Reservoir identification method and device and electronic equipment

Abstract

The invention provides a reservoir identification method and device and electronic equipment, and belongs to the technical field of data processing. The method comprises the following steps: acquiring a plurality of rock debris particle size analysis data of a to-be-identified stratum of a target well; a fitting formula for describing the linear relation of the core particle size analysis data of the known well is obtained, and based on the multiple pieces of rock debris particle size analysis data and the fitting formula, multiple pieces of fitted rock debris particle size analysis data of the target well after fitting are obtained; based on the plurality of pieces of fitting rock debris particle size analysis data, calculating a particle size gamma value or a fusion gamma value based on the stratum to be identified; calculating a reservoir index of the to-be-identified place based on the granularity gamma value or the fusion gamma value; and constructing a judgment coordinate system based on the granularity gamma value and the reservoir index, or constructing the judgment coordinate system based on the fusion gamma value and the reservoir index, and determining a reservoir identification result of the stratum to be identified based on a similarity coefficient between adjacent coordinate points in the judgment coordinate system. The method solves the problem that the existing method cannot quickly identify the reservoir by using granularity analysis data.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and particularly relates to a reservoir identification method, a reservoir identification device, and an electronic device. Background Art

[0002] Currently, during the drilling process of a target well, to characterize the lithology and reservoir development, it mainly relies on the method of visual observation combined with identification using a T-type microscope to identify the lithology of the well section to be identified in the target well, and the influence of human factors is relatively large. If the grain size identification of the reservoir in the target well is inaccurate, it will affect the judgment of reservoir identification, that is, it is impossible to quickly identify the reservoir using grain size analysis data at the drilling and logging site, thereby affecting the adjustment of the horizontal wellbore trajectory and the drilling encounter rate of high-quality reservoirs. Summary of the Invention

[0003] The purpose of the embodiments of the present invention is to provide a reservoir identification method, device, and electronic device to solve the defect that the existing method cannot quickly identify the reservoir using grain size analysis data at the drilling and logging site, thereby affecting the adjustment of the horizontal wellbore trajectory and the drilling encounter rate of high-quality reservoirs.

[0004] To achieve the above purpose, the embodiments of the present invention provide a reservoir identification method, including:

[0005] Obtain multiple cuttings grain size analysis data of the formation to be identified in the target well;

[0006] Obtain a fitting formula describing the linear relationship of the core grain size analysis data of a known well, and based on the multiple cuttings grain size analysis data and the fitting formula, obtain multiple fitted cuttings grain size analysis data of the target well after fitting;

[0007] Based on the multiple fitted cuttings grain size analysis data, calculate the grain size gamma value or the fusion gamma value based on the formation to be identified;

[0008] Calculate the reservoir index of the formation to be identified based on the grain size gamma value or the fusion gamma value;

[0009] Based on the grain size gamma value and the reservoir index, construct a determination coordinate system, or based on the fusion gamma value and the reservoir index, construct a determination coordinate system, and determine the reservoir identification result of the formation to be identified based on the similarity coefficient between adjacent coordinate points in the determination coordinate system during the drilling of the formation to be identified.

[0010] Optionally, the obtaining multiple fitted cuttings grain size analysis data of the target well after fitting based on the multiple cuttings grain size analysis data and the fitting formula includes:

[0011] Substitute all the cuttings grain size analysis data into the fitting formula one by one to obtain multiple fitted cuttings grain size analysis data of the target well after fitting.

[0012] Optionally, calculating the grain-size gamma value based on the formation to be identified based on the multiple fitted cuttings grain-size analysis data includes:

[0013] Performing lithology classification and naming based on grain size on the basis of the multiple fitted cuttings grain-size analysis data to obtain the percentages of different lithology types of the cuttings of the formation to be identified;

[0014] Obtaining the shale percentage of the cuttings of the formation to be identified from the percentages of different lithology types of the cuttings of the formation to be identified, and calculating the grain-size gamma value based on the cuttings of the formation to be identified based on the shale percentage of the cuttings of the formation to be identified, the gamma value corresponding to pure shale, and the gamma value corresponding to pure quartz sandstone.

[0015] Optionally, calculating the integrated gamma value based on the formation to be identified based on the multiple fitted cuttings grain-size analysis data includes:

[0016] Performing lithology classification and naming based on grain size on the basis of the multiple fitted cuttings grain-size analysis data to obtain the percentages of different lithology types of the cuttings of the formation to be identified;

[0017] Obtaining the shale percentage of the cuttings of the formation to be identified from the percentages of different lithology types of the cuttings of the formation to be identified, and calculating the grain-size gamma value based on the cuttings of the formation to be identified based on the shale percentage of the cuttings of the formation to be identified, the gamma value corresponding to pure shale, and the gamma value corresponding to pure quartz sandstone;

[0018] Calculating the integrated gamma value based on the cuttings of the formation to be identified based on the grain-size gamma value, the gamma value of logging while drilling, and the weight coefficient of the gamma value of logging while drilling.

[0019] Optionally, the calculation of the grain-size gamma value based on the cuttings of the formation to be identified based on the shale percentage of the cuttings of the formation to be identified, the gamma value corresponding to pure shale, and the gamma value corresponding to pure quartz sandstone is represented by the following formula:

[0020] GR L = (GR sh - GR sa ) log2(3V shl + 1) + GR sa ;

[0021] wherein, GR L is the grain-size gamma value based on the cuttings of the formation to be identified, GR sh is the gamma value corresponding to pure shale, GR sa is the gamma value corresponding to pure quartz sandstone, and V shl is the shale percentage of the cuttings of the formation to be identified.

[0022] Optionally, calculating a fused gamma value of cuttings of a formation to be identified based on the granularity gamma value, the logging-while-drilling gamma value, and the weight coefficient of the logging-while-drilling gamma value, which is represented by the following formula:

[0023] GR R = Q c × GR c + (1 - Q c ) × GR L ;

[0024] Wherein, GR R is the fused gamma value of cuttings of the formation to be identified, GR c is the logging-while-drilling gamma value, Q c is the weight coefficient of the logging-while-drilling gamma value, and GR L is the granularity gamma value;

[0025] The weight coefficient Q of the logging-while-drilling gamma value c is represented by the following formula:

[0026] Q c = (πL 2 + 2πd) / (π(L + d) 2 );

[0027] Wherein, L is the set logging gamma detection depth, and d is the diameter of the drilled wellbore.

[0028] Optionally, calculating the reservoir index of the formation to be identified based on the granularity gamma value includes:

[0029] Calculating an intermediate operation coefficient based on the common logarithm of the gas logging data of the formation to be identified in the target well, the standard deviation of the common logarithms of the historical gas logging data of the drilled formations, the average value of the common logarithms of the historical gas logging data of the drilled formations, the drilling time of the formation to be identified, the standard deviation of the historical drilling times of the drilled formations, and the average value of the historical drilling times of the drilled formations;

[0030] Calculating a compensation coefficient based on the gamma value corresponding to pure shale, the gamma value corresponding to pure quartz sandstone, the intermediate operation coefficient, and the absolute value of the intermediate operation coefficient;

[0031] Calculating a first corrected granularity gamma value based on the granularity gamma value and the compensation coefficient;

[0032] Calculating the reservoir index of the formation to be identified based on the first corrected granularity gamma value.

[0033] Optionally, calculate the intermediate operation coefficient based on the common logarithm of the gas logging data of the formation to be identified in the target well, the standard deviation of the common logarithm of the historical gas logging data of the drilled formation, the average value of the common logarithm of the historical gas logging data of the drilled formation, the drilling time of the formation to be identified, the standard deviation of the historical drilling time of the drilled formation, and the average value of the historical drilling time of the drilled formation, which is expressed by the following formula:

[0034] Z = (V - aver(V)) / V' - (ROP - aver(ROP)) / ROP';

[0035] Wherein, Z is the intermediate operation coefficient, V is the common logarithm of the gas logging data of the formation to be identified, V' is the standard deviation of the common logarithm of the historical gas logging data of the drilled formation, aver(V) is the average value of the common logarithm of the historical gas logging data of the drilled formation, ROP is the drilling time of the formation to be identified, ROP' is the standard deviation of the historical drilling time of the drilled formation, and aver(ROP) is the average value of the historical drilling time of the drilled formation;

[0036] Calculate the compensation coefficient based on the gamma value corresponding to pure shale, the gamma value corresponding to pure quartz sandstone, the intermediate operation coefficient, and the absolute value of the intermediate operation coefficient, which is expressed by the following formula:

[0037] Φ R = (GR sh - GR sa ) × (Z + ABS(Z)) / 2;

[0038] Wherein, Φ R is the compensation coefficient, GR sh is the gamma value corresponding to pure shale, GR sa is the gamma value corresponding to pure quartz sandstone, Z is the intermediate operation coefficient, and ABS(Z) is the absolute value of the intermediate operation coefficient;

[0039] Calculate the first corrected grain size gamma value based on the grain size gamma value and the compensation coefficient, which is expressed by the following formula:

[0040] GR Φ = GR L - Φ R ; Wherein, GR Φ is the first corrected grain size gamma value, and GR L is the grain size gamma value;

[0041] Calculate the reservoir index of the formation to be identified based on the first corrected grain size gamma value, which is expressed by the following formula:

[0042] Φ L = (GR Φ - MIN(GR Φ )) / 10 * (MAX(GRΦ ) - MIN(GR Φ ));

[0043] where Φ L is the reservoir index of the reservoir to be identified, GR Φ is the first corrected grain size gamma value, MIN(GR Φ ) is the minimum value of the historical reservoir index of the drilled formation, MAX(GR Φ ) is the maximum value of the historical reservoir index of the drilled formation.

[0044] Optionally, calculating the reservoir index of the formation to be identified based on the fused gamma value includes:

[0045] Calculating an intermediate operation coefficient based on the common logarithm of the gas logging data of the formation to be identified in the target well, the standard deviation of the common logarithms of the historical gas logging data of the drilled formation, the average value of the common logarithms of the historical gas logging data of the drilled formation, the drilling time of the formation to be identified, the standard deviation of the historical drilling times of the drilled formation, and the average value of the historical drilling times of the drilled formation;

[0046] Calculating a compensation coefficient based on the gamma value corresponding to pure shale, the gamma value corresponding to pure quartz sandstone, the intermediate operation coefficient, and the absolute value of the intermediate operation coefficient;

[0047] Calculating a second corrected grain size gamma value based on the fused gamma value and the compensation coefficient;

[0048] Calculating the reservoir index of the formation to be identified based on the second corrected grain size gamma value.

[0049] Optionally, calculating the intermediate operation coefficient based on the common logarithm of the gas logging data of the formation to be identified in the target well, the standard deviation of the common logarithms of the historical gas logging data of the drilled formation, the average value of the common logarithms of the historical gas logging data of the drilled formation, the drilling time of the formation to be identified, the standard deviation of the historical drilling times of the drilled formation, and the average value of the historical drilling times of the drilled formation is expressed by the following formula:

[0050] Z = (V - aver(V)) / V' - (ROP - aver(ROP)) / ROP';

[0051] where Z is the intermediate operation coefficient, V is the common logarithm of the gas logging data of the formation to be identified, V' is the standard deviation of the common logarithms of the historical gas logging data of the drilled formation, aver(V) is the average value of the common logarithms of the historical gas logging data of the drilled formation, ROP is the drilling time of the formation to be identified, ROP' is the standard deviation of the historical drilling times of the drilled formation, and aver(ROP) is the average value of the historical drilling times of the drilled formation;

[0052] The compensation coefficient is calculated based on the gamma value corresponding to pure mudstone, the gamma value corresponding to pure quartz sandstone, the intermediate operation coefficient, and the absolute value of the intermediate operation coefficient, and is expressed by the following formula:

[0053] Φ R =(GR sh -GR sa )×(Z + ABS(Z)) / 2;

[0054] where Φ R is the compensation coefficient, GR sh is the gamma value corresponding to pure mudstone, GR sa is the gamma value corresponding to pure quartz sandstone, Z is the intermediate operation coefficient, and ABS(Z) is the absolute value of the intermediate operation coefficient;

[0055] The second corrected grain size gamma value is calculated based on the fused gamma value and the compensation coefficient, and is expressed by the following formula:

[0056] GR Φ =GR R -Φ R ; where GR Φ is the second corrected grain size gamma value, and GR R is the fused gamma value;

[0057] The reservoir index of the formation to be identified is calculated based on the second corrected grain size gamma value, and is expressed by the following formula:

[0058] Φ L =(GR Φ -MIN(GR Φ )) / 10*(MAX(GR Φ )-MIN(GR Φ ));

[0059] where Φ L is the reservoir index of the reservoir to be identified, GR Φ is the second corrected grain size gamma value, MIN(GR Φ ) is the minimum value of the historical reservoir indices of the drilled formations, and MAX(GR Φ ) is the maximum value of the historical reservoir indices of the drilled formations.

