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: reading a logging data set of a horizontal well collected according to a preset sampling interval in the drilling process of the horizontal well; processing based on the measurement and recording data set, and determining mechanical specific energy and a gas measurement anomaly index; performing normalization processing on the measurement data set, the mechanical specific energy and the gas measurement abnormal index to obtain target data; first weights of the first data on instantaneous drilling time in the target data are calculated; depth elimination processing is carried out on the instantaneous drilling time based on the first data and the first weight, and new instantaneous drilling time is determined; the fracture development probability is calculated based on the new instantaneous drilling time and the gas logging anomaly index; and determining a crack identification result of the current horizontal depth based on the crack development probability so as to subsequently carry out early warning based on the crack identification result. And thus, the underground stratum fracture-cavity development condition can be accurately identified.

Description

Technical Field

[0001] This invention relates to the field of petroleum exploration technology, and in particular to a fracture identification method, device, electronic device, and storage medium. Background Technology

[0002] During horizontal well drilling in oil and gas exploration and development, there is a 60% probability of encountering complex conditions involving mud loss, and fracture-related losses account for as much as 84% ​​of well leakage incidents. Therefore, early warning systems for fractures are necessary.

[0003] Currently, in the process of crack early warning, seismic data can often be used to identify larger cracks and faults. However, since well leakage accidents mainly occur in areas with small-scale cracks, and the resolution of seismic data is insufficient, cracks cannot be effectively identified. Summary of the Invention

[0004] In view of this, embodiments of the present invention provide a crack identification method, apparatus, electronic device, and storage medium to solve the problem that existing technologies cannot effectively identify cracks.

[0005] To achieve the above objectives, the embodiments of the present invention provide the following technical solutions:

[0006] A first aspect of the present invention discloses a crack identification method, the method comprising:

[0007] During horizontal well drilling, the logging dataset of the horizontal well is read according to a preset sampling interval;

[0008] Based on the recorded dataset, mechanical specific energy and gas measurement anomaly index are determined.

[0009] The recorded dataset, mechanical specific energy, and gas measurement anomaly index were normalized respectively to obtain the target data.

[0010] Calculate the first weight of the first data in relation to the instantaneous drilling time in the target data, wherein the first data belongs to the target data and there are multiple first data;

[0011] Based on the first data and the first weight, the instantaneous drilling time is subjected to depth elimination processing to determine a new instantaneous drilling time;

[0012] The probability of fracture development is calculated based on the new instantaneous drilling time and gas measurement anomaly index.

[0013] The crack development probability is used to determine the crack identification result at the current horizontal depth, so that subsequent early warnings can be issued based on the crack identification result.

[0014] Optionally, read logging data from horizontal wells collected at preset sampling intervals, including:

[0015] During horizontal well drilling, determine whether the current drilling status of the drilling equipment is a normal drilling status;

[0016] If so, collect and record the dataset according to the preset sampling interval;

[0017] The recorded dataset is filtered to obtain the processed recorded dataset.

[0018] Optionally, the recorded dataset is processed to determine the mechanical specific energy and gas anomaly index, including:

[0019] The mechanical specific energy is obtained by processing the drilling pressure, rotational speed, and drilling speed data, as well as the drill bit information of the drilling equipment, in the aforementioned dataset. The drill bit information of the drilling equipment is obtained in advance.

[0020] The gas measurement anomaly index is determined by processing the total hydrocarbon data from the recorded dataset and the drilling information of the drilling equipment, wherein the drilling information of the drilling equipment is acquired in real time.

[0021] Optionally, calculating the first weight of the first data with respect to the instantaneous drilling time in the target data includes:

[0022] Draw intersection diagrams between the instantaneous drilling time in the target data and each first data point;

[0023] For the intersection plot of the instantaneous drilling time and each first data point, an ellipse fitting result is obtained based on the intersection plot;

[0024] For each ellipse fitting result, the ellipse fitting result and the corresponding intersection plot are processed to obtain the corresponding average fitting degree.

[0025] Based on the average fitting degree and the ellipse fitting result, calculate the first weight of each first data point for the instantaneous drilling time.

[0026] Optionally, for the intersection plot of the instantaneous drilling time and each first data point, an ellipse fitting result is obtained based on the intersection plot, including:

[0027] For the intersection plot of the instantaneous drilling time and each first data point, the coordinates of the ellipse center are calculated based on the data in the intersection plot.

[0028] Calculate the translation coordinates based on the coordinates of the ellipse center and the intersection diagram;

[0029] The azimuth angle, major axis length, and minor axis length of the ellipse are calculated based on the translation coordinates.

[0030] Based on the ellipse center coordinates, ellipse azimuth angle, ellipse major axis length, and ellipse minor axis length, an ellipse fitting result is constructed for each first data point.

[0031] Optionally, the probability of fracture development is calculated based on the new instantaneous drilling time and gas logging anomaly index, including:

[0032] Determine whether the new instantaneous drilling time is greater than a preset first threshold;

[0033] If it is greater than that, the new instantaneous drilling time will be considered as suspected data;

[0034] The probability of crack development was calculated based on suspected data and gas anomaly index.

[0035] Optionally, determining the crack identification result at the current horizontal depth based on the crack development probability includes:

[0036] Determine the relationship between the crack development probability and a preset first threshold and a preset second threshold;

[0037] If the probability of fracture development is less than or equal to a preset first threshold, the fracture identification result at the current horizontal depth of the horizontal well is determined to be that there are no fractures.

[0038] If the probability of fracture development is greater than a preset first threshold and less than a preset second threshold, the fracture identification result at the current horizontal depth of the horizontal well is determined to be a suspected fracture.

[0039] If the probability of fracture development is greater than or equal to a preset second threshold, the fracture identification result at the current horizontal depth of the horizontal well is determined to be that fractures exist.

