A method, apparatus, equipment and medium for identifying the properties of shallow gas reservoir fluids

Abstract

This application discloses a method, apparatus, equipment, and medium for identifying the fluid properties of shallow gas reservoirs, relating to the field of reservoir evaluation technology. It utilizes pre-set logging instruments to measure data from shallow gas reservoirs, obtaining shallow gas reservoir data; calculates the P-wave and S-wave transit times in the shallow gas reservoir data to obtain rock mechanics parameters; calculates the reservoir fluid property indication sensitivity of the shallow gas reservoir data and rock mechanics parameters to obtain values ​​for each sensitivity parameter; selects target sensitivity parameters from the shallow gas reservoir data and rock mechanics parameters based on these sensitivity parameter values; calculates a comprehensive indicator factor for the shallow gas reservoir using the target sensitivity parameters; and combines the comprehensive indicator factor and the target sensitivity parameters to establish a fluid property identification standard for shallow gas reservoirs. Using this fluid property identification standard to identify the fluid properties of the shallow gas reservoir can improve the accuracy of fluid property identification.

Description

Technical Field

[0001] This invention relates to the field of reservoir evaluation technology, and in particular to a method, apparatus, equipment and medium for identifying the fluid properties of shallow gas reservoirs. Background Technology

[0002] Currently, methods and techniques for identifying reservoir fluid properties can be categorized into three types: cross-plotting, curve overlay, and correlation analysis. Among these, typical techniques include porosity-resistivity cross-plotting, density-neutron or acoustic-neutron curve overlay, water saturation-bound water saturation overlay, and porosity-resistivity correlation analysis. These methods have played a significant role in identifying fluid properties in conventional reservoirs and low-permeability to tight sandstone reservoirs. However, for shallow gas reservoirs, due to their shallow burial depth, short diagenetic period, and still-water depositional environment, the rocks are loose, weakly consolidated, and fine-grained. Conventional logging curves exhibit high natural gamma, low resistivity contrast, and low gas saturation response characteristics. Logging curves can only reflect the gas content of the reservoir from one or two aspects, making it difficult to accurately identify fluid properties. This results in a low accuracy rate in identifying shallow gas reservoir fluid properties, posing a significant challenge to reservoir fluid property evaluation and reserve estimation.

[0003] As can be seen from the above, how to accurately identify the fluid properties of shallow gas reservoirs and improve the accuracy of identifying the fluid properties of shallow gas reservoirs is a problem that needs to be solved in this field. Summary of the Invention

[0004] In view of this, the purpose of this invention is to provide a method, apparatus, device, and medium for identifying the properties of shallow gas reservoir fluids, which can accurately identify the properties of shallow gas reservoir fluids and improve the accuracy of identifying the properties of shallow gas reservoir fluids. The specific solution is as follows:

[0005] In a first aspect, this application discloses a method for identifying the fluid properties of shallow gas reservoirs, including:

[0006] Data on shallow gas reservoirs are obtained by using pre-set logging instruments.

[0007] The P-wave and S-wave transit times in the shallow gas reservoir data are calculated to obtain rock mechanical parameters;

[0008] The shallow gas reservoir data and the rock mechanical parameters are used to perform reservoir fluid property indication sensitivity calculations to obtain the values ​​of each sensitivity parameter;

[0009] Based on the values ​​of the aforementioned sensitivity parameters, target sensitivity parameters are selected from the shallow gas reservoir data and the rock mechanics parameters, and the comprehensive indicator factor of the shallow gas reservoir is calculated using the target sensitivity parameters.

[0010] The shallow gas reservoir comprehensive indicator factor 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 properties of the shallow gas reservoir to be identified.

[0011] Optionally, the step of using a preset logging instrument to measure data from the shallow gas reservoir 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 bulk density, deep resistivity, P-wave and S-wave transit time, and total hydrocarbon data.

[0013] Optionally, array acoustic logging instruments can be used to measure data from shallow gas reservoirs to obtain P-wave and S-wave transit times, including:

[0014] The array acoustic logging instrument is used to measure data in shallow gas reservoirs to obtain P-wave and S-wave velocities. The P-wave and S-wave velocities are then converted using the P-wave time difference calculation formula and the S-wave time difference calculation formula to obtain the P-wave and S-wave time differences respectively.

[0015] Alternatively, the array acoustic logging instrument can be used to measure data from shallow gas reservoirs to obtain the P-wave and S-wave time differences;

[0016] The formula for calculating the longitudinal wave time difference is as follows:

[0017] ;

[0018] The formula for calculating the transverse wave time difference is:

[0019] ;

[0020] in, For P-wave time difference, , For the longitudinal wave velocity, , For transverse wave time difference, , For transverse wave velocity, .

