Crack identification method and device, electronic equipment and storage medium

Abstract

The invention provides a crack identification method and device, electronic equipment and a storage medium, and the method comprises the steps: determining a corresponding target well section according to the obtained logging data of a to-be-evaluated well; extracting an interval transit time logging curve and a deep lateral resistivity logging curve of the target well section from the logging data; determining a corresponding interval transit time change rate curve and a corresponding deep lateral resistivity change rate curve based on the interval transit time logging curve and the deep lateral resistivity logging curve respectively; based on the sound wave time difference change rate curve, filling the deep lateral resistivity change rate curve to obtain a corresponding filling result; the filling result is the fracture development section. On the basis of obtaining interval transit time and deep lateral resistivity logging values at different depths, a corresponding change rate curve is obtained, and then a corresponding fracture development section is determined, so that fracture recognition is realized.

Description

Technical Field

[0001] This invention relates to the field of oil and gas reservoir geophysics, and in particular to a fracture identification method, device, electronic device, and storage medium. Background Technology

[0002] Currently, the main methods for identifying fractures include core drilling, imaging logging, and conventional logging.

[0003] Core drilling is the most direct method of identification, allowing direct observation of fracture formation. However, this method is costly, and the impact of fractures on the core can easily lead to core breakage, making it difficult to utilize effectively.

[0004] Imaging logging methods include several types such as electrical imaging, acoustic imaging, nuclear magnetic resonance imaging, and downhole optical photography. Imaging logging can clearly display the two-dimensional geological features of the wellbore. However, the current availability of imaging logging data is relatively limited, and the detection depth is usually shallow. Therefore, in poor wellbore conditions, there may be issues with misidentification of real and false fractures.

[0005] Conventional logging methods include the relative diameter anomaly method, the three-porosity ratio method, the secondary porosity ratio method, the elastic modulus difference ratio method, the resistivity invasion correction difference ratio method, and the cross-plot method. However, most of these methods involve complex mathematical models, and therefore, in the actual process of identifying fractures in tight reservoirs, they often face challenges such as complex operation, difficulty in parameter selection, low certainty, and a high degree of human intervention. Summary of the Invention

[0006] This invention provides a crack identification method, device, electronic device, and storage medium for simple and intuitive crack identification with minimal human intervention.

[0007] In a first aspect, the present invention provides a crack identification method, comprising:

[0008] Based on the logging data of the well to be evaluated, determine the corresponding target well section;

[0009] From the logging data, extract the sonic transit time logging curve and deep lateral resistivity logging curve of the target well section;

[0010] Based on the sonic transit time logging curve and the deep lateral resistivity logging curve, the corresponding sonic transit time change rate curve and deep lateral resistivity change rate curve are determined respectively.

[0011] Based on the acoustic time difference rate curve, the deep lateral resistivity rate curve is filled to obtain the corresponding filling result; the filling result is the crack development segment.

[0012] Optionally, the sonic transit time logging curve and the deep lateral resistivity logging curve are displayed in the same channel on the logging chart; based on the sonic transit time logging curve and the deep lateral resistivity logging curve, the corresponding sonic transit time change rate curve and deep lateral resistivity change rate curve are determined, including:

[0013] Adjust the scale range in the logging chart until the sonic transit time logging curve and the deep lateral resistivity logging curve displayed on the same channel coincide in the low natural gamma reservoir.

[0014] The corresponding values ​​of the curves in the well sections with the most overlap in the low natural gamma reservoirs are selected as the base values ​​of the response curves.

[0015] Based on the baseline curve, and in conjunction with the sonic transit time logging curve and the deep lateral resistivity logging curve, the sonic transit time change rate curve and the deep lateral resistivity change rate curve are determined.

[0016] Optionally, the acoustic transit time rate curve and the deep lateral resistivity rate curve are displayed on the same channel; based on the acoustic transit time rate curve, the deep lateral resistivity rate curve is filled to obtain a corresponding filling result; the filling result is the crack development segment, including:

[0017] In the well logging diagram, the sonic transit time rate curve and the deep lateral resistivity rate curve displayed on the same channel are overlapped according to a preset scale to obtain the curve overlap point;

[0018] Using the acoustic wave time difference rate curve as the right boundary, the area where the curves overlap is filled from left to right based on the deep lateral resistivity rate curve to obtain the filling result.

[0019] Optionally, based on the baseline curve value, and in conjunction with the sonic transit time logging curve and the deep lateral resistivity logging curve, the sonic transit time change rate curve and the deep lateral resistivity change rate curve are determined, including:

[0020] Based on the sonic transit time logging curve and the deep lateral resistivity logging curve, the sonic transit time logging value and the deep lateral resistivity logging value are determined respectively.

[0021] The acoustic transit time change rate curve is determined by using a pre-defined expression based on the acoustic transit time change rate, combined with the curve baseline and the acoustic transit time logging values.

[0022] The deep lateral resistivity change rate curve is determined by using a pre-defined expression for the deep lateral resistivity change rate, combined with the curve base value and the deep lateral resistivity logging value.