[0040] A second aspect of the present invention discloses a crack identification system, the system comprising:

[0041] The reading unit is used to read logging data of the horizontal well collected at preset sampling intervals during the horizontal well drilling process;

[0042] The processing unit is configured to process the recorded dataset to determine the mechanical specific energy and gas measurement anomaly index; normalize the processed recorded data, mechanical specific energy, and gas measurement anomaly index to obtain target data; calculate the first weight of the first data in the target data for the instantaneous drilling time, wherein the first data belongs to the target data and there are multiple first data; and perform depth elimination processing on the instantaneous drilling time based on the first data and the first weight to determine a new instantaneous drilling time.

[0043] The calculation unit is used to calculate the fracture development probability based on the new instantaneous drilling time and gas measurement anomaly index;

[0044] The identification unit is used to determine the crack identification result at the current horizontal depth based on the crack development probability.

[0045] A third aspect of the present invention discloses an electronic device for running a program, wherein the program executes a crack identification method as shown in the first aspect of the present invention.

[0046] A fourth aspect of the present invention discloses a storage medium comprising a stored program, wherein, when the program is executed, it controls the device on which the storage medium is located to perform a crack identification method as shown in the first aspect of the present invention.

[0047] Based on the above embodiments of the present invention, a fracture identification method, apparatus, electronic device, and storage medium are provided. The method includes: during horizontal well drilling, reading a logging dataset of the horizontal well collected at a preset sampling interval; processing the logging dataset to determine mechanical specific energy and gas anomaly index; normalizing the logging dataset, mechanical specific energy, and gas anomaly index to obtain target data; calculating a first weight of a first data point relative to the instantaneous drilling time in the target data, wherein the first data point belongs to the target data and there are multiple first data points; performing depth elimination processing on the instantaneous drilling time based on the first data point and the first weight to determine a new instantaneous drilling time; calculating a fracture development probability based on the new instantaneous drilling time and the gas anomaly index; and determining the fracture identification result at the current horizontal depth based on the fracture development probability, so as to provide an early warning based on the fracture identification result. In this embodiment of the invention, data logging data such as drill pressure, rotation speed, instantaneous drilling time, total hydrocarbons measured in gas, and gamma ray while drilling are collected from the start of sampling to the current depth i according to the sampling time. Then, mechanical energy specificity (MSE) and gas anomaly index are calculated based on the logging data. Then, the logging data, mechanical energy specificity (MSE), and gas anomaly index are normalized to determine the first weights of drill pressure, rotation speed, GR, and MSE with the instantaneous drilling time. Then, based on the first weights, the trend influence of drill pressure, rotation speed, GR, and MSE is removed from the instantaneous drilling time in the depth domain to obtain a new instantaneous drilling time. Finally, the instantaneous drilling time with the trend removed is processed with the gas anomaly index to identify the probability of fracture development, so as to accurately identify the development of fractures and vulnerabilities in the downhole formation. Attached Figure Description

[0048] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0049] Figure 1 This is a schematic flowchart illustrating a crack identification method according to an embodiment of the present invention;

[0050] Figure 2 This is a schematic diagram illustrating the process of processing logging data during drilling, as shown in an embodiment of the present invention.

[0051] Figure 3 This is an example diagram illustrating the normalization of logging dataset, MSE, and gas anomaly index according to an embodiment of the present invention;

[0052] Figure 4a This is a schematic diagram of the elliptic fitting result of drilling pressure and instantaneous drilling time shown in an embodiment of the present invention;

[0053] Figure 4b This is a schematic diagram of the elliptic fitting result between rotational speed and instantaneous drilling time, as shown in an embodiment of the present invention.

[0054] Figure 4c This is a schematic diagram illustrating the elliptical fitting result between gamma GR and instantaneous drilling, as shown in an embodiment of the present invention.

[0055] Figure 4d This is a schematic diagram showing the elliptic fitting results of mechanical specific energy (MSE) and instantaneous drilling time in an embodiment of the present invention;

[0056] Figure 5 This is an example diagram illustrating the probability of crack development in an embodiment of the present invention;

[0057] Figure 6 This is a schematic diagram of the structure of a crack identification device according to an embodiment of the present invention. Detailed Implementation

[0058] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0059] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a particular order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments described herein can be implemented in a sequence other than that illustrated or described herein. Furthermore, the terms “comprising” and “having,” and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0060] It should be noted that the descriptions involving "first," "second," etc., in this invention are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined with "first" or "second" may explicitly or implicitly include at least one of that feature. Furthermore, the technical solutions of the various embodiments can be combined with each other, but this must be based on the ability of those skilled in the art to implement them. If the combination of technical solutions is contradictory or impossible to implement, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection claimed by this invention.

[0061] In this application, the terms "comprising," "including," or any other variations thereof are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0062] As the background technology indicates, during horizontal well drilling, most locations where lost circulation (WS) occurs do not show large cracks or faults in seismic data. This suggests that WWS primarily occur at small-scale fractures, which seismic data, due to its insufficient resolution, cannot effectively identify. Furthermore, the real-time performance and resolution of methods such as pre-drilling modeling based on seismic data are insufficient to meet the demands of increasingly rapid drilling speeds, failing to provide early warning of encountered fractures and WWS.

[0063] Therefore, there is an urgent need to establish a new real-time fracture identification method to achieve early warning of fractures and well leakage, thereby accelerating and improving the efficiency of drilling projects.

[0064] See Figure 1The diagram below illustrates a crack identification method according to an embodiment of the present invention. The method includes:

[0065] Step S101: During the horizontal well drilling process, read the logging dataset of the horizontal well collected according to the preset sampling interval.

[0066] During the drilling process, a large amount of first-hand measurement and engineering data can be obtained while drilling. Therefore, sensors are installed at the drilling site to monitor drilling pressure, rotation speed, displacement, drilling fluid properties, drill bit type and usage, etc.

[0067] Therefore, in a certain well section, by combining cuttings logging or gamma-ray logging, the development of fractures and vulnerabilities in the downhole formation can be determined based on the drilling time.