[0060] Optionally, when drilling the reservoir to be identified, determining the reservoir identification result of the reservoir to be identified based on the similarity coefficient between adjacent coordinate points in the determination coordinate system includes:

[0061] When the similarity coefficient between adjacent coordinate points in the determination coordinate system is less than or equal to a set threshold during drilling into the reservoir to be identified, it is determined that continuing drilling will reach a non-reservoir. In the case where the trajectory can still be adjusted in a timely manner within the controllable range of the adjustment critical angle to continue drilling in the current reservoir, the drilling trajectory is adjusted to the previous normal point until the similarity coefficient between adjacent coordinate points is gradually adjusted to be greater than the set threshold within the controllable range of the adjustment critical angle.

[0062] An embodiment of the present invention further provides a reservoir identification device, including:

[0063] A data acquisition module, configured to acquire a plurality of cuttings grain size analysis data of the formation to be identified of the target well;

[0064] A fitting module, configured to obtain a fitting formula describing the linear relationship of the core grain size analysis data of the known well, and based on the plurality of cuttings grain size analysis data and the fitting formula, obtain a plurality of fitted cuttings grain size analysis data of the target well after fitting;

[0065] A first calculation module, configured to calculate a grain gamma value or a fusion gamma value based on the plurality of fitted cuttings grain size analysis data for the formation to be identified;

[0066] A second calculation module, configured to calculate a reservoir index of the formation to be identified based on the grain gamma value or the fusion gamma value;

[0067] A reservoir identification module, configured to construct a determination coordinate system based on the grain gamma value and the reservoir index, or construct a determination coordinate system based on the fusion gamma value and the reservoir index, and determine the reservoir identification result of the formation to be identified based on the similarity coefficient between adjacent coordinate points in the determination coordinate system during drilling into the formation to be identified.

[0068] Optionally, the obtaining a plurality of fitted cuttings grain size analysis data of the target well after fitting based on the plurality of cuttings grain size analysis data and the fitting formula includes:

[0069] Substituting all the cuttings grain size analysis data into the fitting formula one by one to obtain a plurality of fitted cuttings grain size analysis data of the target well after fitting.

[0070] Optionally, the calculating a grain gamma value based on the plurality of fitted cuttings grain size analysis data for the formation to be identified includes:

[0071] Performing grain-based lithology classification and naming based on the plurality of fitted cuttings grain size analysis data to obtain the percentages of different lithology types of the cuttings in the formation to be identified;

[0072] Obtain the shale percentage of the cuttings of the formation to be identified from the percentages of different lithology types of the cuttings of the formation to be identified, and calculate the grain-size gamma value based on the shale percentage of the cuttings of the formation to be identified, the gamma value corresponding to pure shale, and the gamma value corresponding to pure quartz sandstone.

[0073] Optionally, calculating the fused gamma value based on the formation to be identified from the multiple fitting cuttings grain-size analysis data includes:

[0074] Conduct lithology classification and naming based on grain size from the multiple fitting cuttings grain-size analysis data to obtain the percentages of different lithology types of the cuttings of the formation to be identified;

[0075] Obtain the shale percentage of the cuttings of the formation to be identified from the percentages of different lithology types of the cuttings of the formation to be identified, and calculate the grain-size gamma value based on the shale percentage of the cuttings of the formation to be identified, the gamma value corresponding to pure shale, and the gamma value corresponding to pure quartz sandstone;

[0076] Calculate the fused gamma value based on the cuttings of the formation to be identified based on the grain-size gamma value, the gamma value of logging while drilling, and the weight coefficient of the gamma value of logging while drilling.

[0077] Optionally, calculating the grain-size gamma value based on the shale percentage of the cuttings of the formation to be identified, the gamma value corresponding to pure shale, and the gamma value corresponding to pure quartz sandstone is expressed by the following formula:

[0078] GR L =(GR sh -GR sa )log2(3V shl +1)+GR sa ;

[0079] Wherein, GR L is the grain-size gamma value based on the cuttings of the formation to be identified, GR sh is the gamma value corresponding to pure shale, GR sa is the gamma value corresponding to pure quartz sandstone, and V shl is the shale percentage of the cuttings of the formation to be identified.

[0080] Optionally, calculating the fused gamma value based on the grain-size gamma value, the gamma value of logging while drilling, and the weight coefficient of the gamma value of logging while drilling is expressed by the following formula:

[0081] GR R =Q c ×GR c +(1-Qc )×GR L ;

[0082] wherein, GR R is the fusion gamma value of the cuttings of the formation to be identified, GR c is the gamma value of logging while drilling, Q c is the weighting coefficient of the gamma value of logging while drilling, GR L is the grain-size gamma value;

[0083] The weighting coefficient Q of the gamma value of logging while drilling c is expressed by the following formula:

[0084] Q c =(πL 2 +2πd) / (π(L + d) 2 );

[0085] wherein, L is the set logging gamma detection depth, and d is the diameter of the drilled wellbore.

[0086] Optionally, calculating the reservoir index of the formation to be identified based on the grain-size gamma value includes:

[0087] Calculating an intermediate operation coefficient based on the common logarithm of the gas logging data of the formation to be identified in the target well, the standard deviation of the common logarithms of the historical gas logging data of the drilled formations, the average value of the common logarithms of the historical gas logging data of the drilled formations, the drilling time of the formation to be identified, the standard deviation of the historical drilling times of the drilled formations, and the average value of the historical drilling times of the drilled formations;

[0088] Calculating a compensation coefficient based on the gamma value corresponding to pure shale, the gamma value corresponding to pure quartz sandstone, the intermediate operation coefficient, and the absolute value of the intermediate operation coefficient;

[0089] Calculating a first corrected grain-size gamma value based on the grain-size gamma value and the compensation coefficient;

[0090] Calculating the reservoir index of the formation to be identified based on the first corrected grain-size gamma value.

[0091] Optionally, calculating the intermediate operation coefficient based on the common logarithm of the gas logging data of the formation to be identified in the target well, the standard deviation of the common logarithms of the historical gas logging data of the drilled formations, the average value of the common logarithms of the historical gas logging data of the drilled formations, the drilling time of the formation to be identified, the standard deviation of the historical drilling times of the drilled formations, and the average value of the historical drilling times of the drilled formations is expressed by the following formula:

[0092] Z=(V - aver(V)) / V'-(ROP - aver(ROP)) / ROP';

[0093] Wherein, Z is the intermediate operation coefficient, V is the common logarithm of the gas logging data of the formation to be identified, V' is the standard deviation of the common logarithm of the historical gas logging data of the drilled formation, aver(V) is the average value of the common logarithm of the historical gas logging data of the drilled formation, ROP is the drilling time of the formation to be identified, ROP' is the standard deviation of the historical drilling time of the drilled formation, and aver(ROP) is the average value of the historical drilling time of the drilled formation;

[0094] The compensation coefficient is calculated based on the gamma value corresponding to pure shale, the gamma value corresponding to pure quartz sandstone, the intermediate operation coefficient, and the absolute value of the intermediate operation coefficient, and is expressed by the following formula:

[0095] Φ R =(GR sh -GR sa )×(Z + ABS(Z)) / 2;

[0096] Wherein, Φ R is the compensation coefficient, GR sh is the gamma value corresponding to pure shale, GR sa is the gamma value corresponding to pure quartz sandstone, Z is the intermediate operation coefficient, and ABS(Z) is the absolute value of the intermediate operation coefficient;

[0097] The first corrected grain size gamma value is calculated based on the grain size gamma value and the compensation coefficient, and is expressed by the following formula:

[0098] GR Φ =GR L -Φ R ; wherein, GR Φ is the first corrected grain size gamma value, and GR L is the grain size gamma value;

[0099] The reservoir index of the formation to be identified is calculated based on the first corrected grain size gamma value, and is expressed by the following formula:

[0100] Φ L =(GR Φ -MIN(GR Φ )) / 10 * (MAX(GR Φ ) - MIN(GR Φ ));

[0101] Wherein Φ L is the reservoir index of the formation to be identified, GR Φ is the first corrected grain size gamma value, MIN(GR Φ ) is the minimum value of the historical reservoir index of the drilled formation, and MAX(GR Φ ) is the maximum value of the historical reservoir index of the drilled formation.

[0102] Optionally, calculating the reservoir index of the formation to be identified based on the fused gamma value includes:

[0103] Calculating an intermediate operation coefficient based on the common logarithm of the gas logging data of the formation to be identified in the target well, the standard deviation of the common logarithms of the historical gas logging data of the drilled formations, the average value of the common logarithms of the historical gas logging data of the drilled formations, the drilling time of the formation to be identified, the standard deviation of the historical drilling times of the drilled formations, and the average value of the historical drilling times of the drilled formations;

[0104] Calculating a compensation coefficient based on the gamma value corresponding to pure shale, the gamma value corresponding to pure quartz sandstone, the intermediate operation coefficient, and the absolute value of the intermediate operation coefficient;

[0105] Calculating a second corrected grain size gamma value based on the fused gamma value and the compensation coefficient;

[0106] Calculating the reservoir index of the formation to be identified based on the second corrected grain size gamma value.

[0107] Optionally, calculating the intermediate operation coefficient based on the common logarithm of the gas logging data of the formation to be identified in the target well, the standard deviation of the common logarithms of the historical gas logging data of the drilled formations, the average value of the common logarithms of the historical gas logging data of the drilled formations, the drilling time of the formation to be identified, the standard deviation of the historical drilling times of the drilled formations, and the average value of the historical drilling times of the drilled formations is expressed by the following formula:

[0108] Z = (V - aver(V)) / V' - (ROP - aver(ROP)) / ROP';

[0109] Where Z is the intermediate operation coefficient, V is the common logarithm of the gas logging data of the formation to be identified, V' is the standard deviation of the common logarithms of the historical gas logging data of the drilled formations, aver(V) is the average value of the common logarithms of the historical gas logging data of the drilled formations, ROP is the drilling time of the formation to be identified, ROP' is the standard deviation of the historical drilling times of the drilled formations, and aver(ROP) is the average value of the historical drilling times of the drilled formations;

[0110] Calculating the compensation coefficient based on the gamma value corresponding to pure shale, the gamma value corresponding to pure quartz sandstone, the intermediate operation coefficient, and the absolute value of the intermediate operation coefficient is expressed by the following formula:

[0111] Φ R = (GR sh - GR sa ) × (Z + ABS(Z)) / 2;

[0112] Where Φ R is the compensation coefficient, GR sh is the gamma value corresponding to pure shale, GR saThe gamma value corresponding to pure quartz sandstone, Z is the intermediate operation coefficient, and ABS(Z) is the absolute value of the intermediate operation coefficient;

[0113] Calculating the second corrected grain size gamma value based on the fused gamma value and the compensation coefficient is expressed by the following formula:

[0114] GR Φ = GR R - Φ R ; where GR Φ is the second corrected grain size gamma value, and GR R is the fused gamma value;

[0115] Calculating the reservoir index of the formation to be identified based on the second corrected grain size gamma value is expressed by the following formula:

[0116] Φ L = (GR Φ - MIN(GR Φ )) / 10 * (MAX(GR Φ ) - MIN(GR Φ ));

[0117] where Φ L is the reservoir index of the reservoir to be identified, GR Φ is the second corrected grain size gamma value, MIN(GR Φ ) is the minimum value of the historical reservoir index of the drilled formation, and MAX(GR Φ ) is the maximum value of the historical reservoir index of the drilled formation.

