this embodiment, the Lame coefficient calculation formula and the bulk modulus calculation formula are used to calculate the longitudinal and transverse wave time differences in the shallow gas reservoir data to obtain the Lame coefficient and the bulk modulus; the rock mechanics parameters include the Lame coefficient and the bulk modulus;

[0079] The Lame coefficient calculation formula is:

[0080] ;

[0081] The bulk modulus calculation formula is:

[0082] ;

[0083] in, is the Lame coefficient, dimensionless, is the volume density, , is the shear wave time difference, , is the longitudinal wave time difference, , K is the bulk modulus, dimensionless.

[0084] Step S13: performing reservoir fluid property indication sensitivity calculation on the shallow gas reservoir data and the rock mechanics parameters to obtain various sensitivity parameter values.

[0085] Step S14: selecting target sensitivity parameters from the shallow gas reservoir data and the rock mechanics parameters according to the values ​​of the sensitivity parameters, and calculating the comprehensive indicator factor of the shallow gas reservoir gas layer using the target sensitivity parameters.

[0086] In this embodiment, the sensitivity parameter values ​​are sorted, and the number of parameters is determined according to business needs; the sensitivity parameter value with the largest numerical value is determined from the sorted sensitivity parameter values ​​based on the number of parameters; the target sensitivity parameter corresponding to the sensitivity parameter value with the largest numerical value is screened from the shallow gas reservoir data and the rock mechanics parameters, and the pre-selected standard sensitivity parameter corresponding to the target sensitivity parameter is obtained; the comprehensive indicator factor of the shallow gas reservoir gas layer is calculated using the target sensitivity parameter and the standard sensitivity parameter.

[0087] Taking the four parameters of total hydrocarbon, deep resistivity, Lame coefficient and bulk modulus as the sensitivity parameters for indicating the fluid properties of shallow gas reservoirs as an example, combined with the logging data of total hydrocarbon, Lame coefficient, bulk modulus and deep resistivity, the following formula is used to establish the comprehensive indicator factor I of the shallow gas reservoir:

[0088] ;

[0089] Among them, I is the comprehensive indicator factor of the gas layer, dimensionless, TG_YS is the total hydrocarbon value of the gas test actually measured, %, and TG_YSw is the total hydrocarbon value of the gas test of the reference water layer, %. is the Lame coefficient of the reference water layer, is the bulk modulus of the reference water layer, Rt is the deep resistivity, Ω.m, is the deep resistivity of the reference water layer, Ω.m; wherein the pre-selected standard sensitivity parameters include the gas logging total hydrocarbon value of the reference water layer and the bulk modulus of the reference water layer.

[0090] Step S15: combining the comprehensive indicator factor of the shallow gas reservoir and the target sensitivity parameter to establish a fluid property identification standard for the shallow gas reservoir, and using the fluid property identification standard to identify the fluid properties of the shallow gas reservoir to be identified.

[0091] Combining the volume density and the comprehensive indicator factor I of the shallow gas reservoir, the identification standard of the fluid properties of the shallow gas reservoir is established. For example, the target shallow gas reservoir can be divided into two categories: low-contrast gas layer and water layer. The standard is as follows:

[0092] Shallow low-contrast air layer: I ≥ 0.2 or I < 0.2 and ≤2.13;

[0093] Water layer: >2.13 and I<0.2.

[0094] For high-porosity and high-permeability reservoirs, conventional or array acoustic logging data can be used to accurately identify reservoir fluid properties. Under normal circumstances, gas layers often show "three lows, two highs and one abnormality" response characteristics on conventional logging curves, namely low natural gamma, low volume density, low neutron, high acoustic time difference, high resistivity, and obvious natural potential anomaly amplitude. At the same time, under the standard limestone scale, there is an obvious "mirror" feature between the volume density and neutron logging curves. Using these response characteristics, high-resistance gas layers can be intuitively and accurately identified. However, for shallow gas reservoirs, due to factors such as shallow burial depth, short diagenetic period, and hydrostatic sedimentary environment, the rocks are loose, the lithology is fine, the physical properties are poor, and the gas saturation is low. The low gas saturation leads to a significantly smaller difference in the resistivity response between the gas layer and the water layer, and the "mirror" feature between the volume density-neutron logging curve of the gas layer is not obvious. Using conventional logging data, gas layer identification methods based on crossplot method, curve overlap method and correlation analysis method are ineffective, and the accuracy of distinguishing fluid properties in shallow gas reservoirs is low.