[0068] Based on this, the present invention utilizes drilling data to establish a real-time identification method for horizontal well fractures, providing a basis for subsequent well leakage analysis and engineering decision-making.

[0069] It should be noted that the logging data includes drilling pressure (in kN), rotational speed (in r / min), instantaneous drilling time (in min / m), total hydrocarbons measured in gas (in %), and gamma-ray data while drilling.

[0070] It should be noted that the specific implementation process of step S101 includes the following steps:

[0071] Step S11: During horizontal well drilling, determine whether the current drilling status of the drilling equipment is normal. If yes, proceed to step S12; otherwise, continue the detection process and return to step S11.

[0072] In the specific implementation of step S11, the controller collects the current logging data of the drilling equipment while drilling, and determines whether the drilling pressure, rotation speed and standpipe pressure in the current logging data are all greater than 0. If so, the current drilling state is determined to be a normal drilling state, and the logging data is valid. Then, step S12 is executed. If any one or more of the drilling pressure, rotation speed and standpipe pressure are less than or equal to 0, it indicates that the current drilling state is an abnormal drilling state. Interference data from other states such as tripping out of the drill string are filtered out, the logging data is determined to be invalid, and the process returns to step S11.

[0073] The controller is located in the drilling equipment.

[0074] Step S12: Collect and record the dataset according to the preset sampling interval.

[0075] It should be noted that the logging dataset includes the logging dataset from the start of sampling to the current sampling interval, i.e., the logging dataset at the current well horizontal depth i.

[0076] The preset sampling intervals include the first sampling interval for data such as drilling pressure, rotary table speed, instantaneous drilling time, and total hydrocarbons measured in gas, and the second sampling interval for gamma ray while drilling.

[0077] Experiments have shown that the first sampling interval for drilling pressure, rotary table speed, instantaneous drilling time, and total hydrocarbons measured in gas logging data at depth is different from the second sampling interval for gamma-ray while drilling.

[0078] Generally speaking, the first sampling interval for drilling pressure, rotary table speed, instantaneous drilling time, and total hydrocarbons measured in gas is generally 0.03m, while the second sampling interval for gamma ray while drilling is generally 0.1m.

[0079] To facilitate subsequent data processing and calculations, a standardized data sampling interval is required. Therefore, the first sampling interval for drill pressure, rotation speed, drilling time, and total hydrocarbons is uniformly set to 0.1m per data point. Specifically, the second sampling interval determines the number of data collections required for the first sampling interval; that is, the quotient of the second sampling interval divided by the first sampling interval is the number of collections. Drill pressure, rotation speed, drilling time, and total hydrocarbons are collected at each of the first sampling intervals according to the number of collections. Then, the average values ​​of drill pressure, rotation speed, drilling time, and total hydrocarbons within the second sampling interval (i.e., the number of collections) are calculated. In other words, for data at the same well depth, the average value is taken; that is, the average value of drill pressure, rotation speed, drilling time, and total hydrocarbons is taken as the average value of each data point within the second sampling interval.

[0080] This ensures that drilling pressure, rotation speed, drilling time, and total hydrocarbon data are recorded at a unified sampling interval with the gamma-ray while drilling data.

[0081] Optionally, if there is a remainder when the second sampling interval is divided by the first sampling interval, the nearest neighbor KNN algorithm is used to fill in the missing value area, so that the data such as drilling pressure, rotation speed, drilling time, and total hydrocarbon extraction are more accurate and consistent with the data of gamma while drilling.

[0082] Step S13: Filter the recorded dataset to obtain a processed recorded dataset for reading.

[0083] In the specific implementation of step S13, the acquired measurement and recording dataset is cleaned and smoothed to remove outliers, resulting in a processed measurement and recording dataset that can be read and processed further.

[0084] It should be noted that data cleaning and smoothing can be performed using a low-pass filter.

[0085] It should be noted that the data in the measurement dataset is updated in real time based on the progress of the sampling time.

[0086] It should be noted that the specific implementation process of steps S11 to S13 can be illustrated using real-time integrated logging data from well X as an example. Figure 2 As shown.

[0087] Step S102: Process the recorded dataset to determine the mechanical specific energy and the gas measurement anomaly index.

[0088] It should be noted that the specific implementation process of step S102 includes the following steps:

[0089] Step S21: Process the drilling pressure, rotation speed, and drilling speed in the recorded data set, as well as the drill bit information of the drilling equipment, to obtain the mechanical specific energy. The drill bit information of the drilling equipment is obtained in advance.

[0090] It should be noted that the specific implementation process of step S21 includes:

[0091] Step S31: Obtain drill bit information from drilling equipment.

[0092] It should be noted that the drill bit information includes the drill bit area and the drill bit diameter;

[0093] In the specific implementation of step S21, the controller detects the area and diameter of the drill bit used by the drilling equipment in order to obtain the data.

[0094] Step S32: Based on the drill bit information, drilling pressure, rotation speed and drilling speed, calculate the mechanical specific energy (MSE).

[0095] In the specific implementation step S32, the drill bit area and drill bit diameter, as well as the drilling pressure, rotation speed and drilling speed in the processed measurement data are substituted into formula (1) for calculation to obtain the mechanical specific energy MSE.

[0096] Formula (1):

[0097]

[0098] Where MSE is mechanical specific energy, its unit is MPa; WOB is drilling pressure, its unit is kN; and Ab is drill bit area, its unit is mm. 2 N is the rotational speed, in r / min; ROP is the drilling speed, in m / h; Db is the drill bit diameter, in mm.

[0099] Step S22: Process the gas measurement total hydrocarbon data and the drilling information of the drilling equipment in the measurement and recording dataset to determine the gas measurement anomaly index, wherein the drilling information of the drilling equipment is acquired in real time.