[0023] Optionally, the expression for determining the rate of change of acoustic wave time difference is specifically as follows:

[0024] DTroc = (DT - DT base value) / DT base value;

[0025] The specific expression for determining the rate of change of deep lateral resistivity is as follows:

[0026] RDroc = (RD - RD base value) / (RD + RD base value);

[0027] Where DTroc is the sonic transit time rate of change, DT is the sonic transit time logging value, DT baseline is the baseline value of the sonic transit time logging curve, RD is the deep lateral resistivity rate of change, and RD is the deep lateral resistivity measurement value.

[0028] roc

[0029] Well value, RD base value is the curve base value of the deep lateral resistivity logging curve.

[0030] In a second aspect, the present invention provides a crack identification device, comprising:

[0031] The target well section determination module is used to determine the corresponding target well section based on the obtained logging data of the well to be evaluated.

[0032] The extraction module is used to extract the sonic transit time logging curve and deep lateral resistivity logging curve of the target well section from the logging data.

[0033] The rate of change curve determination module is used to determine the corresponding sonic transit time change curve and deep lateral resistivity change curve based on the sonic transit time logging curve and the deep lateral resistivity logging curve, respectively.

[0034] The identification module is used to fill the deep lateral resistivity change rate curve based on the acoustic time difference change rate curve to obtain the corresponding filling result; the filling result is the crack development segment.

[0035] Optionally, the sonic transit time logging curve and the deep lateral resistivity logging curve are displayed on the same channel in the logging chart; the rate of change curve determination module includes:

[0036] The adjustment submodule is used to adjust the scale range in the logging chart until the sonic transit time logging curve and the deep lateral resistivity logging curve displayed on the same channel coincide in the low natural gamma reservoir.

[0037] The baseline value determination submodule is used to select the corresponding value of the curve in the well section with the most overlap in the low natural gamma reservoir as the baseline value of the response curve.

[0038] The rate of change curve determination submodule is used to determine the sonic transit time rate of change curve and the deep lateral resistivity rate of change curve based on the curve base value and in combination with the sonic transit time logging curve and the deep lateral resistivity logging curve.

[0039] Optionally, the acoustic transit time rate curve and the deep lateral resistivity rate curve are displayed on the same channel; the identification module includes:

[0040] The overlap submodule is used to overlap the acoustic transit rate curve and the deep lateral resistivity rate curve displayed on the same channel in the well logging diagram according to a preset scale to obtain the curve overlap point.

[0041] The filling submodule is used to fill the area where the curves overlap, based on the deep lateral resistivity change rate curve, from left to right, with the acoustic wave time difference rate curve as the right boundary, to obtain the filling result.

[0042] Thirdly, the present invention provides an electronic device including a processor and a memory, the memory storing computer-readable instructions that, when executed by the processor, perform the steps of the method provided in the first aspect above.

[0043] Fourthly, the present invention provides a storage medium having a computer program stored thereon, which, when executed by a processor, performs the steps of the method provided in the first aspect above.

[0044] As can be seen from the above technical solutions, the present invention has the following advantages:

[0045] This invention provides a fracture identification method, device, electronic device, and storage medium. The method includes: determining a target well section based on the acquired logging data of the well to be evaluated; extracting the sonic transit time logging curve and deep lateral resistivity logging curve of the target well section from the logging data; determining the corresponding sonic transit time change rate curve and deep lateral resistivity change rate curve based on the sonic transit time logging curve and the deep lateral resistivity logging curve, respectively; filling the deep lateral resistivity change rate curve based on the sonic transit time change rate curve to obtain a corresponding filling result; the filling result is the fracture development section. By obtaining the sonic transit time and deep lateral resistivity logging values ​​at different depths, the corresponding change rate curves are obtained, thereby determining the corresponding fracture development section, thus achieving fracture identification. The parameter selection of this invention is very intuitive and reliable, and the fracture identification process does not require the design of too many complex mathematical models, avoiding excessive manual intervention, and greatly improving the convenience and objectivity of single-well fracture identification. Attached Figure Description

[0046] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0047] Figure 1 This is a flowchart illustrating the steps of a crack identification method according to a first embodiment of the present invention.

[0048] Figure 2 This is a flowchart illustrating the steps of a second embodiment of the crack identification method of the present invention;

[0049] Figure 3 Figure 1 shows an example of crack identification using the acoustic transit time and deep lateral resistivity change rate method.

[0050] Figure 4 Example diagram for crack identification using the method of acoustic transit time and deep lateral resistivity change rate;

[0051] Figure 5 This is a structural block diagram of an embodiment of a crack identification device according to the present invention. Detailed Implementation

[0052] This invention provides a crack identification method, device, electronic device, and storage medium for simple and intuitive crack identification with minimal human intervention.

[0053] To make the objectives, features, and advantages of this invention more apparent and understandable, the technical solutions of the embodiments of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the embodiments described below are only some embodiments of this invention, and not all embodiments. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0054] Example 1

[0055] Please see Figure 1 , Figure 1 This is a flowchart illustrating the steps of a crack identification method according to an embodiment of the present invention. The method includes:

[0056] Step S101: Determine the corresponding target well section based on the obtained logging data of the well to be evaluated;

[0057] Step S102: Extract the sonic transit time logging curve and deep lateral resistivity logging curve of the target well section from the logging data.