[0118] Optionally, determining the reservoir identification result of the reservoir to be identified based on the similarity coefficient between adjacent coordinate points in the determination coordinate system when drilling the reservoir to be identified includes:

[0119] When the similarity coefficient between adjacent coordinate points in the determination coordinate system is less than or equal to the set threshold when drilling the reservoir to be identified, it is determined that continuing to drill will reach a non-reservoir. In the case where the trajectory can still be adjusted in time within the controllable range of the critical angle to continue drilling in the current reservoir, the drilling trajectory is adjusted to the previous normal point until the similarity coefficient between adjacent coordinate points is gradually adjusted to be greater than the set threshold within the controllable range of the critical angle.

[0120] On the other hand, the present invention also provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the program, the above reservoir identification method is implemented.

[0121] On the other hand, the present invention also provides a machine-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the above-mentioned reservoir identification method is implemented.

[0122] Through the above technical solution, the present invention fits multiple cuttings grain size analysis data of the formation to be identified by using a fitting formula describing the linear relationship of the core grain size analysis data of known wells, accurately identifies the grain size of the formation to be identified, and obtains multiple fitted cuttings grain size analysis data of the target well after fitting. Then, based on the multiple fitted cuttings grain size analysis data, the grain size gamma value or the fusion gamma value based on the formation to be identified is calculated, and thus the reservoir index of the formation to be identified is calculated based on the grain size gamma value or the fusion gamma value, so as to identify the reservoir and guide the drilling trajectory of the formation to be identified. It realizes the rapid identification of the reservoir by applying the cuttings grain size analysis data at the drilling and logging site, and further realizes the adjustment of the drilling trajectory of the target well, and improves the drilling encounter rate of high-quality reservoirs.

[0123] Other features and advantages of the embodiments of the present invention will be described in detail in the subsequent specific implementation section. BRIEF DESCRIPTION OF THE DRAWINGS

[0124] The drawings are used to provide a further understanding of the embodiments of the present invention, and constitute a part of the specification, and are used to explain the embodiments of the present invention together with the following specific implementation manners, but do not constitute a limitation to the embodiments of the present invention. In the drawings:

[0125] Figure 1 is one of the flow schematic diagrams of the reservoir identification method provided by the present invention;

[0126] Figure 2 is a schematic diagram of the fitting formula describing the linear relationship of the core grain size analysis data of known wells provided by the present invention;

[0127] Figure 3 is a schematic diagram of the particle size curve obtained by analyzing with an existing laser particle size analyzer;

[0128] Figure 4 is a schematic diagram of the relationship between the grain size gamma value, the gamma value of logging while drilling, and the fusion gamma value provided by the present invention;

[0129] Figure 5 is a schematic diagram of the effect of the grain size gamma value and the reservoir index provided by the present invention;

[0130] Figure 6 is a schematic diagram of assisting in guiding in the determination coordinate system provided by the present invention;

[0131] Figure 7 is another flow schematic diagram of the reservoir identification method provided by the present invention;

[0132] Figure 8 It is a schematic structural diagram of the reservoir identification device provided by the present invention;

[0133] Figure 9 It is a schematic structural diagram of the electronic device provided by the present invention. Specific embodiments

[0134] The following will describe in detail the specific embodiments of the embodiments of the present invention with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are only used to illustrate and explain the embodiments of the present invention, and are not used to limit the embodiments of the present invention.

[0135] Method embodiments

[0136] Please refer to Figure 1 , the embodiments of the present invention provide a reservoir identification method, including:

[0137] Step 100: Obtain a plurality of cuttings grain size analysis data of the formation to be identified in the target well.

[0138] In the embodiments of the present invention, a laser particle size analyzer can be used to measure the formation to be identified in the target well to obtain a plurality of cuttings grain size analysis data, and the electronic device can obtain a plurality of cuttings grain size analysis data of the formation to be identified in the target well from the laser particle size analyzer.

[0139] Among them, a laser particle size analyzer is an instrument that analyzes the particle size through the spatial distribution (scattering spectrum) of the diffraction or scattered light of the particles. Using the Furanhofer diffraction and Mie scattering theories, the test process is not affected by many factors such as temperature change, medium viscosity, sample density, and surface state. As long as the sample to be tested is evenly presented in the laser beam, accurate test results can be obtained.

[0140] Step 200: Obtain a fitting formula describing the linear relationship of the core grain size analysis data of the known well, and based on the plurality of cuttings grain size analysis data and the fitting formula, obtain a plurality of fitted cuttings grain size analysis data of the target well after fitting.

[0141] Among them, the core grain size analysis data of the known well can be the core grain size analysis data of the adjacent well of the target well, or the historical core grain size analysis data of the target well, that is, the historical core grain size analysis data obtained by taking cores from the target well in the past. For example, the formation to be identified in the target well currently is 30 meters underground. The core grain size analysis data of the known well can be the historical core grain size analysis data obtained by taking cores at 15 meters underground in the target well. The fitting formula characterizes the linear relationship of the core grain size analysis data of the known well. In the embodiment of the present invention, the fitting formula describing the linear relationship of the core grain size analysis data of the known well is used to fit multiple cuttings grain size analysis data, so as to obtain multiple fitted cuttings grain size analysis data of the target well after fitting, and thus obtain multiple fitted cuttings grain size analysis data with accurate grain size analysis of the formation to be identified.

[0142] Among them, the fitting formula describing the linear relationship of the core grain size analysis data of the known well can be obtained by fitting multiple groups of core grain size data of the known well. For example, the fitting formula can be the following linear expression: y = 1.1216x + 2.1666.

[0143] Step 300: Calculate the grain size gamma value or the fusion gamma value based on the multiple fitted cuttings grain size analysis data for the formation to be identified.

[0144] Step 400: Calculate the reservoir index of the formation to be identified based on the grain size gamma value or the fusion gamma value.

[0145] The electronic device calculates the grain size gamma value or the fusion gamma value based on the multiple fitted cuttings grain size analysis data for the formation to be identified. In the prior art, the understanding of the reservoir structure of the target well often occurs after the drilling of the target well is completed. By directly measuring the gamma value of the formation to be identified through an instrument and calculating the reservoir index based on the gamma value to identify the reservoir of the formation to be identified, although the reservoir can be identified more accurately in this way. However, this method has a serious lag in the understanding of the reservoir structure of the target well. In the embodiment of the present invention, by calculating the grain size gamma value or the fusion gamma value based on the multiple fitted cuttings grain size analysis data in real time, it is convenient to quickly calculate the reservoir index based on the grain size gamma value or the fusion gamma value. Compared with directly measuring the gamma value of the formation to be identified through an instrument after the drilling of the target well and calculating the reservoir index based on the gamma value to identify the reservoir of the formation to be identified, the present invention can calculate the reservoir index of the formation to be identified through multiple fitted cuttings grain size analysis data during the drilling process, realizing the identification of the reservoir while drilling, and obtaining an accurate understanding of the reservoir dozens of hours, or even hundreds of hours earlier than the existing method.

[0146] Step 500: Based on the granularity gamma value and the reservoir index, construct a determination coordinate system, or based on the fusion gamma value and the reservoir index, construct a determination coordinate system, and determine the reservoir identification result of the formation to be identified during the drilling of the formation to be identified based on the similarity coefficient between adjacent coordinate points in the determination coordinate system.

[0147] In the embodiment of the present invention, a determination coordinate system can be established (where the x-axis is: granularity gamma / fusion gamma, and the y-axis is: reservoir index), and a standard profile sequence of the formation to be drilled can be established accordingly. The similarity coefficient between adjacent coordinate points in the determination coordinate system describes the difference between adjacent coordinate points. When the similarity coefficient between adjacent coordinate points in the determination coordinate system indicates a large difference between adjacent coordinate points, the formation to be drilled next is a non-reservoir formation, that is, a low-value formation without economic value or inconsistent with the drilling target. At this time, when it is still possible to adjust the trajectory in a timely manner within the controllable range of the adjustment critical angle and continue to drill in the current reservoir, the drilling trajectory can be adjusted to the previous normal point until the similarity coefficient between adjacent coordinate points is gradually adjusted to be greater than the set threshold within the controllable range of the adjustment critical angle.

[0148] In the present invention, the granularity of the formation to be identified is accurately identified by fitting the granularity analysis data of multiple cuttings of the formation to be identified through a fitting formula describing the linear relationship of the core granularity analysis data of a known well, and multiple fitting granularity analysis data of the target well after fitting are obtained. Then, based on the multiple fitting granularity analysis data, the granularity gamma value or the fusion gamma value of the formation to be identified is calculated, and thus the reservoir index of the formation to be identified is calculated based on the granularity gamma value or the fusion gamma value, so as to identify the reservoir and guide the drilling trajectory of the formation to be identified. It realizes the rapid identification of the reservoir by applying the granularity analysis data of cuttings at the drill logging site, and further realizes the adjustment of the drilling trajectory of the target well, improving the drilling encounter rate of high-quality reservoirs.

[0149] In other aspects of the embodiment of the present invention, step 200: obtaining multiple fitting granularity analysis data of the target well after fitting based on the multiple granularity analysis data of cuttings and the fitting formula includes: substituting all the granularity analysis data of cuttings into the fitting formula one by one to obtain multiple fitting granularity analysis data of the target well after fitting.

[0150] For example, please refer to Figure 2 , the fitting formula describing the linear relationship of the core granularity analysis data of a known well can be the following linear expression: y = 1.1216x + 2.1666. Figure 2The 30 scatter points in [it] are the 30 core grain size analysis data of known wells. Through the 30 core grain size analysis data of known wells, the fitting formula can be obtained by fitting: y = 1.1216x + 2.1666. In practice, please refer to Table 1, which describes the 30 cuttings grain size analysis data obtained by laser particle size analyzer, the 30 cuttings grain size analysis data obtained by thin section method, and the 30 fitted cuttings grain size analysis data after correction. It can be seen from Table 1 that the cuttings grain size analysis data obtained by laser particle size analyzer are generally smaller than those obtained by thin section method. By substituting the 30 cuttings grain size analysis data obtained by laser particle size analyzer into the independent variable in y = 1.1216x + 2.1666 one by one, the 30 dependent variables obtained are the 30 fitted cuttings grain size analysis data.

[0151] Table 1

[0152]

[0153] It should be noted that taking cores from the formation to be identified in the target well to obtain core grain size analysis data can accurately describe the grain size of the formation to be identified, but the cost of this method is relatively high. And multiple cuttings grain size analysis data of the formation to be identified in the target well can be obtained by laser particle size analyzer during the drilling process, that is, the embodiments of the present invention can obtain multiple cuttings grain size analysis data in a relatively inexpensive way. The embodiments of the present invention use the fitting formula describing the linear relationship of the core grain size analysis data of known wells to fit multiple cuttings grain size analysis data, and obtain multiple fitted cuttings grain size analysis data of the target well after fitting, so that the embodiments of the present invention can accurately identify the grain size of the formation to be identified by obtaining multiple cuttings grain size analysis data in a relatively inexpensive way.

[0154] In other aspects of the embodiments of the present invention, step 300, calculating the grain size gamma value based on the formation to be identified based on the multiple fitted cuttings grain size analysis data, includes:

[0155] Step 310, performing lithology classification and naming based on grain size on the multiple fitted cuttings grain size analysis data to obtain the percentages of different lithology types of the cuttings in the formation to be identified.

[0156] Please refer to Figure 3, the particle size curve obtained by the mainstream laser particle size analyzers on the market at present is a two-dimensional plate with the particle size value on the horizontal axis and the percentage occupancy on the vertical axis. The defects of the output style of this two-dimensional plate are as follows: First, it is difficult to observe and identify with the naked eye, which is not convenient for intuitive analysis; second, the mainstream algorithm on the market directly gives the average value as the output value, and the data representativeness is poor; third, the mainstream technology does not give the data mining and upgraded application methods for further use and analysis in the drilling and logging scenarios through particle size analysis data, and does not develop this important quantitative digital cuttings asset of particle size analysis. Therefore, based on the above situation, it is necessary to first perform lithology classification and naming based on particle size for the multiple fitted cuttings particle size analysis data to obtain the percentages of different lithology types of the cuttings in the formation to be identified.