[0095] The comparison of conventional and gas logging curve responses of high resistivity gas layer and low resistivity gas layer in a certain well in a certain place is shown in the figure below. Figure 2As shown in the figure, the 754.0-756.5m, 773.0-781.0m and 790.0-792.0m sections are typical high-resistivity gas layers. The natural gamma of these three reservoirs is less than 90.0API, the deep resistivity is greater than 2.0Ω.m, the total hydrocarbon of gas logging is also high, and the "mirror" feature between the volume density and neutron logging curves is obvious. Using conventional logging curves, this type of gas layer can be identified more accurately. However, in the 801.0-805.0m and 814.0-824.0m sections, the natural gamma value does not decrease significantly, the deep resistivity is less than 2.0Ω.m, the volume density-neutron logging curve has no "mirror" feature, and there is only an obvious gas layer indication on the gas logging total hydrocarbon curve. For this type of low-contrast gas layer, if only 1 or 2 types of logging curves are used, it is difficult to accurately identify it, resulting in the omission of this type of gas layer. Based on the above analysis, in order to improve the recognition accuracy of low-contrast gas layers in shallow gas reservoirs, it is necessary to establish a comprehensive gas layer indication factor based on a comprehensive analysis of the indication effects of various types of well logging curves on low-contrast gas layers, so as to accurately identify the fluid properties of shallow gas reservoirs. The technical solution of this application is introduced with the above specific embodiments. The specific process is as follows: Figure 3 As shown:

[0096] Step 1: Use conventional, array sonic and gas logging instruments to measure the target reservoir and obtain the target reservoir volume density, deep resistivity, longitudinal and shear wave velocity and gas logging total hydrocarbon data. In order to accurately use gas logging total hydrocarbon data to indicate the fluid properties of shallow gas reservoirs, it is necessary to perform engineering factor and drilling fluid correction on the actual measured gas logging total hydrocarbon curve;

[0097] Step 2: Process the measured array acoustic logging data to obtain rock mechanical parameters such as the Lame coefficient and bulk modulus. It should be noted that when the measured array acoustic logging data are longitudinal and transverse wave velocities, the longitudinal and transverse wave velocities must first be converted into longitudinal and transverse wave time differences.

[0098] Step 3: Based on the conventional logging data, rock mechanics parameters and gas logging data, the following formula is used to calculate the sensitivity parameter values ​​of each curve to the fluid properties of the shallow gas reservoir:

[0099] ;

[0100] in, is the average value of each curve obtained in the gas layer section, is the average value of each curve obtained in the water layer section, DI is the reservoir fluid property indication sensitivity parameter, dimensionless. The higher the DI value, the more sensitive the curve is to the gas layer indication, and vice versa, the lower the DI value, the less sensitive the curve is to the gas layer indication;

[0101] Step 4: Calculate the reservoir fluid property indication sensitivity parameters DI respectively, rank the ability of each parameter to indicate the reservoir fluid property, and select the parameter most sensitive to the shallow gas reservoir fluid property indication; Figure 4 The DI value statistical histogram of reservoir fluid property indication sensitivity parameters of different parameters in 3 wells in a certain place. Based on the high and low DI values ​​in the figure, it is judged that the parameters that are more sensitive to the indication of the fluid properties of the shallow gas reservoir in this area include total hydrocarbons in gas measurement, deep resistivity, Lame coefficient and bulk modulus. Parameters such as Young's modulus, Poisson's ratio, longitudinal and transverse wave velocity ratio have poor sensitivity to the indication of the fluid properties of shallow gas reservoirs. Therefore, four parameters, including total hydrocarbons in gas measurement, deep resistivity, Lame coefficient and bulk modulus, are selected as target sensitivity parameters;

[0102] Step 5: using the four parameters of gas logging total hydrocarbon, deep resistivity, Lame coefficient and bulk modulus to establish a comprehensive indicator factor I of the shallow gas reservoir;

[0103] Step 6: Combine the comprehensive indicator factor I and volume density of the shallow gas reservoir and calibrate them using the test data to obtain the shallow gas reservoir fluid property identification chart, such as Figure 5 Based on Figure 5 The plate shown in the figure provides the identification standard of fluid properties of shallow gas reservoirs.