[0058] In this embodiment of the invention, the sonic transit time logging curve and deep side electron rate logging curve of the target well section are extracted from the imaging logging curve and interpretation results data of the logging data of the well to be evaluated.

[0059] It should be noted that acoustic velocity is typically related to parameters such as rock porosity, pore type, and rock density. By analyzing acoustic transit time curves, the reservoir type, porosity, and formation connectivity can be determined.

[0060] Resistivity is typically associated with parameters such as rock porosity and the conductivity of pore fluids. By analyzing deep lateral resistivity curves, information such as the water content, porosity, and rock type of a formation can be identified.

[0061] Step S103: Based on the sonic transit time logging curve and the deep lateral resistivity logging curve, determine the corresponding sonic transit time change rate curve and the deep lateral resistivity change rate curve, respectively.

[0062] It should be noted that the sonic transit time rate curve reflects the rate of change of sonic wave velocity in the formation, and these rates of change may be related to the P-wave velocity, lithological variations, porosity variations, and other factors. By analyzing the sonic transit time rate curve, information such as formation interfaces and reservoir variations can be identified more precisely.

[0063] The deep lateral resistivity rate curve reflects the rate of change of resistivity in the formation, which may be related to changes in water content, porosity, and lithology. By analyzing the deep lateral resistivity rate curve, the boundaries of water, oil, and gas layers in the formation, as well as the changes in reservoir properties, can be identified more accurately.

[0064] In an optional embodiment, the sonic transit time logging curve and the deep lateral resistivity logging curve are displayed on the same channel in the logging chart; based on the sonic transit time logging curve and the deep lateral resistivity logging curve, the corresponding sonic transit time change rate curve and the deep lateral resistivity change rate curve are determined, including:

[0065] Adjust the scale range in the logging chart until the sonic transit time logging curve and the deep lateral resistivity logging curve displayed on the same channel coincide in the low natural gamma reservoir.

[0066] The corresponding values ​​of the curves in the well sections with the most overlap in the low natural gamma reservoirs are selected as the base values ​​of the response curves.

[0067] Based on the baseline curve, and in conjunction with the sonic transit time logging curve and the deep lateral resistivity logging curve, the sonic transit time change rate curve and the deep lateral resistivity change rate curve are determined.

[0068] In this embodiment of the invention, the scale range of the logging chart is adjusted until the sonic transit time logging curve and the deep lateral resistivity curve overlap as much as possible in the low natural gamma reservoir. Then, the corresponding values ​​of the curves in the well section with the most overlap within the overlapping area are selected as the base values ​​of the response curves of the sonic transit time logging curve and the deep lateral resistivity logging curve, thereby determining the sonic transit time change rate curve and the deep lateral resistivity change rate curve. Overlapping the curves in the low natural gamma reservoir better represents the basic characteristics of the formation, thus ensuring the reliability of subsequent calculations.

[0069] Step S104: Based on the acoustic wave time difference change rate curve, fill the deep lateral resistivity change rate curve to obtain the corresponding filling result; the filling result is the crack development segment.

[0070] In this embodiment of the invention, after analyzing the acoustic time difference rate curve and the deep lateral resistivity rate curve, the deep lateral resistivity rate curve can be filled using a corresponding filling method. The filling result will indicate the location of the crack development segment.

[0071] This invention provides a fracture identification method, comprising: determining a target well section based on the acquired logging data of the well to be evaluated; extracting the sonic transit time logging curve and deep lateral resistivity logging curve of the target well section from the logging data; determining the corresponding sonic transit time change rate curve and deep lateral resistivity change rate curve based on the sonic transit time logging curve and the deep lateral resistivity logging curve, respectively; filling the deep lateral resistivity change rate curve based on the sonic transit time change rate curve to obtain a corresponding filling result; the filling result is the fracture development section. By obtaining the sonic transit time and deep lateral resistivity logging values ​​at different depths, the corresponding change rate curves are obtained, thereby determining the corresponding fracture development section, thus achieving fracture identification. The parameter selection of this invention is very intuitive and reliable, and the fracture identification process does not require the design of too many complex mathematical models, avoiding excessive manual intervention, and greatly improving the convenience and objectivity of single-well fracture identification.

[0072] Example 2

[0073] Please see Figure 2 , Figure 2 This is a flowchart illustrating a second embodiment of a method of the present invention, the steps of which include:

[0074] S201. Based on the logging data of the well to be evaluated, determine the corresponding target well section.

[0075] In this embodiment of the invention, based on the actual situation of the study area, logging data of the well to be evaluated is collected, including conventional logging curves and interpretation results, imaging logging curve interpretation results, and logging core and cuttings data. Then, one or more of the following methods are used to determine the target well section: geological analysis, seismic data analysis, logging data analysis, geological model establishment, expert review, and risk assessment.