[0157] In the embodiments of the present invention, the lithology classification and naming of the multiple fitted cuttings particle size analysis data can be realized through various existing lithology classification standards. The present invention classifies the lithology types of the multiple fitted cuttings particle size analysis data according to particle size, such as conglomerate, coarse sandstone, etc. distinguished by particle size; according to the industry standards S / Y-T-5434 and S / Y-T-5468.2, all clastic rocks can be classified according to particle size; assuming there are m classification types, then the multiple fitted cuttings particle size analysis data obtained can be divided into m categories, which are L j , j = 1, 2, 3, …, m, m ∈ Z+, and the corresponding percentage content is B i , j = 1, 2, 3, …, m, m ∈ Z+, then the final particle size analysis result output for the formation to be identified is:

[0158] L Z = ∑B i × L j

[0159] For the formation to be identified in the clastic rock well section with a length of q to be analyzed, its particle size analysis data is an array with a data capacity of q, which can be expressed as L Z k, k = 1, 2, 3, …, q.

[0160] For example, multiple fitted cuttings grain size analysis data are those with a grain size range of 0 - 2 mm. According to the definition and classification scheme of sandstone, sandstone is a clastic rock in which particles with a grain size of 2 - 0.063 mm account for more than 50%. Further, those with a grain size of 2 - 0.5 mm are coarse sandstone, those with a grain size of 0.5 - 0.25 mm are medium sandstone, and those with a grain size of 0.25 - 0.0063 mm are fine sandstone. Then, the grain size analysis results can be divided into three intervals. The L1 grain size value range is (0.5 - 2 mm), and its proportion is 25%. For L2, the medium sandstone with a grain size value range of 0.25 - 0.5 mm has a proportion of 35%. For L3, the fine sandstone with a grain size value range of 0.00063 - 0.25 mm has a proportion of 10%. The part with other finer grain sizes below 0.00063 mm is defined as matrix. Among them, the fine particles that play a filling rather than a supporting role are not included in the grain size analysis calculation conclusion.

[0161] It should be noted that different methods and classification criteria for classifying multiple fitted cuttings grain size analysis data according to grain size levels can be adjusted according to the actual situation.

[0162] Based on the grain size analysis results, combined with the rock naming method to assist in automatic cuttings naming. Wildcards are set in the computer, and by inputting the percentages of different lithology types of cuttings in the formation to be identified, the corresponding clastic rock naming results can be output. Then, the cuttings grain size analysis data can be expressed as "containing" X&Y "quality" &Z "rock"; among them, when using the traditional three - part method to determine the rock naming of clastic rocks.

[0163] Step 320: Obtain the shale percentage of the cuttings in the formation to be identified from the percentages of different lithology types of the cuttings in the formation to be identified. Based on the shale percentage of the cuttings in the formation to be identified, the gamma value corresponding to pure shale, and the gamma value corresponding to pure quartz sandstone, calculate the grain size gamma value based on the cuttings in the formation to be identified.

[0164] Further, the calculation of the grain size gamma value based on the shale percentage of the cuttings in the formation to be identified, the gamma value corresponding to pure shale, and the gamma value corresponding to pure quartz sandstone is represented by the following formula:

[0165] GR L =(GR sh -GR sa )log2(3V shl +1)+GR sa ;

[0166] Where, GR L is the grain size gamma value based on the cuttings in the formation to be identified, GR sh is the gamma value corresponding to pure shale, GR saIt is the gamma value corresponding to pure quartz sandstone. Among them, the constant GR sh = 120, GR sa = 60. After taking the constant, the grain-size gamma is calculated as follows:

[0167] GR L = (120 - 60)log2(3V shl + 1)+ 60.

[0168] V shl is the percentage of argillaceous rock in the cuttings of the formation to be identified. If the set grain size is less than 4μm, it is shale. V shl is equal to the percentage of multiple fitting cuttings grain-size analysis data with a grain size less than the critical value of 4μm in the total number of all fitting cuttings grain-size analysis data. For example, there are 10 fitting cuttings grain-size analysis data with a grain size less than 4μm, and the total number of all fitting cuttings grain-size analysis data is 50, then V shl = 10 / 50 = 20%.

[0169] The electronic device obtains the percentage of argillaceous rock in the cuttings of the formation to be identified from the percentages of different lithology types of the cuttings of the formation to be identified. For example, the percentage of argillaceous rock in the cuttings of the formation to be identified is 10%. Based on the percentage of argillaceous rock in the cuttings of the formation to be identified, the gamma value corresponding to pure shale, and the gamma value corresponding to pure quartz sandstone, based on the argillaceous calculation principle, the grain-size gamma value based on the cuttings of the formation to be identified is calculated.

[0170] Compared with directly measuring the gamma value of the formation to be identified by an instrument after the drilling of the target well and calculating the reservoir index based on the gamma value to identify the reservoir of the formation to be identified, the present invention can calculate the grain-size gamma value of the cuttings of the formation to be identified through multiple fitting cuttings grain-size analysis data during the drilling process, thereby calculating the reservoir index, realizing reservoir identification while drilling, and obtaining an accurate reservoir understanding dozens of hours, or even hundreds of hours earlier than the existing method.

[0171] In other aspects of the embodiments of the present invention, step 300, calculating the fusion gamma value based on the formation to be identified based on the multiple fitting cuttings grain-size analysis data, includes:

[0172] Step 330, performing grain-size-based lithology classification and naming based on the multiple fitting cuttings grain-size analysis data to obtain the percentages of different lithology types of the cuttings of the formation to be identified.

[0173] Step 340, obtaining the percentage of argillaceous rock in the cuttings of the formation to be identified from the percentages of different lithology types of the cuttings of the formation to be identified, and calculating the grain-size gamma value based on the cuttings of the formation to be identified based on the percentage of argillaceous rock in the cuttings of the formation to be identified, the gamma value corresponding to pure shale, and the gamma value corresponding to pure quartz sandstone.

[0174] For the specific steps of step 330 and step 340, reference may be made to the above-mentioned step 310 and step 320, which will not be elaborated here.

[0175] Step 350: Calculate the fusion gamma value of the cuttings based on the formation to be identified, based on the grain-size gamma value, the logging-while-drilling gamma value, and the weight coefficient of the logging-while-drilling gamma value.

[0176] In the embodiment of the present invention, while obtaining the cutting grain-size analysis data of the formation to be identified and solving the grain-size gamma value GR L the logging-while-drilling gamma value GR c is obtained. At this time, the logging gamma detection depth is set to L, which is a constant, and the current drilling hole diameter is d. Calculate the weight coefficient of the logging-while-drilling gamma value based on the set logging gamma detection depth L and the drilling hole diameter d, and then calculate the fusion gamma value of the cuttings based on the formation to be identified, based on the grain-size gamma value, the logging-while-drilling gamma value, and the weight coefficient of the logging-while-drilling gamma value.

[0177] Further, please refer to Figure 4 The calculation of the fusion gamma value of the cuttings based on the formation to be identified, based on the grain-size gamma value, the logging-while-drilling gamma value, and the weight coefficient of the logging-while-drilling gamma value, is represented by the following formula:

[0178] GR R = Q c × GR c +(1 - Q c )× GR L ;

[0179] where GR R is the fusion gamma value of the cuttings based on the formation to be identified, GR c is the logging-while-drilling gamma value, Q c is the weight coefficient of the logging-while-drilling gamma value, and GR L is the grain-size gamma value;

[0180] The weight coefficient Qc of the logging-while-drilling gamma value is represented by the following formula:

[0181] Q c =(πL 2 + 2πd) / (π(L + d) 2 );

[0182] where L is the set logging gamma detection depth and d is the drilling hole diameter.

[0183] Compared with directly measuring the gamma value of the formation to be identified by an instrument after the drilling of the target well and calculating the reservoir index based on the gamma value to identify the reservoir of the formation to be identified, the present invention can calculate the fusion gamma value of the cuttings of the formation to be identified through multiple fitting cuttings particle size analysis data during the drilling process, so as to calculate the reservoir index, realize reservoir identification while drilling, and obtain an accurate reservoir understanding dozens of hours, or even hundreds of hours earlier than the existing method.

[0184] In other aspects of the embodiments of the present invention, please refer to Figure 5 , step 400, calculating the reservoir index of the formation to be identified based on the particle size gamma value, including:

[0185] Step 410a, calculate an intermediate operation coefficient based on the standard deviation of the common logarithm of the historical gas logging data of the formation to be identified and the drilled formation of the target well, the average value of the common logarithm of the historical gas logging data of the drilled formation, the standard deviation of the historical drilling time of the formation to be identified and the drilled formation, and the average value of the historical drilling time of the drilled formation.

[0186] Wherein, the common logarithm of the gas logging data of the formation to be identified refers to the common logarithm of the gas logging data of the current formation to be identified. For example, if the current formation to be identified is 30 meters underground, the common logarithm of the gas logging data is the one measured at 30 meters underground. The common logarithm of the historical gas logging data of the drilled formation includes multiple gas logging data measured in the formations drilled before the target well. For example, the first common logarithm of the gas logging data measured at 10 meters underground, the second common logarithm of the gas logging data measured at 15 meters underground, the third common logarithm of the gas logging data measured at 20 meters underground, and the fourth common logarithm of the gas logging data measured at 25 meters underground. Then, the average value of the common logarithm of the historical gas logging data of the drilled formation is the average value calculated based on the first, second, third, and fourth common logarithms of the gas logging data, and the standard deviation of the common logarithm of the historical gas logging data of the drilled formation is calculated based on the common logarithm of the gas logging data of the formation to be identified and the average value of the common logarithm of the historical gas logging data of the drilled formation.

[0187] The drilling time of the formation to be identified refers to the drilling time of the current formation to be identified. For example, if the current formation to be identified is 30 meters underground, the drilling time of the formation to be identified is the one measured at 30 meters underground. The historical drilling time of the drilled formation includes multiple drilling times measured in the formations drilled before the target well. For example, the first drilling time measured at 10 meters underground, the second drilling time measured at 15 meters underground, the third drilling time measured at 20 meters underground, and the fourth drilling time measured at 25 meters underground. Then, the average value of the historical drilling time of the drilled formation is the average value calculated based on the first, second, third, and fourth drilling times, and the first drilling time is calculated based on the drilling time of the formation to be identified and the average value of the historical drilling time of the drilled formation.

[0188] Specifically, in one embodiment, the intermediate operation coefficient is calculated based on the common logarithm of the gas logging data of the formation to be identified in the target well, the standard deviation of the common logarithm of the historical gas logging data of the drilled formation, the average value of the common logarithm of the historical gas logging data of the drilled formation, the drilling time of the formation to be identified, the standard deviation of the historical drilling time of the drilled formation, and the average value of the historical drilling time of the drilled formation, and is expressed by the following formula:

[0189] Z = (V - aver(V)) / V' - (ROP - aver(ROP)) / ROP';

[0190] Wherein, Z is the intermediate operation coefficient, V is the common logarithm of the gas logging data of the formation to be identified, V' is the standard deviation of the common logarithm of the historical gas logging data of the drilled formation, aver(V) is the average value of the common logarithm of the historical gas logging data of the drilled formation, ROP is the drilling time of the formation to be identified, ROP' is the standard deviation of the historical drilling time of the drilled formation, and aver(ROP) is the average value of the historical drilling time of the drilled formation.

[0191] Step 420a: Calculate the compensation coefficient based on the gamma value corresponding to pure shale, the gamma value corresponding to pure quartz sandstone, the intermediate operation coefficient, and the absolute value of the intermediate operation coefficient.

[0192] Wherein, the gamma value corresponding to pure shale and the gamma value corresponding to pure quartz sandstone are both known quantities. In one embodiment, the compensation coefficient is calculated based on the gamma value corresponding to pure shale, the gamma value corresponding to pure quartz sandstone, the intermediate operation coefficient, and the absolute value of the intermediate operation coefficient, and is expressed by the following formula:

[0193] Φ R = (GR sh - GR sa ) × (Z + ABS(Z)) / 2;

[0194] Wherein, Φ R is the compensation coefficient, GR sh is the gamma value corresponding to pure shale, GR sa is the gamma value corresponding to pure quartz sandstone, Z is the intermediate operation coefficient, and ABS(Z) is the absolute value of the intermediate operation coefficient.