[0021] Optionally, gas logging instruments can be used to measure data in shallow gas reservoirs to obtain total hydrocarbon data, including:

[0022] Gas logging instruments are used to measure data from shallow gas reservoirs to obtain gas logging total hydrocarbon curves;

[0023] The gas-measured total hydrocarbon curve is corrected to obtain gas-measured total hydrocarbon data including the corrected gas-measured total hydrocarbon values;

[0024] The formula for calculating the correction is:

[0025] ;

[0026] in, The corrected total hydrocarbon value for gas measurement, %. The measured total hydrocarbon value, % This represents the actual rock fragmentation volume per unit time, in min / m. The average volume of rock fragmentation per unit time, min / m. Standard drill bit diameter, mm. The diameter of the drill bit used to drill through the formation, in mm. This represents the actual drilling fluid discharge rate, in L / min. The average drilling fluid displacement is expressed in L / min. The diameter of the core sample is in centimeters. For bulk density, .

[0027] Optionally, the step of calculating the P-wave and S-wave transit times in the shallow gas reservoir data to obtain rock mechanical parameters includes:

[0028] The Lamé coefficient and bulk modulus were calculated using the formulas for calculating the Lamé coefficient and bulk modulus to obtain the P-wave and S-wave transit times in the shallow gas reservoir data; the rock mechanical parameters include the Lamé coefficient and bulk modulus.

[0029] The formula for calculating the Lamé coefficient is as follows:

[0030] ;

[0031] The formula for calculating the bulk modulus is:

[0032] ;

[0033] in, Let Lamé coefficient be a dimensionless coefficient. For bulk density, , For transverse wave time difference, , For P-wave time difference, K is the bulk modulus, which is dimensionless.

[0034] Optionally, the step of selecting target sensitivity parameters from the shallow gas reservoir data and the rock mechanical parameters based on the values ​​of each of the aforementioned sensitivity parameters includes:

[0035] Sort the values ​​of each sensitivity parameter and determine the number of parameters according to business requirements;

[0036] Based on the number of parameters, the sensitivity parameter value with the largest value is determined from the sorted sensitivity parameter values;

[0037] Select the target sensitivity parameter corresponding to the largest sensitivity parameter value from the shallow gas reservoir data and the rock mechanics parameters.

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

[0039] Obtain the pre-selected standard sensitivity parameters corresponding to the target sensitivity parameters;

[0040] The comprehensive indicator factor of shallow gas reservoirs is calculated using the target sensitivity parameter and the standard sensitivity parameter.

[0041] Secondly, this application discloses a shallow gas reservoir fluid property identification device, comprising:

[0042] The data measurement module is used to measure the shallow gas reservoir using a pre-set logging instrument to obtain shallow gas reservoir data.

[0043] The parameter calculation module is used to calculate the P-wave and S-wave time differences in the shallow gas reservoir data to obtain rock mechanical parameters.

[0044] The sensitivity parameter value calculation module is used to perform reservoir fluid property indication sensitivity calculations on the shallow gas reservoir data and the rock mechanical parameters to obtain the values ​​of each sensitivity parameter.

[0045] The indicator factor calculation module is used to select target sensitivity parameters from the shallow gas reservoir data and the rock mechanics parameters based on the values ​​of each of the aforementioned sensitivity parameters, and to calculate the comprehensive indicator factor of the shallow gas reservoir 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 a fluid property identification standard for the shallow gas reservoir, and to use the fluid property identification standard to identify the fluid properties of the shallow gas reservoir to be identified.

[0047] Thirdly, this application discloses an electronic device, including:

[0048] Memory, used to store computer programs;

[0049] A processor is used to execute the computer program to implement the aforementioned method for identifying the fluid properties of shallow gas reservoirs.

[0050] Fourthly, this application discloses a computer storage medium for storing a computer program; wherein, when the computer program is executed by a processor, it implements the steps of the aforementioned shallow gas reservoir fluid property identification method.