[0076] S202, extract the sonic transit time logging curve and the deep lateral resistivity logging curve of the target well section from the logging data; the sonic transit time logging curve and the deep lateral resistivity logging curve are displayed in the same channel on the logging chart;

[0077] Well logging charts typically display multiple curves, each representing different formation parameters or characteristics. Simultaneous display refers to showing two or more curves on the same plane simultaneously in a well logging chart, such as... Figure 3 As shown, Figure 3 Figure 1 shows an embodiment of the method for crack identification using acoustic transit time and deep lateral resistivity change rate, including... Figure 3 (A) Schematic diagram of lithology curves Figure 3 (B) Schematic diagram of acoustic transit time and deep lateral resistivity curves. Figure 3 (C) Porosity curve schematic diagram Figure 3 (D) is a schematic diagram showing the overlap of the curves representing the rate of change of acoustic transit time and the rate of change of deep lateral resistivity. Figure 3 (E) The fracture tadpole plot interpreted from imaging logging, by displaying multiple curves along the same path, allows for a more intuitive observation of the relationships and trends between them, aiding in geological interpretation and engineering evaluation. Please refer to... Figure 3 , Figure 3 Schematic diagram of lithology curve in (A), Figure 3 (B) Schematic diagram of acoustic transit time and deep lateral resistivity curves and Figure 3 The porosity curve in (C) can be obtained through analysis of the logging data in step S201, whereby... Figure 3 In (B), the solid line represents the deep lateral resistivity logging curve, and the dashed line represents the sonic transit time logging curve. Simultaneously, by statistically analyzing the dip angle of fractures in the target formation, logging curves incorporating fracture tadpole diagrams are plotted using logging processing and interpretation software. Figure 3 As shown in (E).

[0078] S203, Adjust the scale range in the logging chart until the sonic transit time logging curve and the deep lateral resistivity logging curve displayed on the same channel coincide in the low natural gamma reservoir.

[0079] In this embodiment of the invention, the scale range on the logging chart is adjusted to better show that the sonic transit time curve and the deep lateral resistivity logging curve overlap as much as possible in the low natural gamma reservoir.

[0080] S204, Select the corresponding value of the curve in the well section with the most overlap in the low natural gamma reservoir as the base value of the response curve;

[0081] In this embodiment of the invention, the corresponding values ​​of the sonic transit time and resistivity curves within the well section where the two curves overlap most in the same well log are the baseline values ​​of the response curve. Generally, the rationality of the baseline value selection can be verified by statistically analyzing the average sonic transit time and deep lateral resistivity of the target well section. Generally, the selected baseline value should not differ significantly from the average value. Furthermore, for reservoirs of different formations, if there are significant differences in lithological and electrical responses, the baseline values ​​of the curves should be determined segment by segment.

[0082] S205, based on the sonic transit time logging curve and the deep lateral resistivity logging curve, determine the sonic transit time logging value and the deep lateral resistivity logging value respectively;

[0083] S206, the acoustic transit time change rate curve is determined by using a pre-set expression for the expression and combining it with the curve base value and the acoustic transit time logging value; the expression for determining the acoustic transit time change rate is specifically as follows:

[0084] DTroc = (DT - DT base value) / DT base value;

[0085] S207, by using a pre-set expression for the rate of change of deep lateral resistivity, and combining the curve base value and the deep lateral resistivity logging value, the deep lateral resistivity change rate curve is determined; the sonic transit time change rate curve and the deep lateral resistivity change rate curve are displayed on the same channel; the expression for determining the rate of change of deep lateral resistivity is specifically as follows:

[0086] RDroc = (RD - RD base value) / (RD + RD base value);

[0087] Where DTroc is the sonic transit time rate of change, DT is the sonic transit time logging value, DT baseline is the baseline value of the sonic transit time logging curve, RD is the deep lateral resistivity rate of change, and RD is the deep lateral resistivity measurement value.

[0088] roc

[0089] Well value, RD base value is the curve base value of deep lateral resistivity logging curve.

[0090] In this embodiment of the invention, based on the well logging interpretation results and well logging lithology data, the sonic transit rate curve and the deep lateral resistivity rate curve are calculated only in the sandstone section (reservoir section), and not in the non-reservoir section (mudstone section).

[0091] S208, in the well logging diagram, the sonic transit time rate curve and the deep lateral resistivity rate curve displayed on the same channel are overlapped according to a preset scale to obtain the curve overlap point;

[0092] In this embodiment of the invention, the acoustic transit rate curve and the deep lateral resistivity rate curve are both displayed on the same track in the logging chart with a scale of -1 to 1. In the fracture development section, the acoustic transit rate increases positively, while the deep lateral resistivity rate increases negatively, and the two have certain mirror symmetry characteristics.

[0093] In the specific implementation, the expressions for determining the rate of change of acoustic wave transit time and the rate of change of deep lateral resistivity are determined by superimposing them with a pre-set scale to obtain the result. Figure 3 The solid and dashed parts in (D) are where the curves overlap.

[0094] S209, using the acoustic wave time difference rate of change curve as the right boundary, fill the area where the curves overlap from left to right based on the deep lateral resistivity rate of change curve to obtain the filling result.

[0095] In this embodiment of the invention, the curve fill function in the well logging plotting software can be used to continuously depict the fracture development on a single well, resulting in the following: Figure 3 (D) shows a schematic diagram of the overlap between the acoustic transit time rate and the lateral resistivity change rate curves. The solid line represents the acoustic transit time rate curve, the dashed line represents the deep lateral resistivity change rate curve, and the filled area represents the area from the deep lateral resistivity change rate curve to the acoustic transit time rate curve. The filling effect is evident. Figure 3 The crack development indicated by the crack tadpole diagram in (E) is quite consistent, thus demonstrating that a crack identification method of the present invention can achieve the purpose of crack identification.