[0104] The conventional, array acoustic wave and gas logging data of the well are processed by the method described in steps 1 to 6 to obtain the comprehensive indicator factor I of the gas layer, which is used to continuously identify the fluid properties of the target reservoir. Figure 6 This is an application example of using the gas reservoir comprehensive indicator factor I to identify the fluid properties of shallow gas reservoirs. Figure 6The first to third tracks show conventional lithology, resistivity and physical property curves, which are used to identify effective reservoirs, calculate reservoir porosity and identify reservoir fluid properties. The fourth track shows the content of total hydrocarbons, methane and ethane in gas logging after correction by engineering factors and drilling fluid. The fifth track is the gas layer comprehensive indicator factor I calculated continuously by combining deep resistivity, corrected total hydrocarbons in gas logging, Lame coefficient and bulk modulus. From the response characteristics of conventional logging curves, the 752.0-754.0m, 770.0-772.5m and 788.0-790.0m well sections are typical high-resistivity gas layers, and the corresponding gas layer comprehensive indicator factor I values ​​are also high, which can be well identified. However, the conventionally measured deep resistivity of the 793.0-794.0m, 805.0-808.0m, 817.0-818.0m and 832.0-835.0m sections is low, and the "mirror" feature of the density-neutron logging curve is not obvious, so it is easy to misjudge them as non-gas layers using conventional methods. However, the comprehensive indication factor I of the gas layer in these sections is much greater than 0.2, so they are judged as low-contrast gas layers. This discrimination result is confirmed by the test data. The results obtained by testing the 752.0-822.0m section using three types of nozzles all show high-yield gas layers, which fully proves the reliability of the method described in the present invention.

[0105] In this embodiment, a preset logging instrument is used to measure data of a shallow gas reservoir to obtain shallow gas reservoir data; parameter calculation is performed on the longitudinal and transverse wave time differences in the shallow gas reservoir data to obtain rock mechanical parameters; reservoir fluid property indication sensitivity calculation is performed on the shallow gas reservoir data and the rock mechanical parameters to obtain each sensitivity parameter value; target sensitivity parameters are screened out from the shallow gas reservoir data and the rock mechanical parameters according to each sensitivity parameter value, and a comprehensive indicator factor of a shallow gas reservoir is calculated using the target sensitivity parameters; the comprehensive indicator factor of a shallow gas reservoir is combined with the target sensitivity parameter to establish a fluid property identification standard for the shallow gas reservoir, and the fluid property identification standard is used to identify the fluid properties of the shallow gas reservoir to be identified. In order to improve the accuracy of distinguishing the fluid properties of such reservoirs, the present application comprehensively considers the lithology, physical properties, electrical properties and gas content, and innovatively proposes to integrate the logging and logging data based on the analysis of the sensitivity of conventional, array acoustic logging and gas logging data to gas layer indication, and use preset logging and logging instruments to measure the data of shallow gas reservoirs to obtain shallow gas reservoir data, calculate the rock mechanical parameters reflecting the mechanical properties of the reservoir, calculate the reservoir fluid property indication sensitivity of the shallow gas reservoir data and rock mechanical parameters, screen out the target sensitivity parameters that are most sensitive to the indication of the fluid properties of the shallow gas reservoir from the shallow gas reservoir data and rock mechanical parameters according to the values ​​of each sensitivity parameter, calculate the comprehensive indication factor of the shallow gas reservoir gas layer, establish the fluid property identification standard of the shallow gas reservoir, realize the identification of the fluid properties of the shallow gas reservoir to be identified, accurately identify the fluid properties of the shallow gas reservoir, and improve the compliance rate of identifying the fluid properties of the shallow gas reservoir.

[0106] See also Figure 7 As shown, the embodiment of the present invention discloses a device for identifying the properties of fluid in a shallow gas reservoir, which may specifically include:

[0107] The data measurement module 11 is used to measure the shallow gas reservoir data using a preset logging instrument to obtain shallow gas reservoir data;

[0108] A parameter calculation module 12 is used to perform parameter calculation on the P-wave and S-wave time differences in the shallow gas reservoir data to obtain rock mechanics parameters;

[0109] A sensitivity parameter value calculation module 13 is used to perform reservoir fluid property indication sensitivity calculation on the shallow gas reservoir data and the rock mechanics parameters to obtain various sensitivity parameter values;

[0110] The indicator factor calculation module 14 is used to select target sensitivity parameters from the shallow gas reservoir data and the rock mechanics parameters according to the sensitivity parameter values, and calculate the comprehensive indicator factor of the shallow gas reservoir gas layer using the target sensitivity parameters;

[0111] The fluid property identification module 15 is used to combine the shallow gas reservoir comprehensive indicator factor and the target sensitivity parameter to establish the fluid property identification standard of the shallow gas reservoir, and use the fluid property identification standard to identify the fluid property of the shallow gas reservoir to be identified.