[0100] In the specific implementation of step S22, the controller controls the logging instrument set on the drilling equipment to detect the current horizontal depth and obtain the drilling information of the drilling equipment;

[0101] Since this application uses gas measurement anomalies to represent the degree of gas measurement anomalies, generally speaking, when a horizontal section of the well encounters a fracture, the gas measurement value will increase abnormally. In order to quantitatively describe the degree of anomaly, a gas measurement anomaly index λ is used for quantification. Based on this, the current horizontal depth in the drilling information and the gas measurement total hydrocarbons at the current horizontal depth in the processed logging data are substituted into formula (2) for processing to obtain the gas measurement anomaly index.

[0102] Formula (2):

[0103]

[0104] Where i is the current horizontal depth, λ i Let x be the gas anomaly index at depth i, where x is the gas anomaly index. i The gas measurement value at depth i is the total hydrocarbon measurement value.

[0105] Step S103: Normalize the measured dataset, mechanical specific energy, and gas measurement anomaly index respectively to obtain the target data.

[0106] The target data includes each recorded data after normalization, namely, drilling pressure, rotary table speed, instantaneous drilling time and gamma retrieval while drilling, normalized mechanical specific energy, and normalized gas measurement anomaly index.

[0107] In the specific implementation of step S103, in order to eliminate the dimensional differences of each drilling parameter and avoid possible weight imbalance, the processed drilling pressure, rotation speed (i.e., rotary table speed), drilling time (i.e., instantaneous drilling time), gamma, MSE and gas logging anomaly index need to be input into formula (3) for normalization to obtain the target data.

[0108] Formula (3):

[0109]

[0110] Where, if the drilling pressure is normalized, x represents the drilling pressure, i represents the drilling depth, and x... min It refers to the minimum drill pressure at any drilled depth i, x max It refers to the maximum drilling pressure at any depth i.

[0111] x can also be data such as rotational speed, drilling time, gamma, MSE, and gas measurement anomaly index. min It refers to the minimum value of the data that has been drilled to any depth i, x max It refers to the maximum value of the data that has been drilled to any depth i.

[0112] It should be noted that the specific implementation process of step S103 can be illustrated using the real-time integrated logging data of well X, the MSE and the normalized results of the gas logging anomaly index as an example. Figure 3 As shown.

[0113] Step S104: Calculate the first weight of the first data in relation to the instantaneous drilling time in the target data.

[0114] The first data belongs to the target data, and there are multiple first data; the first data includes the drilling pressure, rotation speed, GR and MSE in the target data.

[0115] In the specific implementation of step S104, based on the target data, correlation analysis is performed on instantaneous drilling time and drilling pressure, instantaneous drilling time and rotation speed, instantaneous drilling time and GR, and instantaneous drilling time and MSE respectively to obtain the weights of the influence of drilling pressure, rotation speed, GR and MSE on instantaneous drilling time, namely the first weight.

[0116] Among them, GR and MSE represent lithological influences.

[0117] The first weights of drilling pressure, rotational speed, GR, and MSE on instantaneous drilling time shown in this invention represent the weights of their respective parameters on drilling time.

[0118] The applicant found that, generally speaking, drilling time is affected by rotation speed, drilling pressure, lithology, and fracture development. The faster the drilling speed, the greater the drilling pressure, the better the rock drillability, and the shorter the drilling time. If the effects of rotation speed, drilling pressure, and lithology are eliminated, the relationship between fracture development and drilling time can be theoretically obtained. Theoretically, the change in drilling time can represent the fracture development. In order to prevent the influence of rotation speed, drilling pressure, and lithology on drilling time, it is necessary to eliminate the influence of rotation speed, drilling pressure, and lithology on drilling time.

[0119] Therefore, this application uses correlation analysis of rotation speed, drilling pressure, lithology and drilling time to determine the relationship between fracture development and drilling time; at this time, the magnitude of the drilling time can represent the fracture development.

[0120] Correlation analysis refers to the analysis of two or more correlated variables to measure the degree of correlation between the two variables.

[0121] Next, step S104 determines the correlation between various parameters such as rotation speed, drilling pressure, and lithology and drilling time, i.e., their weights, thereby eliminating the influence of each parameter on drilling time and obtaining a new drilling time. This new drilling time is then processed with the gas logging anomaly index to identify the probability of fracture development, so as to accurately identify the development of fractures and cavities in the downhole formation.

[0122] It should be noted that the specific implementation process of step S104 includes the following steps:

[0123] Step S41: Draw the intersection diagram of the instantaneous drilling time in the target data with each first data point.

[0124] In the specific implementation of step S41, cross plots are drawn for instantaneous drilling time and drilling pressure, instantaneous drilling time and rotation speed, instantaneous drilling time and GR, and instantaneous drilling time and MSE, respectively. That is, instantaneous drilling time is used as the Y-axis, and drilling pressure, rotation speed, GR and MSE are used as the X-axis, respectively, and corresponding cross plots are drawn.

[0125] It should be noted that the stronger the correlation between instantaneous drilling time and drilling pressure, instantaneous drilling time and rotational speed, instantaneous drilling time and GR, or instantaneous drilling time and MSE, the more concentrated the scatter points of the cross plot will be, and the smaller the scatter point distribution area will be.

[0126] Step S42: For the intersection plot of the instantaneous drilling time and each first data point, perform fitting based on the intersection plot to obtain the ellipse fitting result;

[0127] It should be noted that the ellipse fitting results include the ellipse fitting results of instantaneous drilling time and drilling pressure, instantaneous drilling time and rotational speed, instantaneous drilling time and GR, and instantaneous drilling time and MSE.

[0128] The specific implementation of step S42 includes the following steps:

[0129] Step S51: For the intersection diagram of the instantaneous drilling time and each first data point, calculate the coordinates of the ellipse center based on the data in the intersection diagram.

[0130] The data in the cross plot includes a first data point, such as drill pressure, rotation speed, GR or MSE, and instantaneous drill time.