[0096] In summary, the embodiments of the present invention utilize the sonic transit time logging curve and the deep lateral resistivity logging curve, which are more sensitive to fractures, to calculate their rate of change curves and perform mirror filling on the logging chart, thereby amplifying the response characteristics to fractures and thus intuitively reflecting the fracture development section.

[0097] This invention discloses a fracture identification method, comprising: determining a corresponding target well section based on the acquired logging data of the well to be evaluated; extracting the sonic transit time logging curve and the deep lateral resistivity logging curve of the target well section from the logging data; determining the corresponding sonic transit time change rate curve and the deep lateral resistivity change rate curve based on the sonic transit time logging curve and the deep lateral resistivity logging curve, respectively; filling the deep lateral resistivity change rate curve based on the sonic transit time change rate curve to obtain a corresponding filling result; the filling result being the fracture development section. By intuitively and reliably obtaining the acoustic transit time and deep lateral resistivity logging values ​​at different depths, and then obtaining the acoustic transit time change rate curve and the deep lateral resistivity change rate curve respectively according to the pre-set acoustic transit time change rate determination expression and the deep lateral resistivity change rate determination expression, the two change rate curves are finally displayed and filled in the same row of the logging chart to obtain a single identification fracture development segment. Thus, fracture identification can be achieved simply and intuitively without much manual intervention, greatly improving the convenience and objectivity of single-well fracture identification.

[0098] To facilitate understanding of the present invention by those skilled in the art, the following example illustrates the use of the Xu'er tight sandstone gas reservoir in the Xinchang tectonic belt of western Sichuan Basin.

[0099] Example: (1) Collect conventional logging data and imaging logging results from the drilled well X601 in the study area, such as Figure 4 (A) lithology curve diagram Figure 4 (B) Schematic diagram of acoustic transit time and deep lateral resistivity curves, and Figure 4 As shown in the porosity curve diagram of (C), the dip angle of the fractures in the target formation is statistically analyzed, and a well logging curve including the fracture tadpole diagram is plotted using well logging processing and interpretation software, as follows. Figure 4 (E) shows a crack tadpole diagram of an example crack identification method of the present invention;

[0100] (2) Compare the fracture development interpreted by imaging logging with conventional logging curves to establish logging response characteristics for typical fracture types;

[0101] (3) According to the logging response characteristics of typical fracture types, the common characteristics of fracture-developed sections are: resistivity is relatively low against a high-resistivity background; sonic transit time is significantly higher than that of the surrounding rock sections; and the sonic transit time and resistivity curves show a sharp "sawtooth" change. Other logging curves, such as compensated density, also show significant changes in fracture-developed sections, but the density curve is greatly affected by the wellbore environment and also shows a significant expansion trend in the enlarged section, which can easily lead to misjudgment of fracture development. Therefore, through comprehensive analysis of conventional logging-imaging fracture interpretation results, sonic transit time and deep lateral resistivity were selected as sensitive curves for fracture identification.

[0102] (4) Based on the collected well logging interpretation data and well logging lithology data, calculate the rate of change curves of wave depth lateral resistivity and sonic transit time in the sandstone section (reservoir section), but not in the non-reservoir section (mudstone section). The rate of change of the curve refers to the degree of deviation of the curve value at each depth point from the curve base value. A positive value indicates that the relative base value has increased, and a negative value indicates that the relative base value has decreased.

[0103] (5) Using well logging plotting software, display both the sonic transit rate curve and the deep lateral resistivity rate curve on the same track in the well logging chart with a scale of -1 to 1, as shown below. Figure 4 (D) shows the overlapping diagram of the acoustic transit time rate and the deep lateral resistivity rate curves. In the fracture development section, the acoustic transit time rate increases positively, while the deep lateral resistivity rate increases negatively, exhibiting a certain degree of mirror symmetry. Filling the deep lateral resistivity rate curve from left to right yields the following... Figure 4 (D) The larger the envelope area of ​​the fill right boundary, which is the acoustic transit time rate curve, the more developed the crack segment. No refill indicates a less developed crack segment, demonstrating the filling effect. Figure 4 (E) indicates a relatively good match in terms of crack development, thus demonstrating that the crack identification method of the present invention can achieve the purpose of crack identification.

[0104] Example 3

[0105] Please see Figure 5 , Figure 5 This is a structural block diagram of an embodiment of a crack identification device according to the present invention. The device includes:

[0106] The target well section determination module 301 is used to determine the corresponding target well section based on the obtained logging data of the well to be evaluated.

[0107] Extraction module 302 is used to extract the sonic transit time logging curve and deep lateral resistivity logging curve of the target well section from the logging data;

[0108] The rate of change curve determination module 303 is used to determine the corresponding sonic transit time change curve and deep lateral resistivity change curve based on the sonic transit time logging curve and the deep lateral resistivity logging curve, respectively.

[0109] The identification module 304 is used to fill the deep lateral resistivity change rate curve based on the acoustic time difference change rate curve to obtain the corresponding filling result; the filling result is the crack development segment.