[0112] In some specific embodiments, the data measurement module 11 may specifically include:

[0113] The data measurement module is used to measure the shallow gas reservoir data using conventional logging instruments, array acoustic logging instruments and gas logging instruments to obtain shallow gas reservoir data including volume density, deep resistivity, longitudinal and shear wave time difference and gas logging total hydrocarbon data.

[0114] In some specific embodiments, the data measurement module 11 may specifically include:

[0115] A velocity conversion module is used to measure data of shallow gas reservoirs using the array acoustic logging instrument to obtain longitudinal and transverse wave velocities, and to convert the longitudinal and transverse wave velocities using a longitudinal wave time difference calculation formula and a transverse wave time difference calculation formula to obtain longitudinal and transverse wave time differences, respectively;

[0116] A module for directly measuring the time difference between longitudinal and shear waves, used to measure data of shallow gas reservoirs using the array acoustic logging instrument to obtain the time difference between longitudinal and shear waves;

[0117] The longitudinal wave time difference calculation formula is:

[0118] ;

[0119] The shear wave time difference calculation formula is:

[0120] ;

[0121] in, is the longitudinal wave time difference, , is the longitudinal wave velocity, , is the shear wave time difference, , is the shear wave velocity, .

[0122] In some specific embodiments, the data measurement module 11 may specifically include:

[0123] The gas logging full hydrocarbon curve measurement module is used to measure data of shallow gas reservoirs using gas logging instruments to obtain a gas logging full hydrocarbon curve;

[0124] A correction module, used for correcting the gas-tested total hydrocarbon curve to obtain gas-tested total hydrocarbon data including corrected gas-tested total hydrocarbon values;

[0125] The calculation formula for the correction is:

[0126] ;

[0127] in, is the corrected total hydrocarbon value of gas measurement, %, is the total hydrocarbon value of the measured gas, %, is the actual rock crushing volume per unit time, min / m, is the average rock crushing volume per unit time, min / m, is the standard drill diameter, mm, The diameter of the drill bit used to drill through the formation, mm, is the actual displacement of drilling fluid, L / min, is the average displacement of drilling fluid, L / min, is the core diameter, cm, is the volume density, .

[0128] In some specific embodiments, the parameter calculation module 12 may specifically include:

[0129] A rock mechanics parameter calculation module, used to calculate the time difference between longitudinal and transverse waves in the shallow gas reservoir data using a Lame coefficient calculation formula and a bulk modulus calculation formula to obtain a Lame coefficient and a bulk modulus; the rock mechanics parameters include a Lame coefficient and a bulk modulus;

[0130] The Lame coefficient calculation formula is:

[0131] ;

[0132] The bulk modulus calculation formula is:

[0133] ;

[0134] in, is the Lame coefficient, dimensionless, is the volume density, , is the shear wave time difference, , is the longitudinal wave time difference, , K is the bulk modulus, dimensionless.

[0135] In some specific embodiments, the indicator factor calculation module 14 may specifically include:

[0136] A sorting module, used to sort the sensitivity parameter values ​​and determine the number of parameters according to business requirements;

[0137] A sensitivity parameter value screening module, used for determining the sensitivity parameter value with the largest value from the sorted sensitivity parameter values ​​based on the number of parameters;

[0138] The target sensitivity parameter determination module is used to select the target sensitivity parameter corresponding to the maximum sensitivity parameter value from the shallow gas reservoir data and the rock mechanics parameters.

[0139] In some specific embodiments, the indicator factor calculation module 14 may specifically include:

[0140] A standard sensitivity parameter acquisition module, used to acquire a pre-selected standard sensitivity parameter corresponding to a target sensitivity parameter;

[0141] The shallow gas reservoir gas layer comprehensive indicator factor calculation module is used to calculate the shallow gas reservoir gas layer comprehensive indicator factor by using the target sensitivity parameter and the standard sensitivity parameter.