[0131] In the specific implementation step S51, n instantaneous drilling times x in the first data are input into formula (4) for calculation to obtain the first endpoint. A first data, such as drilling pressure, rotation speed, GR or MSE, is input into formula (5) for calculation to obtain the second endpoint of each first data.

[0132] Next, the first endpoint Second endpoint As the coordinates of the center of the ellipse

[0133] Formula (4):

[0134]

[0135] Formula (5):

[0136]

[0137] Where n is the number of data points in the first set of data, x q Let y be the x-coordinate of the q-th point on the intersection graph. q Let q be the ordinate of the point q on the intersection graph.

[0138] Step S52: Calculate the translation coordinates based on the coordinates of the ellipse center and the intersection diagram.

[0139] In the specific implementation step S52, the first endpoint X in the coordinates of the ellipse center and the drilling time x at a certain instant are... q Enter formula (6) to calculate and obtain the translated x′. q The second endpoint in the coordinates of the ellipse center And a first data y q For example, drilling pressure, rotation speed, GR or MSE can be input into formula (7) for calculation to obtain the translated ordinate y′. q Next, combine the translated x-coordinate and the translated y-coordinate to obtain the translated coordinates (x′) of point q. q y′ q ).

[0140] Formula (6):

[0141]

[0142] Formula (7):

[0143]

[0144] Where q can be a number from 1 to n, and n is the drilling pressure, rotation speed, instantaneous drilling time, GR or MSE collected from the start of sampling to the current sampling time.

[0145] Step S53: Calculate the azimuth angle, major axis length, and minor axis length of the ellipse based on the translation coordinates.

[0146] In the specific implementation step S53, the translation coordinates are substituted into formula (8) for calculation to obtain the ellipse azimuth angle θ. Then, the translation coordinates and the ellipse azimuth angle θ are substituted into formula (9) for calculation to obtain the length σ of the ellipse major axis. x Substituting the translation coordinates and the ellipse azimuth into formula (10) for calculation, the length of the minor axis σ of the ellipse is obtained. y ;

[0147] Formula (8):

[0148]

[0149] Formula (9):

[0150]

[0151] Formula (10):

[0152]

[0153] Step S54: Based on the ellipse center coordinates, ellipse azimuth angle, ellipse major axis length, and ellipse minor axis length, construct the ellipse fitting result corresponding to each first data point.

[0154] It should be noted that the ellipse fitting results corresponding to each first data point can be obtained through the process of steps S51 to S54.

[0155] The ellipse fitting results include the virtual ellipse, the coordinates of the ellipse center, the ellipse azimuth angle, the length of the ellipse major axis, and the length of the ellipse minor axis.

[0156] It should be noted that the specific implementation process of steps S51 to S54 can be illustrated using the X well drilling pressure versus the instantaneous drilling time ellipse fitting result as an example. Figure 4a As shown; the example of fitting the instantaneous drilling time ellipse to the X-well rotation speed is illustrated below. Figure 4b As shown; the example of fitting the instantaneous drilling ellipse to the X-well gamma GR is illustrated below. Figure 4c As shown; the example of fitting the instantaneous drilling ellipse using the MSE of well X is illustrated below. Figure 4d As shown.

[0157] In other words, through the above steps, we can obtain multiple k-σ fitting ellipses for drilling pressure versus instantaneous drilling time, rotational speed versus instantaneous drilling time, GR versus instantaneous drilling time, and MSE versus instantaneous drilling time, where k takes integer values ​​from 1 to 3. If the ellipse is required to cover relatively concentrated data, k = 1 can be used; if the ellipse is required to cover most of the data, k = 3 can be used.

[0158] It should be noted that the value of K can be set according to the actual situation.

[0159] Step S43: For each ellipse fitting result, process the ellipse fitting result and the corresponding intersection plot to obtain the corresponding average fitting degree.

[0160] In the specific implementation of step S43, for each ellipse fitting result, such as the ellipse fitting result of instantaneous drilling time and drilling pressure, the number of data points s of instantaneous drilling time and drilling pressure in the ellipse fitting result is calculated. i And the total number of data points S for instantaneous drilling time and drilling pressure in the cross plot. i Substitute the values ​​into formula (11) to calculate the average goodness of fit corresponding to the drilling pressure. Similarly, calculate the average goodness of fit corresponding to the rotational speed, GR, and MSE in the same way as above.

[0161] Formula (11):

[0162]

[0163] Among them, s i S represents the number of data points in the ellipse. i This represents the total number of data points.

[0164] Step S44: Calculate the first weight of each first data point relative to the instantaneous drilling time based on the average fitting degree and the ellipse fitting result.

[0165] In the specific implementation of step S44, for the average fitting degree corresponding to the drilling pressure, the length of the major axis and the length of the minor axis of the ellipse corresponding to the drilling pressure are substituted into formula (12) for calculation to obtain the first weight corresponding to the drilling pressure, that is, the weight of the influence of the drilling pressure on the instantaneous drilling time. Then, for the average fitting degree corresponding to the rotation speed, GR and MSE respectively, they are substituted into formula (12) for processing to obtain the first weight of the drilling pressure, rotation speed, GR and MSE on the instantaneous drilling time.

[0166] Formula (12):

[0167]

[0168] Using steps S41 to S44, calculate the average goodness of fit (i.e., correlation coefficient) of drilling pressure, rotation speed, and lithology (gamma, MSE) to instantaneous drilling time, and the weights of the influence of drilling pressure, rotation speed, GR, and MSE on drilling time. Taking well X as an example, the average goodness of fit of each parameter is obtained as follows: The weight is: ω 钻压 =0.38, ω 转速 =0.22, ω GR =0.47, ω MSE =0.64.

[0169] Step S105: Perform depth elimination processing on the instantaneous drilling time based on the first data and the first weight to determine a new instantaneous drilling time.