[0051] As can be seen, this application provides a method for identifying the fluid properties of shallow gas reservoirs, including: measuring data of the shallow gas reservoir using a pre-set logging instrument to obtain shallow gas reservoir data; calculating the P-wave and S-wave transit times in the shallow gas reservoir data to obtain rock mechanical parameters; calculating the reservoir fluid property indication sensitivity of the shallow gas reservoir data and the rock mechanical parameters to obtain values ​​of each sensitivity parameter; selecting target sensitivity parameters from the shallow gas reservoir data and the rock mechanical parameters based on each sensitivity parameter value; calculating a comprehensive indicator factor for the shallow gas reservoir using the target sensitivity parameters; combining the comprehensive indicator factor for the shallow gas reservoir and the target sensitivity parameters 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. To improve the accuracy of fluid property identification in this type of reservoir, this application innovatively proposes a comprehensive approach considering lithology, physical properties, electrical properties, and gas-bearing characteristics. Based on the analysis of the sensitivity of conventional, array acoustic logging, and gas logging data to gas reservoir indication, this approach integrates logging and surveying data. Using pre-set logging instruments, data measurements are performed on shallow gas reservoirs to obtain shallow gas reservoir data. Rock mechanical parameters reflecting reservoir mechanical properties are calculated. The sensitivity of the shallow gas reservoir data and rock mechanical parameters to reservoir fluid property indication is calculated. Based on the values ​​of each sensitivity parameter, the most sensitive target sensitivity parameter for indicating shallow gas reservoir fluid properties is selected from the shallow gas reservoir data and rock mechanical parameters. This is used to calculate the comprehensive indicator factor of the shallow gas reservoir, establish a fluid property identification standard for shallow gas reservoirs, and achieve accurate identification of the fluid properties of the shallow gas reservoirs to be identified, thereby improving the accuracy of shallow gas reservoir fluid property identification. Attached Figure Description

[0052] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0053] Figure 1 This is a flowchart of a method for identifying the fluid properties of shallow gas reservoirs disclosed in this application;

[0054] Figure 2This is a comparison diagram of conventional well logging response characteristics of high gas-resistivity layers and shallow gas reservoirs with low contrast in a certain basin, as disclosed in this application.

[0055] Figure 3 This application discloses a method for identifying the fluid properties of shallow gas reservoirs by integrating logging and well logging data.

[0056] Figure 4 This is a comparative analysis of the low-contrast gas reservoir indicator sensitivity parameters of the shallow gas reservoir in the Baiyun Depression of a basin disclosed in this application.

[0057] Figure 5 This application discloses a chart for identifying the fluid properties of shallow gas reservoirs using a gas layer composite indicator factor and a volume density cross plot.

[0058] Figure 6 This application example illustrates a discrimination criterion disclosed in this application for identifying the fluid properties of a shallow gas reservoir in the Baiyun Depression of a 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 This application provides a structural diagram of an electronic device. Detailed Implementation

[0061] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0062] Currently, methods and techniques for identifying reservoir fluid properties can be categorized into three types: cross-plotting, curve overlay, and correlation analysis. Among these, typical techniques include porosity-resistivity cross-plotting, density-neutron or acoustic-neutron curve overlay, water saturation-bound water saturation overlay, and porosity-resistivity correlation analysis. These methods have played a significant role in identifying fluid properties in conventional reservoirs and low-permeability to tight sandstone reservoirs. However, for shallow gas reservoirs, due to their shallow burial depth, short diagenetic period, and still-water depositional environment, the rocks are loose, weakly consolidated, and fine-grained. Conventional logging curves exhibit high natural gamma, low resistivity contrast, and low gas saturation response characteristics. Logging curves can only reflect the gas content of the reservoir from one or two aspects, making it difficult to accurately identify fluid properties. This results in a low accuracy rate in identifying shallow gas reservoir fluid properties, posing a significant challenge to reservoir fluid property evaluation and reserve estimation. As can be seen from the above, how to accurately identify the fluid properties of shallow gas reservoirs and improve the accuracy of identifying the fluid properties of shallow gas reservoirs is a problem that needs to be solved in this field.

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

[0064] Step S11: Use a pre-set logging instrument to measure data of 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 bulk density, deep resistivity, longitudinal and transverse wave transit times, and total hydrocarbon data.

[0066] The process of using an array acoustic logging instrument to measure data in a shallow gas reservoir to obtain the P-wave and S-wave time differences includes: using the array acoustic logging instrument to measure data in a shallow gas reservoir to obtain the P-wave and S-wave velocities; and using the P-wave time difference calculation formula and the S-wave time difference calculation formula to convert the P-wave and S-wave velocities to obtain the P-wave and S-wave time differences respectively.

[0067] Alternatively, the array acoustic logging instrument can be used to measure data from shallow gas reservoirs to obtain the P-wave and S-wave time differences;

[0068] The formula for calculating the longitudinal wave time difference is as follows:

[0069] ;

[0070] The formula for calculating the transverse wave time difference is:

[0071] ;

[0072] in, For P-wave time difference, , For the longitudinal wave velocity, , For transverse wave time difference, , For transverse wave velocity, .

[0073] The process of measuring data in shallow gas reservoirs using gas logging instruments to obtain total hydrocarbon data includes: measuring data in shallow gas reservoirs using gas logging instruments to obtain a total hydrocarbon curve; and correcting the total hydrocarbon curve to obtain total hydrocarbon data including the corrected total hydrocarbon values.