[0142] Figure 8 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. The electronic device 20 may specifically include: at least one processor 21, at least one memory 22, a power supply 23, a communication interface 24, an input / output interface 25, and a communication bus 26. The memory 22 is used to store a computer program, which is loaded and executed by the processor 21 to implement the relevant steps in the shallow gas reservoir fluid property identification method performed by the electronic device disclosed in any of the aforementioned embodiments.

[0143] In this embodiment, the power supply 23 is used to provide working voltage for each hardware device on the electronic device 20; the communication interface 24 can create a data transmission channel between the electronic device 20 and the external device, and the communication protocol it follows is any communication protocol that can be applied to the technical solution of the present application, and is not specifically limited here; the input and output interface 25 is used to obtain external input data or output data to the outside world, and its specific interface type can be selected according to specific application needs and is not specifically limited here.

[0144] In addition, the memory 22, as a carrier for storing resources, can be a read-only memory, a random access memory, a disk or an optical disk, etc. The resources stored thereon include an operating system 221, a computer program 222 and data 223, etc. The storage method can be temporary storage or permanent storage.

[0145] Among them, the operating system 221 is used to manage and control the hardware devices and computer programs 222 on the electronic device 20, so as to realize the operation and processing of the data 223 in the memory 22 by the processor 21, which can be Windows, Unix, Linux, etc. In addition to including a computer program that can be used to complete the shallow gas reservoir fluid property identification method performed by the electronic device 20 disclosed in any of the aforementioned embodiments, the computer program 222 can further include a computer program that can be used to complete other specific tasks. In addition to including data transmitted from an external device received by the shallow gas reservoir fluid property identification device, the data 223 can also include data collected by its own input and output interface 25, etc.

[0146] The steps of the method or algorithm described in conjunction with the embodiments disclosed herein may be implemented directly using hardware, a software module executed by a processor, or a combination of the two. The software module may be placed in a random access memory (RAM), a memory, a read-only memory (ROM), an electrically programmable ROM, an electrically erasable programmable ROM, a register, a hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.

[0147] Furthermore, an embodiment of the present application also discloses a computer-readable storage medium, in which a computer program is stored. When the computer program is loaded and executed by a processor, the steps of the method for identifying the fluid properties of a shallow gas reservoir disclosed in any of the aforementioned embodiments are implemented.

[0148] Finally, it should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.

[0149] The above is a detailed introduction to a method, device, equipment and storage medium for identifying fluid properties of shallow gas reservoirs provided by the present invention. Specific examples are used in this article to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea; at the same time, for general technical personnel in this field, according to the idea of ​​the present invention, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present invention.

Claims

1. A method for identifying fluid properties of shallow gas reservoirs, characterized in that: include: Using the preset logging instrument to measure the shallow gas reservoir data to obtain the shallow gas reservoir data; Calculating the parameters of the longitudinal and transverse wave time differences in the shallow gas reservoir data to obtain rock mechanics parameters; Performing reservoir fluid property indication sensitivity calculation on the shallow gas reservoir data and the rock mechanics parameters to obtain various sensitivity parameter values; Screening out target sensitivity parameters from the shallow gas reservoir data and the rock mechanics parameters according to the sensitivity parameter values, and calculating the shallow gas reservoir gas layer comprehensive indicator factor using the target sensitivity parameters; The gas layer comprehensive indicator factor of the shallow gas reservoir and the target sensitivity parameter are combined to establish a fluid property identification standard for the shallow gas reservoir, and the fluid property identification standard is used to identify the fluid property of the shallow gas reservoir to be identified.

2. The method for identifying the properties of shallow gas reservoir fluid according to claim 1, characterized in that: The method of measuring data of the shallow gas reservoir using a preset logging instrument to obtain shallow gas reservoir data includes: Conventional logging instruments, array acoustic logging instruments and gas logging instruments are used to measure data of shallow gas reservoirs to obtain shallow gas reservoir data including volume density, deep resistivity, longitudinal and shear wave time difference and gas logging total hydrocarbon data.

3. The method for identifying the properties of shallow gas reservoir fluid according to claim 2, characterized in that: Array acoustic logging instruments are used to measure data of shallow gas reservoirs to obtain the time difference between longitudinal and shear waves, including: The array acoustic logging instrument is used to measure data of a shallow gas reservoir to obtain longitudinal and transverse wave velocities, and the longitudinal and transverse wave velocities are converted using a longitudinal wave time difference calculation formula and a transverse wave time difference calculation formula to obtain longitudinal and transverse wave time differences, respectively; Or, using the array acoustic logging instrument to measure data of shallow gas reservoirs to obtain the time difference between longitudinal and shear waves; The longitudinal wave time difference calculation formula is: ； The shear wave time difference calculation formula is: ； in, is the longitudinal wave time difference, , is the longitudinal wave velocity, , is the shear wave time difference, , is the shear wave velocity, .