[0170] In the specific implementation step S105, the first weight of drilling pressure on instantaneous drilling time, the first weight of drilling speed on instantaneous drilling time, the first weight of GR on instantaneous drilling time, and the first weight of MSE on instantaneous drilling time are substituted into formula (13) for processing to eliminate the influence of drilling pressure, drilling speed, GR and MSE on instantaneous drilling time and obtain the detrended instantaneous drilling time.

[0171] Formula (13):

[0172]

[0173] in, The result after detrending during instantaneous drilling at depth i. For the instantaneous drilling time at depth i after homogenization, ω j The weight of j is the drilling pressure, drilling speed, GR, or MSE. The values ​​of drilling pressure, drilling speed, GR, or MSE at depth i after homogenization.

[0174] In other words, first calculate the drilling pressure. and its corresponding weight ω j The product of the two factors is used to calculate the drilling speed. and its corresponding weight ω j The product of , calculate GR and its corresponding weight ω j Calculate the product of . and its corresponding weight ω j The product of the above drilling pressure, drilling speed, GR, and MSE is then summed to obtain the cumulative result, and then the instantaneous drilling time is used. The difference between the instantaneous drilling time and the cumulative result of one-quarter is used to calculate the detrended result of the instantaneous drilling time at depth i, i.e., the new instantaneous drilling time, in order to eliminate the influence of drilling rate, GR and MSE on the instantaneous drilling time in the depth sequence.

[0175] Step S106: Calculate the fracture development probability based on the new instantaneous drilling time and gas measurement anomaly index.

[0176] It should be noted that the specific implementation process of step S106 includes the following steps:

[0177] Step S61: Determine whether the new instantaneous drilling time is greater than the preset first threshold. If it is greater, proceed to step S62. If it is less than or equal to, determine that there are no fractures in the current well horizontal section.

[0178] In the specific implementation of step S61, the new instantaneous drilling time is compared with the preset first threshold. If the new instantaneous drilling time is greater than the preset first threshold, step S62 is executed. If the new instantaneous drilling time is less than or equal to the preset first threshold, it is determined that there are no fractures in the current well horizontal section, and the result is output.

[0179] It should be noted that the preset first threshold was set through multiple experiments and can generally be set to 0.

[0180] Step S62: Use the new instantaneous drilling time as suspected data;

[0181] In the specific implementation of step S62, it is explained that a new instantaneous drilling time greater than a preset first threshold may affect crack development, and this is taken as suspected data.

[0182] The process based on steps S61 and S62 can be explained by the following formula (14).

[0183] Formula (14):

[0184]

[0185] Among them, when the new instantaneous drilling time When the value is less than or equal to 0, the value of its suspected data is 0. When a new instantaneous drilling time is reached... When the value is greater than 0, the value of its suspected data is... Therefore F i When the value is less than 0, it is meaningless, meaning the result after detrending at depth i to j is not considered. Cases less than or equal to 0.

[0186] Step S63: Calculate the probability of crack development based on the suspected data and the gas anomaly index.

[0187] In the specific implementation step S63, suspected data With the gas measurement anomaly index λ i Substituting into formula (15) for calculation, the probability of crack development F is obtained. i .

[0188] Formula (15):

[0189]

[0190] Step S107: Determine the crack identification result at the current horizontal depth based on the crack development probability, so as to provide early warning based on the crack identification result.

[0191] The crack identification results include: cracks exist, cracks do not exist, and suspected cracks.

[0192] It should be noted that the specific implementation process of step S107 includes the following steps:

[0193] Step S71: Determine the relationship between the crack development probability and the preset first threshold and the preset second threshold. If the crack development probability is less than or equal to the preset first threshold, proceed to step S72. If the crack development probability is greater than the preset first threshold and less than the preset second threshold, proceed to step S73. If the crack development probability is greater than or equal to the preset second threshold, proceed to step S74.

[0194] It should be noted that the preset second threshold was set after multiple experiments and is greater than the preset first threshold. It can generally be set to 1.

[0195] In the specific implementation step S71, the crack development probability Fi Substitute into formula (16) to determine the relationship between the crack development probability and the preset first threshold and the preset second threshold. If the crack development probability is less than or equal to the preset first threshold, then execute step S72. If the crack development probability is greater than the preset first threshold and less than the preset second threshold, then execute step S73. If the crack development probability is greater than or equal to the preset second threshold, then execute step S74.

[0196] A value greater than 1 indicates the presence of a crack. Therefore, the results are truncated, with values ​​less than 0 and greater than 1 assigned the values ​​0 and 1 respectively.

[0197] Formula (16):

[0198]

[0199] Step S72: Determine that the fracture identification result at the current horizontal depth of the horizontal well is that there are no fractures.

[0200] Step S73: Determine that the fracture identification result at the current horizontal depth of the horizontal well is a suspected fracture.

[0201] In the specific implementation of step S73, if the crack development probability F i The closer the value is to 1, the greater the probability of fracture-induced well leakage.

[0202] Step S73: Determine that the fracture identification result at the current horizontal depth of the horizontal well is that fractures exist.

[0203] Taking well X as an example, the above calculations yielded the final probability of fracture development in the horizontal section of the well during drilling. Figure 5 As shown below.

[0204] Figure 5 The diagram shows the probability of fracture development in well X, which identifies six fractured well sections at 4690-4692m, 4713-4717m, 4879-4882m, 4894-4901m, 4924-4927m, and 4943-4951m.

[0205] During the construction process, a fractured well leakage occurred at 4880.9m, resulting in a loss of 8.6m3, which verified the feasibility and effectiveness of the prediction method and data.