[0074] The formula for calculating the correction is:

[0075] ;

[0076] in, The corrected total hydrocarbon value for gas measurement, %. The measured total hydrocarbon value, % This represents the actual rock fragmentation volume per unit time, in min / m. The average volume of rock fragmentation per unit time, min / m. Standard drill bit diameter, mm. The diameter of the drill bit used to drill through the formation, in mm. This represents the actual drilling fluid discharge rate, in L / min. The average drilling fluid displacement is expressed in L / min. The diameter of the core sample is in centimeters. For bulk density, .

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

[0078] In this embodiment, the Lamé coefficient and bulk modulus calculation formulas are used to calculate the P-wave and S-wave transit times in the shallow gas reservoir data to obtain the Lamé coefficient and bulk modulus; the rock mechanical parameters include the Lamé coefficient and bulk modulus.

[0079] The formula for calculating the Lamé coefficient is as follows:

[0080] ;

[0081] The formula for calculating the bulk modulus is:

[0082] ;

[0083] in, Let Lamé coefficient be a dimensionless coefficient. For bulk density, , For transverse wave time difference, , For P-wave time difference, K is the bulk modulus, which is dimensionless.

[0084] Step S13: Perform reservoir fluid property indication sensitivity calculations on the shallow gas reservoir data and the rock mechanical parameters to obtain the values ​​of each sensitivity parameter.

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

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

[0087] Taking four parameters—total hydrocarbons, deep resistivity, Lamé coefficient, and bulk modulus—as sensitive parameters for indicative of fluid properties in shallow gas reservoirs, and combining well logging data of total hydrocarbons, Lamé coefficient, bulk modulus, and deep resistivity, the following formula is used to establish a comprehensive indicator factor I for shallow gas reservoirs:

[0088] ;

[0089] Where I is the gas layer composite indicator factor, dimensionless; TG_YS is the actual measured total hydrocarbon value, %; and TG_YSw is the total hydrocarbon value of the reference water layer, % For reference water layer Lamé coefficient, The bulk modulus of the reference water layer is given by Rt, where Rt is the deep resistivity in Ω·m. The deep resistivity of the reference water layer is Ω·m; among which, the pre-selected standard sensitivity parameters include the total hydrocarbon value measured by gas in the reference water layer and the bulk modulus of the reference water layer.

[0090] Step S15: Combine the shallow gas reservoir gas layer 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 properties of the shallow gas reservoir to be identified.

[0091] By combining volumetric density and the comprehensive indicator factor I for shallow gas reservoirs, a standard for identifying the fluid properties of shallow gas reservoirs is established. For example, target shallow gas reservoirs can be divided into two main categories: low-contrast gas layers and water layers, 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, high-permeability reservoirs, conventional or array-based sonic logging data can accurately identify reservoir fluid properties. Typically, gas reservoirs exhibit a "three lows, two highs, and one anomaly" response characteristic on conventional logging curves: low spontaneous gamma, low bulk density, low neutron, high sonic transit time, high resistivity, and a significant amplitude of spontaneous potential anomalies. Simultaneously, under standard limestone calibration, there is a clear "mirror image" characteristic between the bulk density and neutron logging curves. These response characteristics allow for intuitive and accurate identification of high-resistivity gas reservoirs. However, for shallow gas reservoirs, factors such as shallow formation depth, short diagenetic period, and still-water depositional environment result in loose rocks, fine lithology, poor physical properties, and low gas saturation. The lower gas saturation leads to a significantly smaller difference in resistivity response between gas and water layers, and the "mirror image" characteristic between the gas layer's bulk density and neutron logging curves is not obvious. Using conventional well logging data, gas reservoir identification methods based on cross plots, curve overlay, and correlation analysis become ineffective, resulting in low accuracy in determining the fluid properties of shallow gas reservoirs.

[0095] The following is a comparison of the conventional and gas logging response curves of a high-resistivity gas layer and a low-resistivity gas layer in a certain well in a certain location: Figure 2As shown in the figure, the intervals 754.0-756.5m, 773.0-781.0m, and 790.0-792.0m are typical high-resistivity gas reservoirs. These three intervals have a natural gamma ray value less than 90.0 API, a deep resistivity greater than 2.0 Ω·m, and high total hydrocarbon content in gas logging. Furthermore, the "mirror image" characteristic between the volumetric density and neutron logging curves is obvious, allowing for relatively accurate identification of these gas reservoirs using conventional logging curves. However, in the intervals 801.0-805.0m and 814.0-824.0m, the natural gamma ray value does not decrease significantly, the deep resistivity is less than 2.0 Ω·m, and the volumetric density-neutron logging curves do not show a "mirror image" characteristic. Only the total hydrocarbon logging curve shows a clear indication of a gas reservoir. For this type of low-contrast gas reservoir, it is difficult to accurately identify it using only one or two logging curves, leading to the omission of such gas reservoirs. Based on the above analysis, in order to improve the accuracy of identifying low-contrast gas layers in shallow gas reservoirs, it is necessary to establish a comprehensive gas layer indicator factor based on a comprehensive analysis of the indicative effects of various types of 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 described using the specific embodiments above, and the specific process is as follows: Figure 3 As shown:

[0096] Step 1: Measure the target reservoir using conventional, array acoustic, and gas logging instruments to obtain the target reservoir's bulk density, deep resistivity, P-wave and S-wave velocities, and total hydrocarbon data. To accurately use the total hydrocarbon data to indicate the fluid properties of shallow gas reservoirs, the actual measured total hydrocarbon curves need to be corrected for engineering factors and drilling fluid.