[0195] Step 430a: Calculate the first corrected grain size gamma value based on and the compensation coefficient.

[0196] Specifically, in one embodiment, the first corrected grain size gamma value is calculated based on the grain size gamma value and the compensation coefficient, and is expressed by the following formula:

[0197] GR Φ = GR L - Φ R; where GR Φ is the first corrected grain size gamma value, and GR L is the grain size gamma value.

[0198] Step 440a: Calculate the reservoir index of the formation to be identified based on the first corrected grain size gamma value.

[0199] Specifically, in one embodiment, calculating the reservoir index of the formation to be identified based on the first corrected grain size gamma value is represented by the following formula:

[0200] Φ L =(GR Φ -MIN(GR Φ )) / 10*(MAX(GR Φ )-MIN(GR Φ ));

[0201] where Φ L is the reservoir index of the reservoir to be identified, GR Φ is the first corrected grain size gamma value, MIN(GR Φ ) is the minimum value of the historical reservoir indices of the drilled formations, and MAX(GR Φ ) is the maximum value of the historical reservoir indices of the drilled formations.

[0202] The reservoir index of the reservoir to be identified refers to the reservoir index of the current formation to be identified. For example, if the current formation to be identified is 30 meters underground, the reservoir index of the formation to be identified is measured at 30 meters underground. The historical reservoir indices of the drilled formations include multiple reservoir indices measured from the formations drilled before the target well. For example, the first reservoir index measured at 10 meters underground, the second reservoir index measured at 15 meters underground, the third reservoir index measured at 20 meters underground, and the fourth reservoir index measured at 25 meters underground. Then, the minimum value of the historical reservoir indices of the drilled formations is based on the minimum value among the first, second, third, and fourth reservoir indices, and the maximum value of the historical reservoir indices of the drilled formations is based on the maximum value among the first, second, third, and fourth reservoir indices.

[0203] Therefore, in the embodiments of the present invention, the reservoir index of the formation to be identified is calculated by fusing the common logarithm of the gas logging data, the drilling time, and the grain size gamma value of the formation to be identified, improving the accuracy of calculating the reservoir index, and realizing the identification of the reservoir while drilling, obtaining an accurate understanding of the reservoir dozens of hours, or even hundreds of hours earlier than the existing methods.

[0204] In other aspects of the embodiments of the present invention, step 400: Calculate the reservoir index of the formation to be identified based on the fused gamma value, including:

[0205] Step 410b: Calculate an intermediate operation coefficient based on the common logarithm of the gas logging data of the formation to be identified in the target well, the standard deviation of the common logarithms of the historical gas logging data of the drilled formations, the average value of the common logarithms of the historical gas logging data of the drilled formations, the drilling time of the formation to be identified, the standard deviation of the historical drilling times of the drilled formations, and the average value of the historical drilling times of the drilled formations.

[0206] Among them, the definitions of the common logarithm of the gas logging data of the formation to be identified, the standard deviation of the common logarithms of the historical gas logging data of the drilled formations, the average value of the common logarithms of the historical gas logging data of the drilled formations, the drilling time of the formation to be identified, the standard deviation of the historical drilling times of the drilled formations, and the average value of the historical drilling times of the drilled formations can be referred to the relevant content in Step 410a and will not be elaborated here.

[0207] In one embodiment, the calculating of the intermediate operation coefficient based on the common logarithm of the gas logging data of the formation to be identified in the target well, the standard deviation of the common logarithms of the historical gas logging data of the drilled formations, the average value of the common logarithms of the historical gas logging data of the drilled formations, the drilling time of the formation to be identified, the standard deviation of the historical drilling times of the drilled formations, and the average value of the historical drilling times of the drilled formations is represented by the following formula:

[0208] Z = (V - aver(V)) / V' - (ROP - aver(ROP)) / ROP';

[0209] Wherein, Z is the intermediate operation coefficient, V is the common logarithm of the gas logging data of the formation to be identified, V' is the standard deviation of the common logarithms of the historical gas logging data of the drilled formations, aver(V) is the average value of the common logarithms of the historical gas logging data of the drilled formations, ROP is the drilling time of the formation to be identified, ROP' is the standard deviation of the historical drilling times of the drilled formations, and aver(ROP) is the average value of the historical drilling times of the drilled formations;

[0210] Step 420b: Calculate a compensation coefficient based on the gamma value corresponding to pure shale, the gamma value corresponding to pure quartz sandstone, the intermediate operation coefficient, and the absolute value of the intermediate operation coefficient.

[0211] Among them, the gamma value corresponding to pure shale and the gamma value corresponding to pure quartz sandstone are both known quantities. In one embodiment, the calculating of the compensation coefficient based on the gamma value corresponding to pure shale, the gamma value corresponding to pure quartz sandstone, the intermediate operation coefficient, and the absolute value of the intermediate operation coefficient is represented by the following formula:

[0212] Φ R = (GR sh - GR sa ) × (Z + ABS(Z)) / 2;

[0213] Wherein, Φ R is the compensation coefficient, GRsh is the gamma value corresponding to pure mudstone, GR sa is the gamma value corresponding to pure quartz sandstone, Z is the intermediate operation coefficient, and ABS(Z) is the absolute value of the intermediate operation coefficient.

[0214] Step 430b: Calculate the second corrected grain size gamma value based on the fused gamma value and the compensation coefficient;

[0215] Specifically, calculating the second corrected grain size gamma value based on the fused gamma value and the compensation coefficient is represented by the following formula:

[0216] GR Φ = GR R - Φ R ; where GR Φ is the second corrected grain size gamma value, and GR R is the fused gamma value.

[0217] Step 440b: Calculate the reservoir index of the formation to be identified based on the second corrected grain size gamma value.

[0218] Specifically, calculating the reservoir index of the formation to be identified based on the second corrected grain size gamma value is represented by the following formula:

[0219] Φ L = (GR Φ - MIN(GR Φ )) / 10 * (MAX(GR Φ ) - MIN(GR Φ ));

[0220] where Φ L is the reservoir index of the reservoir to be identified, GR Φ is the second corrected grain size gamma value, MIN(GR Φ ) is the minimum value of the historical reservoir indices of the drilled formations, and MAX(GR Φ ) is the maximum value of the historical reservoir indices of the drilled formations.

[0221] Among them, for the reservoir index of the reservoir to be identified, GR Φ is the second corrected grain size gamma value, MIN(GR Φ ) is the minimum value of the historical reservoir indices of the drilled formations, and MAX(GR Φ ) is the maximum value of the historical reservoir indices of the drilled formations. For the definitions, please refer to Step 440a and will not be elaborated here.

[0222] In other aspects of the embodiments of the present invention, Step 500: When drilling the reservoir to be identified, determine the reservoir identification result of the reservoir to be identified based on the similarity coefficient between adjacent coordinate points in the determination coordinate system, including:

[0223] When the similarity coefficient between adjacent coordinate points in the determination coordinate system is less than or equal to the set threshold during the drilling of the reservoir to be identified, it is determined that continuing drilling will reach a non-reservoir. In the case where the trajectory can still be adjusted in time within the controllable range of the critical angle to continue drilling in the current reservoir, the drilling trajectory is adjusted to the previous normal point until the similarity coefficient between adjacent coordinate points is gradually adjusted to be greater than the set threshold within the controllable range of the critical angle.

[0224] The electronic device establishes a determination coordinate system P for the formation to be drilled according to the grain-size gamma or the fused gamma. The abscissa is the grain-size gamma value or the fused gamma value, and the ordinate is the grain-size reservoir index. Based on this coordinate system, the adjacent well data is used to establish a sub-division segment based on this determination coordinate system.

[0225] Set the safe angle (critical angle) that the drilling trajectory cannot exceed as β. By analyzing the first point coordinates P1(G1, R1) through the set front and back points, G1 is the gamma energy spectrum value, and R1 is the grain-size reservoir index of this point; the second point coordinates are P2(G2, R2).

[0226] Then the similarity coefficient RE1 2 =(G1×G2 + R1×R2) / ((G1 2 +R1 2 )^(1 / 2)+(G2 2 +R2 2 )^(1 / 2))

[0227] where RE n m , represents the difference between the nth point and the mth point. Generally, the latter point m is selected as the next sampling point of the previous point n to ensure the calculation accuracy. RE n m ∈(0, 1), the closer to 1, the more similar. Set to drill at a certain rate of penetration ROP. When the similarity coefficient RE n m between the coordinates of the current point and the adjacent coordinate points in the determination coordinate system continuously decreases and approaches the value of 0 (it is determined that continuing drilling will reach a non-reservoir, that is, a low-value layer without economic value or not in line with the drilling target), that is, it becomes less and less similar to the target layer. In the case where the trajectory can still be predicted to be adjusted in time within the controllable range of the critical angle to continue drilling in the current reservoir, it is adjusted back to the previous normal point in time, and so on, until the similarity coefficient between adjacent coordinate points is gradually adjusted back to normal (that is, greater than 0 and less than 1) within the controllable range of the critical angle; the determination method of the critical angle β depends on the wellbore structure requirements. For example, for the safety of later construction, β is usually required to be less than 3°.

[0228] Please refer to Figure 6, the white line is the drilling trajectory. When drilling in the formation at a certain drilling time, if the similarity coefficient between the coordinate coefficients of the current point in the coordinate system and the target standard layer, such as layer 4 in this figure, is lower than the critical value (e.g., 0), that is, when it is still predictable to adjust the trajectory in time and continue to drill in layer 4 within the controllable range of the adjustment critical angle β, adjust back to the previous normal point in time, and so on, until gradually adjusting back to normal within the controllable range of the adjustment critical angle.

[0229] The following illustrates the step process of the present invention through an embodiment.

[0230] Please refer to Figure 7 , in a certain well, laser particle size analysis and identification were carried out while drilling. According to the analysis of adjacent well data, it was known that the particle size distribution of the sandstone in this layer was between 11 and 406 um, and the lithology of the horizontal section to be drilled was mainly fine to medium sandstone.

[0231] When drilling to a well depth of 2874.00 m, the gas logging decreased significantly, and the sandstone particle size decreased from 237 um to 65 um. Continuing to drill to 2884.00 m, the sandstone particle size continued to be between 27 and 52 um, and it was likely to reach the top. It was recommended to probe down. The steering adopted a reduction of the inclination angle from 89.0° to 85.8°. After geological particle size analysis and judgment, the particle size rose again at a well depth of 2912.00 m, and the box was turned back in time, ensuring that the drilling trajectory remained in the high-quality reservoir. Finally, the reservoir encounter rate was greater than 90%, achieving the geological and engineering goals.

[0232] In the embodiment of the present invention, by applying the cuttings particle size analysis data at the drilling and logging site, the reservoir is quickly identified, and then the drilling trajectory of the target well is adjusted, improving the reservoir encounter rate and benefits of the high-quality reservoir.

[0233] Device embodiment

[0234] Please refer to Figure 8 , on the other hand, the embodiment of the present invention also provides a reservoir identification device, including:

[0235] A data acquisition module 801, configured to acquire a plurality of cuttings particle size analysis data of the formation to be identified of the target well;

[0236] A fitting module 802, configured to obtain a fitting formula describing the linear relationship of the core particle size analysis data of the known well, and based on the plurality of cuttings particle size analysis data and the fitting formula, obtain a plurality of fitted cuttings particle size analysis data of the target well after fitting;

[0237] A first calculation module 803, configured to calculate the grain size gamma value or the fusion gamma value based on the plurality of fitted cuttings particle size analysis data for the formation to be identified;

[0238] A second calculation module 804, configured to calculate a reservoir index of a formation to be identified based on the granularity gamma value or the fusion gamma value;

[0239] A reservoir identification module 805, configured to construct a determination coordinate system based on the granularity gamma value and the reservoir index, or construct a determination coordinate system based on the fusion gamma value and the reservoir index, and determine a reservoir identification result of the formation to be identified based on a similarity coefficient between adjacent coordinate points in the determination coordinate system when drilling the formation to be identified.