[0206] In this embodiment of the invention, data sets including drill pressure, rotation speed, instantaneous drilling time, total hydrocarbons measured during gas flow, and gamma ray while drilling (GR) are collected from the start of sampling to the current depth i according to the sampling time. Then, mechanical energy specificity (MSE) and gas flow anomaly index are calculated based on the data. Next, the drill pressure, rotation speed, instantaneous drilling time, total hydrocarbons measured during gas flow, GR, mechanical energy specificity (MSE), and gas flow anomaly index are normalized to determine the average fit and weight relationship between instantaneous drilling time and drill pressure, rotation speed, GR, and MSE, respectively. Then, based on the weights, the trend influence of drill pressure, rotation speed, GR, and MSE is removed from the instantaneous drilling time in the depth domain to obtain a new instantaneous drilling time. Finally, the instantaneous drilling time with the trend removed is processed with the gas flow anomaly index to identify the probability of fracture development, so as to accurately identify the development of fractures and vulnerabilities in the downhole formation.

[0207] Based on the crack identification method shown in the above embodiments of the present invention, correspondingly, the present invention also shows a crack identification device, such as... Figure 6 As shown, the device includes:

[0208] The reading unit 601 is used to read the logging data of the horizontal well collected at a preset sampling interval during the horizontal well drilling process;

[0209] Processing unit 602 is configured to process the recorded dataset to determine the mechanical specific energy and gas measurement anomaly index; normalize the processed recorded data, mechanical specific energy, and gas measurement anomaly index to obtain target data; calculate the first weight of the first data in the target data for the instantaneous drilling time, wherein the first data belongs to the target data and there are multiple first data; and perform depth elimination processing on the instantaneous drilling time based on the first data and the first weight to determine a new instantaneous drilling time.

[0210] Calculation unit 603 is used to calculate the probability of fracture development based on the new instantaneous drilling time and gas measurement anomaly index;

[0211] The identification unit 604 is used to determine the crack identification result of the current horizontal depth based on the crack development probability.

[0212] The specific principles and execution processes of each unit in the crack identification device disclosed in the above embodiments of the present invention are the same as the corresponding contents in the crack identification method provided in the above embodiments of the present invention. Please refer to the corresponding parts in the crack identification method disclosed in the above embodiments of the present invention, and they will not be repeated here.

[0213] In this embodiment of the invention, a logging dataset from the start of sampling to the current depth i is collected according to the sampling time. Then, the mechanical specific energy (MSE) and gas anomaly index are calculated based on the logging data. Then, data normalization processing is performed to determine the average fit and weight relationship between instantaneous drilling time and drilling pressure, rotation speed, GR, and MSE. Then, according to the weight relationship, in the depth domain, the trend influence of drilling pressure, rotation speed, GR, and MSE is removed from the instantaneous drilling time to obtain a new instantaneous drilling time. Finally, the instantaneous drilling time with the trend removed is processed with the gas anomaly index to identify the probability of fracture development, so as to accurately identify the development of fractures and cavities in the downhole formation.

[0214] Optionally, based on the apparatus shown in the above embodiments of the present invention, the reading unit 601 is specifically used for:

[0215] During horizontal well drilling, determine whether the current drilling status of the drilling equipment is a normal drilling status;

[0216] If so, collect and record the dataset according to the preset sampling interval;

[0217] The recorded dataset is filtered to obtain the processed recorded dataset.

[0218] Optionally, based on the apparatus shown in the above embodiments of the present invention, the processing unit 602, which processes the recorded dataset to determine the mechanical specific energy and the gas measurement anomaly index, is specifically used for:

[0219] The mechanical specific energy is obtained by processing the drilling pressure, rotational speed, and drilling speed data, as well as the drill bit information of the drilling equipment, in the aforementioned dataset. The drill bit information of the drilling equipment is obtained in advance.

[0220] The gas measurement anomaly index is determined by processing the total hydrocarbon data from the recorded dataset and the drilling information of the drilling equipment, wherein the drilling information of the drilling equipment is acquired in real time.

[0221] Optionally, based on the apparatus shown in the above embodiments of the present invention, the processing unit 602, which calculates the first weight of the first data on the instantaneous drilling time in the target data, is specifically used for:

[0222] Draw intersection diagrams between the instantaneous drilling time in the target data and each first data point;

[0223] For the intersection plot of the instantaneous drilling time and each first data point, an ellipse fitting result is obtained based on the intersection plot;

[0224] For each ellipse fitting result, the ellipse fitting result and the corresponding intersection plot are processed to obtain the corresponding average fitting degree.

[0225] Based on the average fitting degree and the ellipse fitting result, calculate the first weight of each first data point for the instantaneous drilling time.

[0226] Specifically, for the intersection plot of the instantaneous drilling time and each first data point, an ellipse fitting result is obtained based on the intersection plot, including:

[0227] For the intersection plot of the instantaneous drilling time and each first data point, the coordinates of the ellipse center are calculated based on the data in the intersection plot.

[0228] Calculate the translation coordinates based on the coordinates of the ellipse center and the intersection diagram;

[0229] The azimuth angle, major axis length, and minor axis length of the ellipse are calculated based on the translation coordinates.

[0230] Based on the ellipse center coordinates, ellipse azimuth angle, ellipse major axis length, and ellipse minor axis length, an ellipse fitting result is constructed for each first data point.

[0231] Optionally, based on the apparatus shown in the above embodiments of the present invention, the computing unit 603 is specifically used for:

[0232] Determine whether the new instantaneous drilling time is greater than a preset first threshold;

[0233] If it is greater than that, the new instantaneous drilling time will be considered as suspected data;

[0234] The probability of crack development was calculated based on suspected data and gas anomaly index.

[0235] Optionally, based on the apparatus shown in the above embodiments of the present invention, the identification unit 604 is specifically used for:

[0236] Determine the relationship between the crack development probability and a preset first threshold and a preset second threshold;

[0237] If the probability of fracture development is less than or equal to a preset first threshold, the fracture identification result at the current horizontal depth of the horizontal well is determined to be that there are no fractures.

[0238] If the probability of fracture development is greater than a preset first threshold and less than a preset second threshold, the fracture identification result at the current horizontal depth of the horizontal well is determined to be a suspected fracture.