[0097] Step 2: Process the measured array acoustic logging data to obtain rock mechanics parameters such as Lamé coefficient and bulk modulus. It should be noted that when the measured array acoustic logging data is P-wave and S-wave velocity, the P-wave and S-wave velocity must first be converted into P-wave and S-wave transit time.

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

[0099] ;

[0100] in, This represents the average value of each curve obtained from the gas layer segment. The average value of each curve obtained from the water layer segment is DI, which is a dimensionless sensitivity parameter indicating reservoir fluid properties. A higher DI value indicates that the curve is more sensitive to gas layer indication, and vice versa.

[0101] Step 4: Calculate the reservoir fluid property indication sensitivity parameter DI, rank the ability of each parameter to indicate reservoir fluid properties, and select the parameter that is most sensitive to the indication of shallow gas reservoir fluid properties. Figure 4 Histograms were generated for the DI values ​​(indicating sensitivity parameters) of reservoir fluid properties in three wells in a certain area, showing different parameters. Based on the DI values, parameters with relatively high sensitivity to the indication of shallow gas reservoir fluid properties in this area were identified as total hydrocarbon content, deep resistivity, Lamé coefficient, and bulk modulus. Parameters such as Young's modulus, Poisson's ratio, and P-wave / S-wave velocity ratio showed poor sensitivity to the indication of shallow gas reservoir fluid properties. Therefore, four parameters—total hydrocarbon content, deep resistivity, Lamé coefficient, and bulk modulus—were selected as target sensitivity parameters.

[0102] Step 5: Using the four selected parameters of total hydrocarbons, deep resistivity, Lamé coefficient, and bulk modulus, establish the comprehensive indicator factor I for shallow gas reservoirs;

[0103] Step Six: Combining the shallow gas reservoir comprehensive indicator factor I and volume density, calibrate them using test data to obtain a shallow gas reservoir fluid property identification chart, such as... Figure 5 As shown. Based on Figure 5 The diagram shown illustrates the criteria for identifying the fluid properties of shallow gas reservoirs.

[0104] Using the methods described in steps one through six, the conventional, array acoustic, and gas logging data of the well were processed to obtain the gas reservoir comprehensive indicator factor I, which was then 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 channels display conventional lithology, resistivity, and physical property curves, respectively, serving to identify effective reservoirs, calculate reservoir porosity, and identify reservoir fluid properties. The fourth channel shows the contents of total hydrocarbons, methane, and ethane in gas logging after engineering factor and drilling fluid correction. The fifth channel displays the gas reservoir comprehensive indicator factor I, calculated continuously by combining deep resistivity, corrected total hydrocarbons, Lamé coefficient, and bulk modulus. Based on the conventional logging curve response characteristics, the intervals of 752.0-754.0m, 770.0-772.5m, and 788.0-790.0m are typical high-resistivity gas reservoir intervals, corresponding to high gas reservoir comprehensive indicator factor I values, making them easily identifiable. However, in the well intervals of 793.0-794.0m, 805.0-808.0m, 817.0-818.0m, and 832.0-835.0m, the deep resistivity measured by conventional methods is low, and the "mirror image" characteristic of the density-neutron logging curves is not obvious. Using conventional methods, these intervals could easily be misclassified as non-gas-producing layers. However, the comprehensive gas-producing indicator factor I for these intervals is much greater than 0.2, therefore they are classified as low-contrast gas-producing layers. This classification result is confirmed by test data; the 752.0-822.0m interval, tested using three different nozzles, all showed high-production gas layers, fully demonstrating the reliability of the method described in this invention.