4. The method for identifying the properties of shallow gas reservoir fluid according to claim 2, characterized in that: Use gas logging instruments to measure data on shallow gas reservoirs to obtain gas logging full hydrocarbon data, including: Use gas logging instruments to measure data on shallow gas reservoirs to obtain gas logging full hydrocarbon curves; Correcting the gas-tested total hydrocarbon curve to obtain gas-tested total hydrocarbon data including corrected gas-tested total hydrocarbon values; The calculation formula for the correction is: ； in, is the corrected total hydrocarbon value of gas measurement, %, is the total hydrocarbon value of the measured gas, %, is the actual rock crushing volume per unit time, min / m, is the average rock crushing volume per unit time, min / m, is the standard drill diameter, mm, The diameter of the drill bit used to drill through the formation, mm, is the actual displacement of drilling fluid, L / min, is the average displacement of drilling fluid, L / min, is the core diameter, cm, is the volume density, .

5. The shallow gas reservoir fluid property identification method according to claim 1, characterized in that: The parameter calculation of the P-wave and S-wave time differences in the shallow gas reservoir data to obtain rock mechanics parameters includes: The longitudinal and transverse wave time differences in the shallow gas reservoir data are calculated using the Lame coefficient calculation formula and the bulk modulus calculation formula to obtain the Lame coefficient and the bulk modulus; the rock mechanics parameters include the Lame coefficient and the bulk modulus; The Lame coefficient calculation formula is: ； The bulk modulus calculation formula is: ； in, is the Lame coefficient, dimensionless, is the volume density, , is the shear wave time difference, , is the longitudinal wave time difference, , K is the bulk modulus, dimensionless.

6. The shallow gas reservoir fluid property identification method according to claim 1, characterized in that: The step of selecting target sensitivity parameters from the shallow gas reservoir data and the rock mechanics parameters according to the sensitivity parameter values ​​includes: Sorting the sensitivity parameter values ​​and determining the number of parameters according to business requirements; Determine the sensitivity parameter value with the largest value from the sorted sensitivity parameter values ​​based on the number of parameters; A target sensitivity parameter corresponding to the sensitivity parameter value with the largest numerical value is selected from the shallow gas reservoir data and the rock mechanics parameters.

7. The method for identifying the fluid properties of a shallow gas reservoir according to any one of claims 1 to 6, characterized in that: The method of calculating the comprehensive indicator factor of the shallow gas reservoir using the target sensitivity parameter includes: obtaining a pre-selected standard sensitivity parameter corresponding to the target sensitivity parameter; The target sensitivity parameter and the standard sensitivity parameter are used to calculate the comprehensive indicator factor of the shallow gas reservoir.

8. A device for identifying the properties of fluid in a shallow gas reservoir, characterized in that: include: The data measurement module is used to measure the shallow gas reservoir data using a preset logging instrument to obtain the shallow gas reservoir data; A parameter calculation module is used to perform parameter calculation on the P-wave and S-wave time differences in the shallow gas reservoir data to obtain rock mechanics parameters; A sensitivity parameter value calculation module, used for performing reservoir fluid property indication sensitivity calculation on the shallow gas reservoir data and the rock mechanics parameters to obtain various sensitivity parameter values; An indicator factor calculation module, used to select target sensitivity parameters from the shallow gas reservoir data and the rock mechanics parameters according to the sensitivity parameter values, and calculate the comprehensive indicator factor of the shallow gas reservoir gas layer using the target sensitivity parameters; The fluid property identification module is used to combine the comprehensive indicator factor of the shallow gas reservoir and the target sensitivity parameter to establish the fluid property identification standard of the shallow gas reservoir, and use the fluid property identification standard to identify the fluid property of the shallow gas reservoir to be identified.

9. An electronic device, characterized in that: include: Memory, used to store computer programs; A processor, used to execute the computer program to implement the method for identifying fluid properties of shallow gas reservoirs as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: Used to store a computer program; wherein, when the computer program is executed by a processor, the method for identifying the fluid properties of a shallow gas reservoir as described in any one of claims 1 to 7 is implemented.

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