[0239] If the probability of fracture development is greater than or equal to a preset second threshold, the fracture identification result at the current horizontal depth of the horizontal well is determined to be that fractures exist.

[0240] This application provides an electronic device, which includes a processor and a memory. The memory contains program code and data for crack identification, and the processor is used to call program instructions in the memory to execute the steps shown in the crack identification method in the above embodiments.

[0241] This application provides a storage medium including a stored program, wherein, when the program runs, it controls the device where the storage medium is located to execute the crack identification method shown in the above embodiments.

[0242] Furthermore, the electronic devices or storage media shown above are often installed in drilling equipment.

[0243] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, for system or system embodiments, since they are basically similar to method embodiments, the description is relatively simple, and relevant parts can be referred to the descriptions in the method embodiments. The systems and system embodiments described above are merely illustrative. 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 modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without creative effort.

[0244] Those skilled in the art will further recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0245] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A crack identification method, characterized in that, The method includes: During horizontal well drilling, the logging dataset of the horizontal well is read according to a preset sampling interval; Based on the recorded dataset, mechanical specific energy and gas measurement anomaly index are determined. The recorded dataset, mechanical specific energy, and gas measurement anomaly index were normalized respectively to obtain the target data. Calculate the first weight of the first data in relation to the instantaneous drilling time in the target data, wherein the first data belongs to the target data and there are multiple first data; Based on the first data and the first weight, the instantaneous drilling time is subjected to depth elimination processing to determine a new instantaneous drilling time; The probability of fracture development is calculated based on the new instantaneous drilling time and gas measurement anomaly index. The crack development probability is used to determine the crack identification result at the current horizontal depth, so that subsequent early warnings can be issued based on the crack identification result.

2. The method according to claim 1, characterized in that, Read logging data from horizontal wells collected at preset sampling intervals, including: During horizontal well drilling, determine whether the current drilling status of the drilling equipment is a normal drilling status; If so, collect and record the dataset according to the preset sampling interval; The recorded dataset is filtered to obtain the processed recorded dataset.

3. The method according to claim 1, characterized in that, Based on the recorded dataset, the mechanical specific energy and gas measurement anomaly index are determined, including: The mechanical specific energy is obtained by processing the drilling pressure, rotational speed, and drilling speed data, as well as the drill bit information of the drilling equipment, in the aforementioned dataset. The drill bit information of the drilling equipment is obtained in advance. The gas measurement anomaly index is determined by processing the total hydrocarbon data from the recorded dataset and the drilling information of the drilling equipment, wherein the drilling information of the drilling equipment is acquired in real time.

4. The method according to claim 1, characterized in that, Calculating the first weight of the first data with respect to the instantaneous drilling time in the target data includes: Draw intersection diagrams between the instantaneous drilling time in the target data and each first data point; For the intersection plot of the instantaneous drilling time and each first data point, an ellipse fitting result is obtained based on the intersection plot; For each ellipse fitting result, the ellipse fitting result and the corresponding intersection plot are processed to obtain the corresponding average fitting degree. Based on the average fitting degree and the ellipse fitting result, calculate the first weight of each first data point for the instantaneous drilling time.

5. The method according to claim 4, characterized in that, For the intersection plot of the instantaneous drilling time and each first data point, an ellipse fitting result is obtained based on the intersection plot, including: For the intersection plot of the instantaneous drilling time and each first data point, the coordinates of the ellipse center are calculated based on the data in the intersection plot. Calculate the translation coordinates based on the coordinates of the ellipse center and the intersection diagram; The azimuth angle, major axis length, and minor axis length of the ellipse are calculated based on the translation coordinates. Based on the ellipse center coordinates, ellipse azimuth angle, ellipse major axis length, and ellipse minor axis length, an ellipse fitting result is constructed for each first data point.

6. The method according to claim 1, characterized in that, The probability of fracture development is calculated based on the new instantaneous drilling time and gas logging anomaly index, including: Determine whether the new instantaneous drilling time is greater than a preset first threshold; If it is greater than that, the new instantaneous drilling time will be considered as suspected data; The probability of crack development was calculated based on suspected data and gas anomaly index.

7. The method according to claim 1, characterized in that, The crack identification result based on the crack development probability at the current horizontal depth includes: Determine the relationship between the crack development probability and a preset first threshold and a preset second threshold; If the probability of fracture development is less than or equal to a preset first threshold, the fracture identification result at the current horizontal depth of the horizontal well is determined to be that there are no fractures. If the probability of fracture development is greater than a preset first threshold and less than a preset second threshold, the fracture identification result at the current horizontal depth of the horizontal well is determined to be a suspected fracture. If the probability of fracture development is greater than or equal to a preset second threshold, the fracture identification result at the current horizontal depth of the horizontal well is determined to be that fractures exist.

8. A crack detection device, characterized in that, The device includes: The reading unit is used to read logging data of the horizontal well collected at preset sampling intervals during the horizontal well drilling process; The processing unit is configured to process the recorded dataset to determine the mechanical specific energy and gas measurement anomaly index; normalize the processed recorded data, mechanical specific energy, and gas measurement anomaly index to obtain target data; calculate the first weight of the first data in the target data for the instantaneous drilling time, wherein the first data belongs to the target data and there are multiple first data; and perform depth elimination processing on the instantaneous drilling time based on the first data and the first weight to determine a new instantaneous drilling time. The calculation unit is used to calculate the fracture development probability based on the new instantaneous drilling time and gas measurement anomaly index; The identification unit is used to determine the crack identification result at the current horizontal depth based on the crack development probability.

9. An electronic device, characterized in that, The electronic device is used to run a program, wherein the program executes the crack identification method as described in any one of claims 1-7.

10. A storage medium, characterized in that, The storage medium includes a stored program, wherein, when the program is executed, it controls the device where the storage medium is located to perform the crack identification method as described in any one of claims 1-7.

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