[0105] In this embodiment, a preset logging instrument is used to measure data of the shallow gas reservoir to obtain shallow gas reservoir data; the P-wave and S-wave time differences in the shallow gas reservoir data are calculated to obtain rock mechanical parameters; reservoir fluid property indication sensitivity calculations are performed on the shallow gas reservoir data and the rock mechanical parameters to obtain values ​​of each sensitivity parameter; target sensitivity parameters are selected from the shallow gas reservoir data and the rock mechanical parameters based on the values ​​of each sensitivity parameter, and the shallow gas reservoir gas layer comprehensive indicator factor is calculated using the target sensitivity parameters; the shallow gas reservoir gas layer comprehensive indicator factor and the target sensitivity parameters 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 properties of the shallow gas reservoir to be identified. To improve the accuracy of fluid property identification in this type of reservoir, this application innovatively proposes a comprehensive approach considering lithology, physical properties, electrical properties, and gas-bearing characteristics. Based on the analysis of the sensitivity of conventional, array acoustic logging, and gas logging data to gas reservoir indication, this approach integrates logging and surveying data. Using pre-set logging instruments, data measurements are performed on shallow gas reservoirs to obtain shallow gas reservoir data. Rock mechanical parameters reflecting reservoir mechanical properties are calculated. The sensitivity of the shallow gas reservoir data and rock mechanical parameters to reservoir fluid property indication is calculated. Based on the values ​​of each sensitivity parameter, the most sensitive target sensitivity parameter for indicating shallow gas reservoir fluid properties is selected from the shallow gas reservoir data and rock mechanical parameters. This is used to calculate the comprehensive indicator factor of the shallow gas reservoir, establish a fluid property identification standard for shallow gas reservoirs, and achieve accurate identification of the fluid properties of the shallow gas reservoirs to be identified, thereby improving the accuracy of shallow gas reservoir fluid property identification.

[0106] See Figure 7 As shown in the figure, an embodiment of the present invention discloses a shallow gas reservoir fluid property identification device, which may specifically include:

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

[0108] The parameter calculation module 12 is used to calculate the P-wave and S-wave time differences in the shallow gas reservoir data to obtain rock mechanical parameters.

[0109] 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 mechanical parameters to obtain the values ​​of each sensitivity parameter;

[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 values ​​of each of the aforementioned sensitivity parameters, and to calculate the comprehensive indicator factor of the shallow gas reservoir using the target sensitivity parameters.

[0111] The fluid property identification module 15 is used to combine 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 to use the fluid property identification standard to identify the fluid properties 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 perform data measurements on shallow gas reservoirs using conventional logging instruments, array acoustic logging instruments, and gas logging instruments to obtain shallow gas reservoir data including bulk density, deep resistivity, P-wave and S-wave transit time, and total hydrocarbon data.

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

[0115] The velocity conversion module is used to measure data of shallow gas reservoirs using the array acoustic logging instrument, obtain P-wave and S-wave velocities, and convert the P-wave and S-wave velocities using the P-wave time difference calculation formula and the S-wave time difference calculation formula to obtain the P-wave and S-wave time differences respectively.

[0116] The P-wave and S-wave time difference direct measurement module is used to measure data of shallow gas reservoirs using the array acoustic logging instrument to obtain the P-wave and S-wave time differences.

[0117] The formula for calculating the longitudinal wave time difference is as follows:

[0118] ;

[0119] The formula for calculating the transverse wave time difference is:

[0120] ;

[0121] in, For P-wave time difference, , For the longitudinal wave velocity, , For transverse wave time difference, , For transverse 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 the gas logging full hydrocarbon curve.

[0124] A calibration module is used to calibrate the gas measurement total hydrocarbon curve to obtain gas measurement total hydrocarbon data including the calibrated gas measurement total hydrocarbon value.

[0125] The formula for calculating the correction is:

[0126] ;

[0127] in, The corrected total hydrocarbon value for gas measurement, %. The measured total hydrocarbon value, % This represents the actual rock fragmentation volume per unit time, in min / m. The average volume of rock fragmentation per unit time, min / m. Standard drill bit diameter, mm. The diameter of the drill bit used to drill through the formation, in mm. This represents the actual drilling fluid discharge rate, in L / min. The average drilling fluid displacement is expressed in L / min. The diameter of the core sample is in centimeters. For bulk density, .

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

[0129] The rock mechanics parameter calculation module is used to calculate the P-wave and S-wave transit times in the shallow gas reservoir data using the Lamé coefficient calculation formula and the bulk modulus calculation formula, so as to obtain the Lamé coefficient and the bulk modulus; the rock mechanics parameters include the Lamé coefficient and the bulk modulus;

[0130] The formula for calculating the Lamé coefficient is as follows:

[0131] ;

[0132] The formula for calculating the bulk modulus is:

[0133] ;

[0134] in, Let Lamé coefficient be a dimensionless coefficient. For bulk density, , For transverse wave time difference, , For P-wave time difference, K is the bulk modulus, which is dimensionless.

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

[0136] The sorting module is used to sort the values ​​of each of the aforementioned sensitivity parameters and determine the number of parameters according to business requirements;

[0137] The sensitivity parameter value filtering module is used to determine 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 largest sensitivity parameter value from the shallow gas reservoir data and the rock mechanical parameters.