[0110] In an optional embodiment, the sonic transit time logging curve and the deep lateral resistivity logging curve are displayed on the same channel in the logging chart; the rate of change curve determination module 303 includes:

[0111] The adjustment submodule is used to adjust the scale range in the logging chart until the sonic transit time logging curve and the deep lateral resistivity logging curve displayed on the same channel coincide in the low natural gamma reservoir.

[0112] The baseline value determination submodule is used to select the corresponding value of the curve in the well section with the most overlap in the low natural gamma reservoir as the baseline value of the response curve.

[0113] The rate of change curve determination submodule is used to determine the sonic transit time rate of change curve and the deep lateral resistivity rate of change curve based on the curve base value and in combination with the sonic transit time logging curve and the deep lateral resistivity logging curve.

[0114] In an optional embodiment, the acoustic transit time rate curve and the deep lateral resistivity rate curve are displayed on the same channel; the identification module 304 includes:

[0115] The overlap submodule is used to overlap the acoustic transit rate curve and the deep lateral resistivity rate curve displayed on the same channel in the well logging diagram according to a preset scale to obtain the curve overlap point.

[0116] The filling submodule is used to fill the area where the curves overlap, based on the deep lateral resistivity change rate curve, from left to right, with the acoustic wave time difference rate curve as the right boundary, to obtain the filling result.

[0117] In an optional embodiment, the rate of change curve determination submodule includes:

[0118] The logging value determination unit is used to determine the sonic transit time logging value and the deep lateral resistivity logging value based on the sonic transit time logging curve and the deep lateral resistivity logging curve, respectively.

[0119] The first rate of change curve determination unit is used to determine the sonic transit time change rate curve by combining the curve base value and the sonic transit time logging value with a pre-set sonic transit time change rate determination expression.

[0120] The second rate of change curve determination unit is used to determine the deep lateral resistivity change rate curve by combining the curve base value and the deep lateral resistivity logging value with a pre-set deep lateral resistivity change rate determination expression.

[0121] In an optional embodiment, the expression for determining the rate of change of acoustic time difference is specifically as follows:

[0122] DTroc = (DT - DT base value) / DT base value;

[0123] The specific expression for determining the rate of change of deep lateral resistivity is as follows:

[0124] RDroc = (RD - RD base value) / (RD + RD base value);

[0125] Where DTroc is the sonic transit time rate of change, DT is the sonic transit time logging value, DT baseline is the baseline value of the sonic transit time logging curve, RD is the deep lateral resistivity rate of change, and RD is the deep lateral resistivity logging value.

[0126] Well value, RD base value is the curve base value of the deep lateral resistivity logging curve.

[0127] Example 4

[0128] This invention also provides an electronic device, including a memory and a processor. The memory stores a computer program, which, when executed by the processor, causes the processor to perform the steps of a crack identification method according to any embodiment, including:

[0129] Based on the logging data of the well to be evaluated, determine the corresponding target well section;

[0130] From the logging data, extract the sonic transit time logging curve and deep lateral resistivity logging curve of the target well section;

[0131] Based on the sonic transit time logging curve and the deep lateral resistivity logging curve, the corresponding sonic transit time change rate curve and deep lateral resistivity change rate curve are determined respectively.

[0132] Based on the acoustic transit time rate curve, the deep lateral resistivity rate curve is filled to obtain the corresponding filling result; the filling result is the crack development segment.

[0133] Optionally, the sonic transit time logging curve and the deep lateral resistivity logging curve are displayed in the same channel on the logging chart; based on the sonic transit time logging curve and the deep lateral resistivity logging curve, the corresponding sonic transit time change rate curve and deep lateral resistivity change rate curve are determined, including:

[0134] Adjust the scale range in the logging chart until the sonic transit time logging curve and the deep lateral resistivity logging curve displayed on the same channel coincide in the low natural gamma reservoir.

[0135] The corresponding values ​​of the curves in the well sections with the most overlap in the low natural gamma reservoirs are selected as the base values ​​of the response curves.

[0136] Based on the baseline curve, and in conjunction with the sonic transit time logging curve and the deep lateral resistivity logging curve, the sonic transit time change rate curve and the deep lateral resistivity change rate curve are determined.

[0137] Optionally, the acoustic transit time rate curve and the deep lateral resistivity rate curve are displayed on the same channel; based on the acoustic transit time rate curve, the deep lateral resistivity rate curve is filled to obtain a corresponding filling result; the filling result is the crack development segment, including:

[0138] In the well logging diagram, the sonic transit time rate curve and the deep lateral resistivity rate curve displayed on the same channel are overlapped according to a preset scale to obtain the curve overlap point;

[0139] Using the acoustic wave time difference rate curve as the right boundary, the area where the curves overlap is filled from left to right based on the deep lateral resistivity rate curve to obtain the filling result.

[0140] Optionally, based on the baseline curve value, and in conjunction with the sonic transit time logging curve and the deep lateral resistivity logging curve, the sonic transit time change rate curve and the deep lateral resistivity change rate curve are determined, including:

[0141] Based on the sonic transit time logging curve and the deep lateral resistivity logging curve, the sonic transit time logging value and the deep lateral resistivity logging value are determined respectively.