[0240] Optionally, the obtaining of the multiple fitting cuttings grain size analysis data of the target well after fitting based on the multiple cuttings grain size analysis data and the fitting formula includes:

[0241] Substituting all the cuttings grain size analysis data into the fitting formula one by one to obtain the multiple fitting cuttings grain size analysis data of the target well after fitting.

[0242] Optionally, the calculating of the granularity gamma value based on the multiple fitting cuttings grain size analysis data and for the formation to be identified includes:

[0243] Performing lithology classification and naming based on grain size for the multiple fitting cuttings grain size analysis data to obtain percentages of different lithology types of the cuttings of the formation to be identified;

[0244] Obtaining the percentage of argillaceous rock of the cuttings of the formation to be identified from the percentages of different lithology types of the cuttings of the formation to be identified, and calculating the granularity gamma value of the cuttings of the formation to be identified based on the percentage of argillaceous rock of the cuttings of the formation to be identified, the gamma value corresponding to pure argillaceous rock, and the gamma value corresponding to pure quartz sandstone.

[0245] Optionally, the calculating of the fusion gamma value based on the multiple fitting cuttings grain size analysis data and for the formation to be identified includes:

[0246] Performing lithology classification and naming based on grain size for the multiple fitting cuttings grain size analysis data to obtain percentages of different lithology types of the cuttings of the formation to be identified;

[0247] Obtaining the percentage of argillaceous rock of the cuttings of the formation to be identified from the percentages of different lithology types of the cuttings of the formation to be identified, and calculating the granularity gamma value of the cuttings of the formation to be identified based on the percentage of argillaceous rock of the cuttings of the formation to be identified, the gamma value corresponding to pure argillaceous rock, and the gamma value corresponding to pure quartz sandstone;

[0248] Calculating the fusion gamma value of the cuttings of the formation to be identified based on the granularity gamma value, the gamma value of logging while drilling, and the weight coefficient of the gamma value of logging while drilling.

[0249] Optionally, the grain size gamma value based on the cuttings of the formation to be identified is calculated from the shale percentage of the cuttings of the formation to be identified, the gamma value corresponding to pure shale, and the gamma value corresponding to pure quartz sandstone, and is expressed by the following formula:

[0250] GR L =(GR sh -GR sa )log2(3V shl +1)+GR sa ;

[0251] where GR L is the grain size gamma value based on the cuttings of the formation to be identified, GR sh is the gamma value corresponding to pure shale, GR sa is the gamma value corresponding to pure quartz sandstone, and V shl is the shale percentage of the cuttings of the formation to be identified.

[0252] Optionally, the fused gamma value based on the cuttings of the formation to be identified is calculated from the grain size gamma value, the gamma value while drilling, and the weight coefficient of the gamma value while drilling, and is expressed by the following formula:

[0253] GR R =Q c ×GR c +(1 - Q c )×GR L ;

[0254] where GR R is the fused gamma value based on the cuttings of the formation to be identified, GR c is the gamma value while drilling, Q c is the weight coefficient of the gamma value while drilling, and GR L is the grain size gamma value;

[0255] The weight coefficient Q c of the gamma value while drilling is expressed by the following formula:

[0256] Q c =(πL 2 +2πd) / (π(L + d) 2 );

[0257] where L is the set logging gamma detection depth and d is the drilled hole diameter.

[0258] Optionally, calculating the reservoir index of the formation to be identified based on the grain size gamma value includes:

[0259] Calculate an intermediate operation coefficient based on the common logarithm of the gas logging data of the formation to be identified in the target well, the standard deviation of the common logarithms of the historical gas logging data of the drilled formations, the average value of the common logarithms of the historical gas logging data of the drilled formations, the drilling time of the formation to be identified, the standard deviation of the historical drilling times of the drilled formations, and the average value of the historical drilling times of the drilled formations;

[0260] Calculate a compensation coefficient based on the gamma value corresponding to pure shale, the gamma value corresponding to pure quartz sandstone, the intermediate operation coefficient, and the absolute value of the intermediate operation coefficient;

[0261] Calculate a first corrected grain-size gamma value based on the grain-size gamma value and the compensation coefficient;

[0262] Calculate the reservoir index of the formation to be identified based on the first corrected grain-size gamma value.

[0263] Optionally, the calculation of the intermediate operation coefficient based on the common logarithm of the gas logging data of the formation to be identified in the target well, the standard deviation of the common logarithms of the historical gas logging data of the drilled formations, the average value of the common logarithms of the historical gas logging data of the drilled formations, the drilling time of the formation to be identified, the standard deviation of the historical drilling times of the drilled formations, and the average value of the historical drilling times of the drilled formations is represented by the following formula:

[0264] Z = (V - aver(V)) / V' - (ROP - aver(ROP)) / ROP';

[0265] Where Z is the intermediate operation coefficient, V is the common logarithm of the gas logging data of the formation to be identified, V' is the standard deviation of the common logarithms of the historical gas logging data of the drilled formations, aver(V) is the average value of the common logarithms of the historical gas logging data of the drilled formations, ROP is the drilling time of the formation to be identified, ROP' is the standard deviation of the historical drilling times of the drilled formations, and aver(ROP) is the average value of the historical drilling times of the drilled formations;

[0266] The calculation of the compensation coefficient based on the gamma value corresponding to pure shale, the gamma value corresponding to pure quartz sandstone, the intermediate operation coefficient, and the absolute value of the intermediate operation coefficient is represented by the following formula:

[0267] Φ R = (GR sh - GR sa ) × (Z + ABS(Z)) / 2;

[0268] Where Φ R is the compensation coefficient, GR sh is the gamma value corresponding to pure shale, GR sa is the gamma value corresponding to pure quartz sandstone, Z is the intermediate operation coefficient, and ABS(Z) is the absolute value of the intermediate operation coefficient;

[0269] The first corrected grain size gamma value is calculated based on the grain size gamma value and the compensation coefficient, and is expressed by the following formula:

[0270] GR Φ = GR L - Φ R ; where GR Φ is the first corrected grain size gamma value, and GR L is the grain size gamma value;

[0271] The reservoir index of the formation to be identified is calculated based on the first corrected grain size gamma value, and is expressed by the following formula:

[0272] Φ L = (GR Φ - MIN(GR Φ )) / 10 * (MAX(GR Φ ) - MIN(GR Φ ));

[0273] where Φ L is the reservoir index of the reservoir to be identified, GR Φ is the first corrected grain size gamma value, MIN(GR Φ ) is the minimum value of the historical reservoir index of the drilled formation, and MAX(GR Φ ) is the maximum value of the historical reservoir index of the drilled formation.

[0274] Optionally, calculating the reservoir index of the formation to be identified based on the fused gamma value includes:

[0275] Calculating an intermediate operation coefficient based on the common logarithm of the gas logging data of the formation to be identified in the target well, the standard deviation of the common logarithm of the historical gas logging data of the drilled formation, the average value of the common logarithm of the historical gas logging data of the drilled formation, the drilling time of the formation to be identified, the standard deviation of the historical drilling time of the drilled formation, and the average value of the historical drilling time of the drilled formation;

[0276] Calculating a compensation coefficient based on the gamma value corresponding to pure shale, the gamma value corresponding to pure quartz sandstone, the intermediate operation coefficient, and the absolute value of the intermediate operation coefficient;

[0277] Calculating a second corrected grain size gamma value based on the fused gamma value and the compensation coefficient;

[0278] Calculating the reservoir index of the formation to be identified based on the second corrected grain size gamma value.

[0279] Optionally, calculate an intermediate operation coefficient based on the common logarithm of the gas logging data of the formation to be identified in the target well, the standard deviation of the common logarithm of the historical gas logging data of the drilled formation, the average value of the common logarithm of the historical gas logging data of the drilled formation, the drilling time of the formation to be identified, the standard deviation of the historical drilling time of the drilled formation, and the average value of the historical drilling time of the drilled formation, which is expressed by the following formula:

[0280] Z = (V - aver(V)) / V' - (ROP - aver(ROP)) / ROP';

[0281] Wherein, Z is the intermediate operation coefficient, V is the common logarithm of the gas logging data of the formation to be identified, V' is the standard deviation of the common logarithm of the historical gas logging data of the drilled formation, aver(V) is the average value of the common logarithm of the historical gas logging data of the drilled formation, ROP is the drilling time of the formation to be identified, ROP' is the standard deviation of the historical drilling time of the drilled formation, and aver(ROP) is the average value of the historical drilling time of the drilled formation;

[0282] Calculate a compensation coefficient based on the gamma value corresponding to pure shale, the gamma value corresponding to pure quartz sandstone, the intermediate operation coefficient, and the absolute value of the intermediate operation coefficient, which is expressed by the following formula:

[0283] Φ R = (GR sh - GR sa ) × (Z + ABS(Z)) / 2;

[0284] Wherein, Φ R is the compensation coefficient, GR sh is the gamma value corresponding to pure shale, GR sa is the gamma value corresponding to pure quartz sandstone, Z is the intermediate operation coefficient, and ABS(Z) is the absolute value of the intermediate operation coefficient;

[0285] Calculate the second corrected grain size gamma value based on the fused gamma value and the compensation coefficient, which is expressed by the following formula:

[0286] GR Φ = GR R - Φ R ; wherein, GR Φ is the second corrected grain size gamma value, and GR R is the fused gamma value;

[0287] Calculate the reservoir index of the formation to be identified based on the second corrected grain size gamma value, which is expressed by the following formula:

[0288] Φ L = (GR Φ - MIN(GR Φ )) / 10 * (MAX(GRΦ ) - MIN(GR Φ ));

[0289] Where Φ L is the reservoir index of the reservoir to be identified, GR Φ is the second corrected grain size gamma value, MIN(GR Φ ) is the minimum value of the historical reservoir index of the drilled formation, and MAX(GR Φ ) is the maximum value of the historical reservoir index of the drilled formation.

[0290] Optionally, when drilling the reservoir to be identified, determining the reservoir identification result of the reservoir to be identified based on the similarity coefficient between adjacent coordinate points in the determination coordinate system includes:

[0291] When the similarity coefficient between adjacent coordinate points in the determination coordinate system is less than or equal to the set threshold during the drilling of the reservoir to be identified, it is determined that continuing to drill will reach a non-reservoir. In the case where the trajectory can still be adjusted in time within the controllable range of the adjustment critical angle and continue to drill in the current reservoir, the drilling trajectory is adjusted to the previous normal point until the similarity coefficient between adjacent coordinate points is gradually adjusted to be greater than the set threshold within the controllable range of the adjustment critical angle.

[0292] The reservoir identification device includes a processor and a memory. The above data acquisition module, fitting module, first calculation module, second calculation module, and reservoir identification module are all stored in the memory as program units, and the processor executes the above program units stored in the memory to implement corresponding functions.

[0293] The processor contains a kernel, and the corresponding program unit is retrieved from the memory by the kernel. One or more kernels can be set.

[0294] The memory includes non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of, for example, read-only memory (ROM) or flash memory (flash RAM). The memory includes at least one storage chip.

[0295] Figure 9 Illustrates a schematic diagram of the physical structure of an electronic device, such as Figure 9As shown in the figure, the electronic device may include: a processor 910, a communications interface 920, a memory 930, and a communication bus 940. Among them, the processor 910, the communications interface 920, and the memory 930 complete communication with each other through the communication bus 940. The processor 910 may call logic instructions in the memory 930 to execute a reservoir identification method, which includes: obtaining a plurality of cuttings grain size analysis data of the formation to be identified in a target well; obtaining a fitting formula describing the linear relationship of the core grain size analysis data of a known well, and based on the plurality of cuttings grain size analysis data and the fitting formula, obtaining a plurality of fitted cuttings grain size analysis data of the target well after fitting; based on the plurality of fitted cuttings grain size analysis data, calculating a grain size gamma value or a fusion gamma value based on the formation to be identified; calculating a reservoir index of the formation to be identified based on the grain size gamma value or the fusion gamma value; constructing a determination coordinate system based on the grain size gamma value and the reservoir index, or constructing a determination coordinate system based on the fusion gamma value and the reservoir index, and determining a reservoir identification result of the formation to be identified based on the similarity coefficient between adjacent coordinate points in the determination coordinate system when drilling the formation to be identified.