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

[0140] The standard sensitivity parameter acquisition module is used to acquire pre-selected standard sensitivity parameters corresponding to the target sensitivity parameters.

[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 using the target sensitivity parameter and the standard sensitivity parameter.

[0142] Figure 8 This is a schematic diagram of an electronic device provided in an embodiment of this 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 stores 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 foregoing embodiments.

[0143] In this embodiment, the power supply 23 is used to provide operating 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 external devices, and the communication protocol it follows can be any communication protocol applicable to the technical solution of this application, and is not specifically limited here; the input / output interface 25 is used to acquire 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 resource storage, can be a read-only memory, random access memory, disk or optical disk, etc. The resources stored on it include operating system 221, computer program 222 and data 223, etc., and the storage method can be temporary storage or permanent storage.

[0145] The operating system 221 manages and controls the various hardware devices on the electronic device 20 and the computer program 222 to enable the processor 21 to perform calculations and processing on the data 223 in the memory 22. It can be Windows, Unix, Linux, etc. The computer program 222, in addition to including a computer program capable of performing the shallow gas reservoir fluid property identification method executed by the electronic device 20 as disclosed in any of the foregoing embodiments, may further include computer programs capable of performing other specific tasks. The data 223 may include data received by the shallow gas reservoir fluid property identification device from external devices, as well as data collected by its own input / output interface 25.

[0146] The steps of the methods or algorithms described in conjunction with the embodiments disclosed herein can be implemented directly by hardware, a software module executed by a processor, or a combination of both. The software module can be located in random access memory (RAM), main memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, removable disk, CD-ROM, or any other form of storage medium known in the art.

[0147] Furthermore, this application also discloses a computer-readable storage medium storing a computer program. When the computer program is loaded and executed by a processor, it implements the steps of the shallow gas reservoir fluid property identification method disclosed in any of the foregoing embodiments.

[0148] Finally, it should be noted that in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0149] The present invention provides a detailed description of a method, apparatus, device, and storage medium for identifying the fluid properties of shallow gas reservoirs. Specific examples have been used to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of the present invention. At the same time, those skilled in the art will recognize that there will be changes in the specific implementation methods and application scope based on the ideas of the present invention. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A method for identifying the fluid properties of shallow gas reservoirs, characterized in that, include: Data on shallow gas reservoirs are obtained by using pre-set logging instruments. The P-wave and S-wave transit times in the shallow gas reservoir data are calculated to obtain rock mechanical parameters; Reservoir fluid property indication sensitivity calculations were performed on the shallow gas reservoir data and the rock mechanical parameters to obtain the values ​​of each sensitivity parameter; the sensitivity parameter values ​​are as follows: ； Among them, the DI sensitivity parameter is dimensionless. This represents the average value of each curve obtained from the water layer section. This represents the average value of each curve obtained from the gas layer segment; Target sensitivity parameters are selected from the shallow gas reservoir data and rock mechanics parameters based on the values ​​of the aforementioned sensitivity parameters. The comprehensive indicator factor for the shallow gas reservoir is then calculated using these target sensitivity parameters. The comprehensive indicator factor for the gas reservoir is: ； Where I is the gas layer comprehensive indicator factor, dimensionless, and TG_YS is the actual measured total hydrocarbon value, %. For reference water layer, the total hydrocarbon value measured by gas is %, For reference water layer Lamé coefficient, Let Lamé coefficient be a dimensionless coefficient. The bulk modulus of the reference water layer is given by K, which is dimensionless, and Rt is the deep resistivity in Ω·m. The deep resistivity of the reference water layer is expressed in Ω·m. The shallow gas reservoir comprehensive indicator factor 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 properties of the shallow gas reservoir to be identified.

2. The method for identifying the fluid properties of shallow gas reservoirs according to claim 1, characterized in that, The method of using a pre-set logging instrument to measure data from shallow gas reservoirs 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 bulk density, deep resistivity, P-wave and S-wave transit time, and total hydrocarbon data.

3. The method for identifying the fluid properties of shallow gas reservoirs according to claim 2, characterized in that, Data measurements of shallow gas reservoirs are performed using array acoustic logging instruments to obtain P-wave and S-wave transit times, including: The array acoustic logging instrument is used to measure data in shallow gas reservoirs to obtain P-wave and S-wave velocities. The P-wave and S-wave velocities are then converted using the P-wave time difference calculation formula and the S-wave time difference calculation formula to obtain the P-wave and S-wave time differences respectively. Alternatively, the array acoustic logging instrument can be used to measure data from shallow gas reservoirs to obtain the P-wave and S-wave time differences; The formula for calculating the longitudinal wave time difference is as follows: ； The formula for calculating the transverse wave time difference is: ； in, For P-wave time difference, , For the longitudinal wave velocity, , For transverse wave time difference, , For transverse wave velocity, .