[0142] The sonic transit time change rate curve is determined by using a pre-set expression based on the sonic transit time change rate, combined with the curve base value and the sonic transit time logging value.

[0143] The deep lateral resistivity change rate curve is determined by using a pre-defined expression for the deep lateral resistivity change rate, combined with the curve base value and the deep lateral resistivity logging value.

[0144] Optionally, the expression for determining the rate of change of acoustic wave time difference is specifically as follows:

[0145] DTroc = (DT - DT base value) / DT base value;

[0146] The specific expression for determining the rate of change of deep lateral resistivity is as follows:

[0147] RDroc = (RD - RD base value) / (RD + RD base value);

[0148] Where DTroc is the sonic transit time rate of change, DT is the sonic transit time logging value, DT baseline is the baseline value of the sonic transit time logging curve, RD is the deep lateral resistivity rate of change, and RD is the deep lateral resistivity logging value.

[0149] Well value, RD base value is the curve base value of the deep lateral resistivity logging curve.

[0150] Example 5

[0151] This invention also provides a computer storage medium storing a computer program thereon, wherein the computer program, when executed by the processor, implements the steps of a crack identification method according to any embodiment, including:

[0152] Based on the logging data of the well to be evaluated, determine the corresponding target well section;

[0153] From the logging data, extract the sonic transit time logging curve and deep lateral resistivity logging curve of the target well section;

[0154] Based on the sonic transit time logging curve and the deep lateral resistivity logging curve, the corresponding sonic transit time change rate curve and deep lateral resistivity change rate curve are determined respectively.

[0155] Based on the acoustic transit time rate curve, the deep lateral resistivity rate curve is filled to obtain the corresponding filling result; the filling result is the crack development segment.

[0156] Optionally, the sonic transit time logging curve and the deep lateral resistivity logging curve are displayed in the same channel on the logging chart; based on the sonic transit time logging curve and the deep lateral resistivity logging curve, the corresponding sonic transit time change rate curve and deep lateral resistivity change rate curve are determined, including:

[0157] Adjust the scale range in the logging chart until the sonic transit time logging curve and the deep lateral resistivity logging curve displayed on the same channel coincide in the low natural gamma reservoir.

[0158] The corresponding values ​​of the curves in the well sections with the most overlap in the low natural gamma reservoirs are selected as the base values ​​of the response curves.

[0159] Based on the baseline curve, and in conjunction with the sonic transit time logging curve and the deep lateral resistivity logging curve, the sonic transit time change rate curve and the deep lateral resistivity change rate curve are determined.

[0160] Optionally, the acoustic transit time rate curve and the deep lateral resistivity rate curve are displayed on the same channel; based on the acoustic transit time rate curve, the deep lateral resistivity rate curve is filled to obtain a corresponding filling result; the filling result is the crack development segment, including:

[0161] In the well logging diagram, the sonic transit time rate curve and the deep lateral resistivity rate curve displayed on the same channel are overlapped according to a preset scale to obtain the curve overlap point;

[0162] Using the acoustic wave time difference rate curve as the right boundary, the area where the curves overlap is filled from left to right based on the deep lateral resistivity rate curve to obtain the filling result.

[0163] Optionally, based on the baseline curve value, and in conjunction with the sonic transit time logging curve and the deep lateral resistivity logging curve, the sonic transit time change rate curve and the deep lateral resistivity change rate curve are determined, including:

[0164] Based on the sonic transit time logging curve and the deep lateral resistivity logging curve, the sonic transit time logging value and the deep lateral resistivity logging value are determined respectively.

[0165] The sonic transit time change rate curve is determined by using a pre-set expression based on the sonic transit time change rate, combined with the curve base value and the sonic transit time logging value.

[0166] The deep lateral resistivity change rate curve is determined by using a pre-defined expression for the deep lateral resistivity change rate, combined with the curve base value and the deep lateral resistivity logging value.

[0167] Optionally, the expression for determining the rate of change of acoustic wave time difference is specifically as follows:

[0168] DTroc = (DT - DT base value) / DT base value;

[0169] The specific expression for determining the rate of change of deep lateral resistivity is as follows:

[0170] RDroc = (RD - RD base value) / (RD + RD base value);

[0171] Where DTroc is the sonic transit time rate of change, DT is the sonic transit time logging value, DT baseline is the baseline value of the sonic transit time logging curve, RD is the deep lateral resistivity rate of change, and RD is the deep lateral resistivity measurement value.

[0172] roc

[0173] Well value, RD base value is the curve base value of the deep lateral resistivity logging curve.

[0174] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0175] In the several embodiments provided in this application, it should be understood that the methods, apparatuses, electronic devices, and storage media disclosed in this invention can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual couplings, direct couplings, or communication connections may be through some interfaces; indirect couplings or communication connections between devices or units may be electrical, mechanical, or other forms.