[0296] In addition, when the logic instructions in the above-mentioned memory 930 are implemented in the form of software functional units and sold or used as independent products, they may be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of this technical solution, may be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The foregoing storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical discs that can store program codes.

[0297] In another aspect, the present invention further provides a machine-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it is used to execute a reservoir identification method, and the method includes: obtaining a plurality of cuttings grain size analysis data of the formation to be identified in a target well; obtaining a fitting formula describing the linear relationship of the core grain size analysis data of a known well, and based on the plurality of cuttings grain size analysis data and the fitting formula, obtaining a plurality of fitted cuttings grain size analysis data of the target well after fitting; based on the plurality of fitted cuttings grain size analysis data, calculating a grain size gamma value or a fusion gamma value based on the formation to be identified; calculating a reservoir index of the formation to be identified based on the grain size gamma value or the fusion gamma value; constructing a determination coordinate system based on the grain size gamma value and the reservoir index, or constructing a determination coordinate system based on the fusion gamma value and the reservoir index, and determining the reservoir identification result of the formation to be identified based on the similarity coefficient between adjacent coordinate points in the determination coordinate system when drilling the formation to be identified.

[0298] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art can understand and implement it without creative labor.

[0299] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on this understanding, the essence of the above technical solution, or the part that contributes to the prior art, can be embodied in the form of a software product. The computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0300] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A reservoir identification method, characterized in that, Including: Obtaining a plurality of cuttings grain size analysis data of the formation to be identified in the target well; Obtaining a fitting formula describing the linear relationship of the core grain size analysis data of the known well, and based on the plurality of cuttings grain size analysis data and the fitting formula, obtaining a plurality of fitted cuttings grain size analysis data of the target well after fitting; Based on the plurality of fitted cuttings grain size analysis data, calculating a grain size gamma value or a fusion gamma value based on the formation to be identified; Calculating a reservoir index of the formation to be identified based on the grain size gamma value or the fusion gamma value; Constructing a determination coordinate system based on the grain size gamma value and the reservoir index, or constructing a determination coordinate system based on the fusion gamma value and the reservoir index, and determining the reservoir identification result of the formation to be identified based on the similarity coefficient between adjacent coordinate points in the determination coordinate system when drilling the formation to be identified.

2. The reservoir identification method according to claim 1, characterized in that The obtaining a plurality of fitted cuttings grain size analysis data of the target well after fitting based on the plurality of cuttings grain size analysis data and the fitting formula includes: Substituting all the cuttings grain size analysis data into the fitting formula one by one to obtain a plurality of fitted cuttings grain size analysis data of the target well after fitting.

3. The reservoir identification method according to claim 1, characterized in that The calculating a grain size gamma value based on the formation to be identified based on the plurality of fitted cuttings grain size analysis data includes: Performing lithology classification and naming based on grain size on the basis of the plurality of fitted cuttings grain size analysis data to obtain the percentages of different lithology types of the cuttings in the formation to be identified; Obtaining the shale percentage of the cuttings in the formation to be identified from the percentages of different lithology types of the cuttings in the formation to be identified, and calculating the grain size gamma value of the cuttings based on the formation to be identified based on the shale percentage of the cuttings in the formation to be identified, the gamma value corresponding to pure shale, and the gamma value corresponding to pure quartz sandstone.

4. The reservoir identification method according to claim 1, characterized in that The calculating a fusion gamma value based on the formation to be identified based on the plurality of fitted cuttings grain size analysis data includes: Performing lithology classification and naming based on grain size on the basis of the plurality of fitted cuttings grain size analysis data to obtain the percentages of different lithology types of the cuttings in the formation to be identified; Obtaining the shale percentage of the cuttings in the formation to be identified from the percentages of different lithology types of the cuttings in the formation to be identified, and calculating the grain size gamma value of the cuttings based on the formation to be identified based on the shale percentage of the cuttings in the formation to be identified, the gamma value corresponding to pure shale, and the gamma value corresponding to pure quartz sandstone; Calculating the fusion gamma value of the cuttings based on the formation to be identified based on the grain size gamma value, the gamma value while drilling, and the weight coefficient of the gamma value while drilling.

5. The reservoir identification method according to claim 3 or 4, characterized in that, The calculating the grain size gamma value of the cuttings based on the formation to be identified based on the shale percentage of the cuttings in the formation to be identified, the gamma value corresponding to pure shale, and the gamma value corresponding to pure quartz sandstone is represented by the following formula: GR L = (GR sh - GR sa ) log2(3V shl + 1) + GR sa ; Among them, GR L is the grain-size gamma value of the cuttings of the formation to be identified, GR sh is the corresponding gamma value of pure mudstone, GR sa is the corresponding gamma value of pure quartz sandstone, V shl is the percentage of mudstone in the cuttings of the formation to be identified.

6. The reservoir identification method according to claim 4, characterized in that The calculating the fusion gamma value of the cuttings based on the formation to be identified based on the grain size gamma value, the gamma value while drilling, and the weight coefficient of the gamma value while drilling is represented by the following formula: GR R = Q c × GR c +(1 - Q c )× GR L ; Among them, GR R is the fused gamma value of the cuttings of the formation to be identified, GR c is the gamma value of the logging-while-drilling, Q c is the weight coefficient of the gamma value of the logging-while-drilling, GR L is the grain-size gamma value; Weight coefficient Q of the gamma value in logging while drilling c It is expressed by the following formula: Q c = (πL 2 + 2πd) / (π(L + d) 2 ) Wherein, L is the set logging gamma detection depth, and d is the drilled hole diameter.

7. The reservoir identification method according to claim 1, wherein, The calculating a reservoir index of the formation to be identified based on the grain size gamma value includes: Calculate an intermediate operation coefficient based on the common logarithm of the gas logging data of the formation to be identified in the target well, the standard deviation of the common logarithms of the historical gas logging data of the drilled formations, the average value of the common logarithms of the historical gas logging data of the drilled formations, the drilling time of the formation to be identified, the standard deviation of the historical drilling times of the drilled formations, and the average value of the historical drilling times of the drilled formations; Calculate a compensation coefficient based on the gamma value corresponding to pure shale, the gamma value corresponding to pure quartz sandstone, the intermediate operation coefficient, and the absolute value of the intermediate operation coefficient; Calculate a first corrected grain-size gamma value based on the grain-size gamma value and the compensation coefficient; Calculate the reservoir index of the formation to be identified based on the first corrected grain-size gamma value.

8. The reservoir identification method according to claim 7, wherein, The calculation of the intermediate operation coefficient based on the common logarithm of the gas logging data of the formation to be identified in the target well, the standard deviation of the common logarithms of the historical gas logging data of the drilled formations, the average value of the common logarithms of the historical gas logging data of the drilled formations, the drilling time of the formation to be identified, the standard deviation of the historical drilling times of the drilled formations, and the average value of the historical drilling times of the drilled formations is expressed by the following formula: Z = (V - aver(V)) / V' - (ROP - aver(ROP)) / ROP'; Where Z is the intermediate operation coefficient, V is the common logarithm of the gas logging data of the formation to be identified, V' is the standard deviation of the common logarithms of the historical gas logging data of the drilled formations, aver(V) is the average value of the common logarithms of the historical gas logging data of the drilled formations, ROP is the drilling time of the formation to be identified, ROP' is the standard deviation of the historical drilling times of the drilled formations, and aver(ROP) is the average value of the historical drilling times of the drilled formations; The calculation of the compensation coefficient based on the gamma value corresponding to pure shale, the gamma value corresponding to pure quartz sandstone, the intermediate operation coefficient, and the absolute value of the intermediate operation coefficient is expressed by the following formula: Φ R =(GR sh -GR sa )×(Z + ABS(Z)) / 2; Among them, Φ R is the compensation coefficient, GR sh is the gamma value corresponding to pure mudstone, GR sa is the gamma value corresponding to pure quartz sandstone, Z is the intermediate operation coefficient, and ABS(Z) is the absolute value of the intermediate operation coefficient; The calculation of the first corrected grain-size gamma value based on the grain-size gamma value and the compensation coefficient is expressed by the following formula: GR Φ = GR L - Φ R ; where, GR Φ is the first corrected grain size gamma value, and GR L is the grain size gamma value; The calculation of the reservoir index of the formation to be identified based on the first corrected grain-size gamma value is expressed by the following formula: Φ L = (GR Φ - MIN(GR Φ )) / 10 * (MAX(GR Φ ) - MIN(GR Φ )); where Φ L is the reservoir index of the reservoir to be identified, GR Φ is the first corrected grain size gamma value, MIN(GR Φ ) is the minimum value of the historical reservoir index of the drilled formation, MAX(GR Φ ) is the maximum value of the historical reservoir index of the drilled formation.

9. The reservoir identification method according to claim 1, wherein The calculation of the reservoir index of the formation to be identified based on the fused gamma value includes: Calculate an intermediate operation coefficient based on the common logarithm of the gas logging data of the formation to be identified in the target well, the standard deviation of the common logarithms of the historical gas logging data of the drilled formations, the average value of the common logarithms of the historical gas logging data of the drilled formations, the drilling time of the formation to be identified, the standard deviation of the historical drilling times of the drilled formations, and the average value of the historical drilling times of the drilled formations; Calculate a compensation coefficient based on the gamma value corresponding to pure shale, the gamma value corresponding to pure quartz sandstone, the intermediate operation coefficient, and the absolute value of the intermediate operation coefficient; Calculate a second corrected grain-size gamma value based on the fused gamma value and the compensation coefficient; Calculate the reservoir index of the formation to be identified based on the second corrected grain-size gamma value.

10. The reservoir identification method according to claim 9, characterized in that The standard deviation of the common logarithm of the gas logging data of the formation to be identified in the target well, the common logarithm of the historical gas logging data of the drilled formation, the average value of the common logarithm of the historical gas logging data of the drilled formation, the drilling time of the formation to be identified, the standard deviation of the historical drilling time of the drilled formation, and the average value of the historical drilling time of the drilled formation are used to calculate an intermediate operation coefficient, which is expressed by the following formula: Z = (V - aver(V)) / V' - (ROP - aver(ROP)) / ROP'; where Z is the intermediate operation coefficient, V is the common logarithm of the gas logging data of the formation to be identified, V' is the standard deviation of the common logarithm of the historical gas logging data of the drilled formation, aver(V) is the average value of the common logarithm of the historical gas logging data of the drilled formation, ROP is the drilling time of the formation to be identified, ROP' is the standard deviation of the historical drilling time of the drilled formation, and aver(ROP) is the average value of the historical drilling time of the drilled formation; The compensation coefficient is calculated based on the gamma value corresponding to pure shale, the gamma value corresponding to pure quartz sandstone, the intermediate operation coefficient, and the absolute value of the intermediate operation coefficient, which is expressed by the following formula: Φ R = (GR sh - GR sa ) × (Z + ABS(Z)) / 2; Among them, Φ R is the compensation coefficient, GR sh is the gamma value corresponding to pure mudstone, GR sa is the gamma value corresponding to pure quartz sandstone, Z is the intermediate operation coefficient, and ABS(Z) is the absolute value of the intermediate operation coefficient; The second corrected grain size gamma value is calculated based on the fused gamma value and the compensation coefficient, which is expressed by the following formula: GR Φ = GR R - Φ R ; where, GR Φ is the second corrected particle size gamma value, and GR R is the fusion gamma value; The reservoir index of the formation to be identified is calculated based on the second corrected grain size gamma value, which is expressed by the following formula: Φ L =(GR Φ -MIN(GR Φ )) / 10*(MAX(GR Φ )-MIN(GR Φ )); where Φ L is the reservoir index of the reservoir to be identified, GR Φ is the second corrected grain size gamma value, MIN(GR Φ ) is the minimum value of the historical reservoir index of the drilled formation, MAX(GR Φ ) is the maximum value of the historical reservoir index of the drilled formation.