4. The method for identifying the fluid properties of shallow gas reservoirs according to claim 2, characterized in that, Gas logging instruments are used to measure data in shallow gas reservoirs to obtain total hydrocarbon data, including: Gas logging instruments are used to measure data from shallow gas reservoirs to obtain gas logging total hydrocarbon curves; The gas-measured total hydrocarbon curve is corrected to obtain gas-measured total hydrocarbon data including the corrected gas-measured total hydrocarbon values; The formula for calculating the correction is: ； in, The corrected total hydrocarbon value for gas measurement, %. The measured total hydrocarbon value, % This represents the actual rock fragmentation volume per unit time, in min / m. The average volume of rock fragmentation per unit time, min / m. Standard drill bit diameter, mm. The diameter of the drill bit used to drill through the formation, in mm. This represents the actual drilling fluid discharge rate, in L / min. The average drilling fluid displacement is expressed in L / min. The diameter of the core sample is in centimeters. For bulk density, .

5. The method for identifying the fluid properties of shallow gas reservoirs according to claim 1, characterized in that, The calculation of P-wave and S-wave transit times in the shallow gas reservoir data to obtain rock mechanical parameters includes: The Lamé coefficient and bulk modulus were calculated using the formulas for calculating the Lamé coefficient and bulk modulus to obtain the P-wave and S-wave transit times in the shallow gas reservoir data; the rock mechanical parameters include the Lamé coefficient and bulk modulus. The formula for calculating the Lamé coefficient is as follows: ； The formula for calculating the bulk modulus is: ； in, Let Lamé coefficient be a dimensionless coefficient. For bulk density, , For transverse wave time difference, , For P-wave time difference, K is the bulk modulus, which is dimensionless.

6. The method for identifying the fluid properties of shallow gas reservoirs according to claim 1, characterized in that, The step of selecting target sensitivity parameters from the shallow gas reservoir data and the rock mechanical parameters based on the values ​​of each of the aforementioned sensitivity parameters includes: Sort the values ​​of each sensitivity parameter and determine the number of parameters according to business requirements; Based on the number of parameters, the sensitivity parameter value with the largest value is determined from the sorted sensitivity parameter values; Select the target sensitivity parameter corresponding to the largest sensitivity parameter value from the shallow gas reservoir data and the rock mechanics parameters.

7. The method for identifying the fluid properties of shallow gas reservoirs according to any one of claims 1 to 6, characterized in that, The calculation of the comprehensive indicator factor of shallow gas reservoir using the target sensitivity parameter includes: Obtain the pre-selected standard sensitivity parameters corresponding to the target sensitivity parameters; The comprehensive indicator factor of shallow gas reservoirs is calculated using the target sensitivity parameter and the standard sensitivity parameter.

8. A device for identifying the fluid properties of shallow gas reservoirs, characterized in that, include: The data measurement module is used to measure the shallow gas reservoir using a pre-set logging instrument to obtain shallow gas reservoir data. The parameter calculation module is used to calculate the P-wave and S-wave time differences in the shallow gas reservoir data to obtain rock mechanical parameters. The sensitivity parameter value calculation module is used to perform reservoir fluid property indication sensitivity calculations on the shallow gas reservoir data and the rock mechanical parameters to obtain the values ​​of each sensitivity parameter; the sensitivity parameter values ​​are: ； Among them, the DI sensitivity parameter is dimensionless. This represents the average value of each curve obtained from the water layer section. This represents the average value of each curve obtained from the gas layer segment; The indicator factor calculation module is used to select target sensitivity parameters from the shallow gas reservoir data and the rock mechanics parameters based on the values ​​of each of the aforementioned sensitivity parameters, and to calculate the comprehensive indicator factor of the shallow gas reservoir using the target sensitivity parameters; the comprehensive indicator factor of the gas reservoir is: ； Where I is the gas layer comprehensive indicator factor, dimensionless, and TG_YS is the actual measured total hydrocarbon value, %. For reference water layer, the total hydrocarbon value measured by gas is %, For reference water layer Lamé coefficient, Let Lamé coefficient be a dimensionless coefficient. The bulk modulus of the reference water layer is given by K, which is dimensionless, and Rt is the deep resistivity in Ω·m. The deep resistivity of the reference water layer is expressed in Ω·m. 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 a fluid property identification standard for the shallow gas reservoir, and to use the fluid property identification standard to identify the fluid properties of the shallow gas reservoir to be identified.

9. An electronic device, characterized in that, include: Memory, used to store computer programs; A processor for executing the computer program to implement the shallow gas reservoir fluid property identification method 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, it implements the shallow gas reservoir fluid property identification method as described in any one of claims 1 to 7.

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