[0176] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0177] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0178] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a readable storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned readable storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0179] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A crack identification method, characterized in that, include: Based on the logging data of the well to be evaluated, determine the corresponding target well section; From the logging data, extract the sonic transit time logging curve and deep lateral resistivity logging curve of the target well section; Based on the sonic transit time logging curve and the deep lateral resistivity logging curve, the corresponding sonic transit time change rate curve and deep lateral resistivity change rate curve are determined respectively. Based on the acoustic time difference rate curve, the deep lateral resistivity rate curve is filled to obtain the corresponding filling result; the filling result is the crack development segment.

2. The crack identification method according to claim 1, characterized in that, The sonic transit time logging curve and the deep lateral resistivity logging curve are displayed in the same channel on the logging chart; based on the sonic transit time logging curve and the deep lateral resistivity logging curve, the corresponding sonic transit time change rate curve and deep lateral resistivity change rate curve are determined, including: Adjust the scale range in the logging chart until the sonic transit time logging curve and the deep lateral resistivity logging curve displayed on the same channel coincide in the low natural gamma reservoir. The corresponding values ​​of the curves in the well sections with the most overlap in the low natural gamma reservoirs are selected as the base values ​​of the response curves. Based on the baseline curve, and in conjunction with the sonic transit time logging curve and the deep lateral resistivity logging curve, the sonic transit time change rate curve and the deep lateral resistivity change rate curve are determined.

3. The crack identification method according to claim 2, characterized in that, The acoustic transit time rate curve and the deep lateral resistivity rate curve are displayed on the same channel; based on the acoustic transit time rate curve, the deep lateral resistivity rate curve is filled to obtain the corresponding filling result; the filling result is the crack development segment, including: In the well logging diagram, the sonic transit time rate curve and the deep lateral resistivity rate curve displayed on the same channel are overlapped according to a preset scale to obtain the curve overlap point; Using the acoustic wave time difference rate curve as the right boundary, the area where the curves overlap is filled from left to right based on the deep lateral resistivity rate curve to obtain the filling result.

4. The crack identification method according to claim 3, characterized in that, Based on the baseline curve, and combining the sonic transit time logging curve and the deep lateral resistivity logging curve, the sonic transit time change rate curve and the deep lateral resistivity change rate curve are determined, including: Based on the sonic transit time logging curve and the deep lateral resistivity logging curve, the sonic transit time logging value and the deep lateral resistivity logging value are determined respectively. The sonic transit time change rate curve is determined by using a pre-set expression based on the sonic transit time change rate, combined with the curve base value and the sonic transit time logging value. The deep lateral resistivity change rate curve is determined by using a pre-defined expression for the deep lateral resistivity change rate, combined with the curve base value and the deep lateral resistivity logging value.

5. The crack identification method according to claim 4, characterized in that, The specific expression for determining the rate of change of acoustic wave time difference is as follows: DTroc = (DT - DT base value) / DT base value; The specific expression for determining the rate of change of deep lateral resistivity is as follows: RDroc = (RD - RD base value) / (RD + RD base value); Where DTroc is the sonic transit time rate of change, DT is the sonic transit time logging value, DT baseline is the baseline value of the sonic transit time logging curve, RD is the deep lateral resistivity rate of change, and RD is the deep lateral resistivity logging value. Well value, RD base value is the curve base value of the deep lateral resistivity logging curve.

6. A crack detection device, characterized in that, include: The target well section determination module is used to determine the corresponding target well section based on the obtained logging data of the well to be evaluated. The extraction module is used to extract the sonic transit time logging curve and deep lateral resistivity logging curve of the target well section from the logging data. The rate of change curve determination module is used to determine the corresponding sonic transit time change curve and deep lateral resistivity change curve based on the sonic transit time logging curve and the deep lateral resistivity logging curve, respectively. The identification module is used to fill the deep lateral resistivity change rate curve based on the acoustic time difference change rate curve to obtain the corresponding filling result; the filling result is the crack development segment.

7. The crack identification device according to claim 6, characterized in that, The sonic transit time logging curve and the deep lateral resistivity logging curve are displayed on the same channel in the logging chart; the rate of change curve determination module includes: The adjustment submodule is used to adjust the scale range in the logging chart until the sonic transit time logging curve and the deep lateral resistivity logging curve displayed on the same channel coincide in the low natural gamma reservoir. The baseline value determination submodule is used to select the corresponding value of the curve in the well section with the most overlap in the low natural gamma reservoir as the baseline value of the response curve. The rate of change curve determination submodule is used to determine the sonic transit time rate of change curve and the deep lateral resistivity rate of change curve based on the curve base value and in combination with the sonic transit time logging curve and the deep lateral resistivity logging curve.

8. The crack identification device according to claim 7, characterized in that, The acoustic transit time rate curve and the deep lateral resistivity rate curve are displayed on the same channel; the identification module includes: The overlap submodule is used to overlap the acoustic transit rate curve and the deep lateral resistivity rate curve displayed on the same channel in the well logging diagram according to a preset scale to obtain the curve overlap point. The filling submodule is used to fill the area where the curves overlap, based on the deep lateral resistivity change rate curve, from left to right, with the acoustic wave time difference rate curve as the right boundary, to obtain the filling result.

9. An electronic device, characterized in that, It includes a processor and a memory, the memory storing computer-readable instructions that, when executed by the processor, perform the method as described in any one of claims 1-5.

10. A storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it performs the method as described in any one of claims 1-5.

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