11. The reservoir identification method according to claim 9, wherein, Determining the reservoir identification result of the reservoir to be identified based on the similarity coefficient between adjacent coordinate points in the determination coordinate system when drilling the reservoir to be identified includes: When the similarity coefficient between adjacent coordinate points in the determination coordinate system is less than or equal to the set threshold during the drilling of the reservoir to be identified, it is determined that continuing drilling will reach a non-reservoir. In the case where the trajectory can still be adjusted in time within the controllable range of the adjustment critical angle to continue drilling in the current reservoir, the drilling trajectory is adjusted to the previous normal point until the similarity coefficient between adjacent coordinate points is gradually adjusted to be greater than the set threshold within the controllable range of the adjustment critical angle.

12. A reservoir identification device, characterized in that, Including: A data acquisition module for acquiring multiple cuttings grain size analysis data of the formation to be identified in the target well; A fitting module for obtaining a fitting formula describing the linear relationship of the core grain size analysis data of the known well, and obtaining multiple fitted cuttings grain size analysis data of the target well based on the multiple cuttings grain size analysis data and the fitting formula; A first calculation module for calculating the grain size gamma value or the fused gamma value based on the multiple fitted cuttings grain size analysis data; A second calculation module for calculating the reservoir index of the formation to be identified based on the grain size gamma value or the fused gamma value; A reservoir identification module for constructing a determination coordinate system based on the grain size gamma value and the reservoir index, or constructing a determination coordinate system based on the fused gamma value and the reservoir index, and determining the reservoir identification result of the formation to be identified based on the similarity coefficient between adjacent coordinate points in the determination coordinate system when drilling the formation to be identified.

13. The reservoir identification device according to claim 12, wherein Obtaining the multiple fitted cuttings grain size analysis data of the target well based on the multiple cuttings grain size analysis data and the fitting formula includes: Substitute all the cuttings grain size analysis data into the fitting formula one by one to obtain multiple fitted cuttings grain size analysis data of the target well after fitting.

14. The reservoir identification device according to claim 12, characterized in that, Calculating the grain size gamma value based on the formation to be identified based on the multiple fitted cuttings grain size analysis data includes: Carry out lithology classification and naming based on grain size for the multiple fitted cuttings grain size analysis data to obtain the percentages of different lithology types of the cuttings in the formation to be identified; From the percentages of different lithology types of the cuttings in the formation to be identified, obtain the shale percentage of the cuttings in the formation to be identified, and calculate the grain size gamma value based on the cuttings in the formation to be identified based on the shale percentage of the cuttings in the formation to be identified, the gamma value corresponding to pure shale, and the gamma value corresponding to pure quartz sandstone.

15. The reservoir identification device according to claim 12, characterized in that, Calculating the fusion gamma value based on the formation to be identified based on the multiple fitted cuttings grain size analysis data includes: Carry out lithology classification and naming based on grain size for the multiple fitted cuttings grain size analysis data to obtain the percentages of different lithology types of the cuttings in the formation to be identified; From the percentages of different lithology types of the cuttings in the formation to be identified, obtain the shale percentage of the cuttings in the formation to be identified, and calculate the grain size gamma value based on the cuttings in the formation to be identified based on the shale percentage of the cuttings in the formation to be identified, the gamma value corresponding to pure shale, and the gamma value corresponding to pure quartz sandstone; Calculate the fusion gamma value based on the cuttings in the formation to be identified based on the grain size gamma value, the gamma value of the logging while drilling, and the weight coefficient of the gamma value of the logging while drilling.

16. The reservoir identification device according to claim 14 or 15, characterized in that Calculating the grain size gamma value based on the cuttings in the formation to be identified based on the shale percentage of the cuttings in the formation to be identified, the gamma value corresponding to pure shale, and the gamma value corresponding to pure quartz sandstone is represented by the following formula: GR L =(GR sh -GR sa )log2(3V shl +1)+GR sa ; Among them, GR L is the grain size gamma value of the cuttings of the formation to be identified, GR sh is the corresponding gamma value of pure mudstone, GR sa is the corresponding gamma value of pure quartz sandstone, V shl is the percentage of argillaceous rock in the cuttings of the formation to be identified.

17. The reservoir identification device according to claim 15, wherein, Calculating the fusion gamma value based on the cuttings in the formation to be identified based on the grain size gamma value, the gamma value of the logging while drilling, and the weight coefficient of the gamma value of the logging while drilling is represented by the following formula: GR R = Q c × GR c +(1 - Q c )× GR L ; Among them, GR R is the fused gamma value of the cuttings of the formation to be identified, GR c is the gamma value of the logging-while-drilling, Q c is the weight coefficient of the gamma value of the logging-while-drilling, GR L is the grain-size gamma value; Weight coefficient Q of the gamma value in logging while drilling c It is expressed by the following formula: Q c = (πL 2 + 2πd) / (π(L + d) 2 ); Wherein, L is the set logging gamma detection depth, and d is the diameter of the drilled wellbore.

18. The reservoir identification device according to claim 12, wherein, Calculating the reservoir index of the formation to be identified based on the grain size gamma value includes: Calculate the intermediate operation coefficient based on the common logarithm of the gas logging data of the formation to be identified in the target well, the standard deviation of the common logarithms of the historical gas logging data of the drilled formations, the average value of the common logarithms of the historical gas logging data of the drilled formations, the drilling time of the formation to be identified, the standard deviation of the historical drilling times of the drilled formations, and the average value of the historical drilling times of the drilled formations; Calculate the compensation coefficient based on the gamma value corresponding to pure shale, the gamma value corresponding to pure quartz sandstone, the intermediate operation coefficient, and the absolute value of the intermediate operation coefficient; Calculate the first corrected grain size gamma value based on the grain size gamma value and the compensation coefficient; Calculate the reservoir index of the formation to be identified based on the first corrected grain size gamma value.

19. The reservoir identification device according to claim 18, wherein, Calculate an intermediate operation coefficient based on the common logarithm of the gas logging data of the formation to be identified in the target well, the standard deviation of the common logarithms of the historical gas logging data of the drilled formations, the average value of the common logarithms of the historical gas logging data of the drilled formations, the drilling time of the formation to be identified, the standard deviation of the historical drilling times of the drilled formations, and the average value of the historical drilling times of the drilled formations, which is expressed by the following formula: Z = (V - aver(V)) / V' - (ROP - aver(ROP)) / ROP'; where Z is the intermediate operation coefficient, V is the common logarithm of the gas logging data of the formation to be identified, V' is the standard deviation of the common logarithms of the historical gas logging data of the drilled formations, aver(V) is the average value of the common logarithms of the historical gas logging data of the drilled formations, ROP is the drilling time of the formation to be identified, ROP' is the standard deviation of the historical drilling times of the drilled formations, and aver(ROP) is the average value of the historical drilling times of the drilled formations; Calculate a compensation coefficient based on the gamma value corresponding to pure shale, the gamma value corresponding to pure quartz sandstone, the intermediate operation coefficient, and the absolute value of the intermediate operation coefficient, which is expressed by the following formula: Φ R =(GR sh -GR sa )×(Z + ABS(Z)) / 2; Among them, Φ R is the compensation coefficient, GR sh is the gamma value corresponding to pure mudstone, GR sa is the gamma value corresponding to pure quartz sandstone, Z is the intermediate operation coefficient, and ABS(Z) is the absolute value of the intermediate operation coefficient; Calculate a first corrected grain-size gamma value based on the grain-size gamma value and the compensation coefficient, which is expressed by the following formula: GR Φ = GR L - Φ R ; where, GR Φ is the first corrected grain size gamma value, and GR L is the grain size gamma value; Calculate the reservoir index of the formation to be identified based on the first corrected grain-size gamma value, which is expressed by the following formula: Φ L =(GR Φ -MIN(GR Φ )) / 10*(MAX(GR Φ )-MIN(GR Φ )); where Φ L is the reservoir index of the reservoir to be identified, GR Φ is the first corrected grain size gamma value, MIN(GR Φ ) is the minimum value of the historical reservoir index of the drilled formation, MAX(GR Φ ) is the maximum value of the historical reservoir index of the drilled formation.

20. The reservoir identification device according to claim 12, characterized in that, Calculating the reservoir index of the formation to be identified based on the fused gamma value includes: Calculating an intermediate operation coefficient based on the common logarithm of the gas logging data of the formation to be identified in the target well, the standard deviation of the common logarithms of the historical gas logging data of the drilled formations, the average value of the common logarithms of the historical gas logging data of the drilled formations, the drilling time of the formation to be identified, the standard deviation of the historical drilling times of the drilled formations, and the average value of the historical drilling times of the drilled formations; Calculating a compensation coefficient based on the gamma value corresponding to pure shale, the gamma value corresponding to pure quartz sandstone, the intermediate operation coefficient, and the absolute value of the intermediate operation coefficient; Calculating a second corrected grain-size gamma value based on the fused gamma value and the compensation coefficient; Calculating the reservoir index of the formation to be identified based on the second corrected grain-size gamma value.

21. The reservoir identification device according to claim 20, wherein Calculate an intermediate operation coefficient based on the common logarithm of the gas logging data of the formation to be identified in the target well, the standard deviation of the common logarithms of the historical gas logging data of the drilled formations, the average value of the common logarithms of the historical gas logging data of the drilled formations, the drilling time of the formation to be identified, the standard deviation of the historical drilling times of the drilled formations, and the average value of the historical drilling times of the drilled formations, which is expressed by the following formula: Z = (V - aver(V)) / V' - (ROP - aver(ROP)) / ROP'; where Z is the intermediate operation coefficient, V is the common logarithm of the gas logging data of the formation to be identified, V' is the standard deviation of the common logarithms of the historical gas logging data of the drilled formations, aver(V) is the average value of the common logarithms of the historical gas logging data of the drilled formations, ROP is the drilling time of the formation to be identified, ROP' is the standard deviation of the historical drilling times of the drilled formations, and aver(ROP) is the average value of the historical drilling times of the drilled formations; The compensation coefficient is calculated based on the gamma value corresponding to pure mudstone, the gamma value corresponding to pure quartz sandstone, the intermediate operation coefficient, and the absolute value of the intermediate operation coefficient, and is expressed by the following formula: Φ R = (GR sh - GR sa ) × (Z + ABS(Z)) / 2; Among them, Φ R is the compensation coefficient, GR sh is the gamma value corresponding to pure mudstone, GR sa is the gamma value corresponding to pure quartz sandstone, Z is the intermediate operation coefficient, and ABS(Z) is the absolute value of the intermediate operation coefficient; The second corrected grain size gamma value is calculated based on the fused gamma value and the compensation coefficient, and is expressed by the following formula: GR Φ = GR R - Φ R ; where, GR Φ is the second corrected particle size gamma value, and GR R is the fusion gamma value; The reservoir index of the formation to be identified is calculated based on the second corrected grain size gamma value, and is expressed by the following formula: Φ L =(GR Φ -MIN(GR Φ )) / 10*(MAX(GR Φ )-MIN(GR Φ )); where Φ L is the reservoir index of the reservoir to be identified, GR Φ is the second corrected grain size gamma value, MIN(GR Φ ) is the minimum value of the historical reservoir index of the drilled formation, MAX(GR Φ ) is the maximum value of the historical reservoir index of the drilled formation.

22. The reservoir identification device according to claim 12, characterized in that, When drilling the reservoir to be identified, the reservoir identification result of the reservoir to be identified is determined based on the similarity coefficient between adjacent coordinate points in the determination coordinate system, including: When the similarity coefficient between adjacent coordinate points in the determination coordinate system is less than or equal to the set threshold during the drilling of the reservoir to be identified, it is determined that continuing drilling will reach a non-reservoir. In the case where the trajectory can still be adjusted in time to continue drilling in the current reservoir within the controllable range of the adjustment critical angle, the drilling trajectory is adjusted to the previous normal point until the similarity coefficient between adjacent coordinate points is gradually adjusted to be greater than the set threshold within the controllable range of the adjustment critical angle.

23. An electronic device, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, When the processor executes the program, the reservoir identification method according to any one of claims 1 to 11 is implemented.

24. A machine-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, the reservoir identification method according to any one of claims 1 to 11 is implemented.

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