Method and device for determining the relationship between a trajectory and a reservoir based on entry and exit layer feature recognition

Abstract

A trajectory and reservoir relationship determination method and device based on entry and exit layer feature recognition, the method comprising: classifying and counting basic data according to angle difference values to obtain a first feature set; simulating a drill bit entering and exiting a layer by using a geological model to obtain drilling parameters at the entry and exit layer time, and performing regression calibration processing on the measurement-while-drilling and logging data corresponding to the entry and exit layer time to obtain a second feature set; performing model correction processing on the geological model by using the first feature set and the second feature set; simulating the drill bit entering and exiting the top and bottom of the target layer at different angle differences by using the corrected geological model to obtain drilling parameters, logging-while-drilling and logging data, and performing logging-while-drilling and logging data conversion calibration processing to obtain a third feature set; obtaining measured data, and performing trajectory adjustment processing on the measured data by using the third feature set to complete trajectory optimization. The present application performs trajectory optimization adjustment in advance, improves the reservoir drilling effect, and has a broad application prospect.

Description

Technical Field

[0001] This invention relates to the field of drilling exploration technology, and more particularly to a method and apparatus for determining the relationship between a trajectory and a reservoir based on the identification of entry and exit layer characteristics. Background Technology

[0002] As oil and gas exploration continues to expand into unconventional areas, horizontal wells have become one of the important technical means for exploring unconventional oil and gas reservoirs. Faced with thinner reservoirs and stronger heterogeneity, the complex geological conditions, the significant impact of trajectory entry angle difference on the expression of logging-while-drilling curve characteristics, the differences in experience of field steering engineers, and the greater difficulty in identifying unconventional reservoir boundaries all pose huge challenges to unconventional oil and gas horizontal well drilling. In order to more efficiently determine the relationship between well trajectory and reservoir location, improve trajectory adjustment efficiency, and achieve the goal of high reservoir encounter rate, it has become a need to develop a trajectory-reservoir relationship discrimination method based on entry feature identification.

[0003] In summary, quickly identifying the spatial relationship between the trajectory and the reservoir, and mitigating the impact of differences in the experience of on-site steering engineers, are key issues for early trajectory control and improving reservoir encounter rates. Current research on steering trajectory control methods to address these issues is as follows:

[0004] Existing technologies disclose geological steering trajectory control methods for horizontal sections of continuously undulating reservoirs in shale gas horizontal wells. These methods involve setting markers at the undulation points at the top and bottom interfaces of the target layer, combining the entry and exit points to form an optimal trajectory control path, and obtaining the well inclination angles of the entry point and each segment to control the horizontal section of the continuously undulating reservoir. However, for thin reservoirs, the seismic resolution is limited, making it difficult to identify structural undulations, and abrupt formation changes occur frequently, making manual control extremely difficult. This method requires prior identification of structural undulation peaks and troughs, and both steering engineers and orientation engineers need to have good experience to achieve trajectory control, making it difficult to operate in practice.

[0005] Existing technologies disclose geological steering early warning methods, which obtain formation characteristic data, drill bit depth position, and steering early warning analysis data by acquiring a target formation depth model and logging-while-drilling curves. Based on the early warning analysis data and the characteristic data of the formation position in the formation depth model, it is determined whether geological steering early warning is needed. This method can perform geological steering trajectory control in areas with significant characteristic variations between homogeneous formations. However, in areas with thin layers, indistinct formation variation characteristics, and high drill bit encounter frequency, the response is slow due to the influence of measurement zero length, making identification difficult and timely trajectory adjustments challenging, significantly impacting reservoir encounter rates.

[0006] Existing technologies disclose integrated geological steering methods for horizontal wells. These methods involve establishing a detailed 3D geological model using geological, logging, well logging, and geophysical data before drilling, determining formation dip and reservoir properties to design a 3D well trajectory, and continuously refining the geological model during the directional drilling phase through logging while drilling to ensure accurate landing. During the horizontal drilling phase, logging while drilling, well logging, and seismic interpretation are combined to adjust the horizontal well trajectory. While this method describes the data and procedures used for steering trajectory control, it does not address methods for target point correction during the directional drilling phase, or for predicting and controlling the trajectory's position within the reservoir. In structurally variable sections or thin reservoirs, it cannot quickly provide trajectory pre-adjustment methods, making it difficult to achieve efficient reservoir drilling.

[0007] Existing technologies disclose a real-time gamma-ray forward modeling geological steering drilling method. This method combines a formation model with the actual drilled wellbore trajectory, forward models the gamma-ray curves and compares them with actual measurements. The formation model is decomposed based on the contact relationship between the gamma-ray logging detection range and the formation interface. Based on the attenuation law of gamma rays in the formation, the gamma-ray flux at the detector position for each region after model decomposition is analyzed and calculated separately, providing a basis for updating the formation model and adjusting the wellbore trajectory. This method uses gamma-ray curve comparison to determine the dip angle changes of segments in the geological model and gamma-ray energy attenuation to determine formation boundaries. However, because the gamma-ray measuring instrument is more than ten meters away from the drill bit, the determination of the drill bit's position in the reservoir is delayed. Furthermore, using only gamma-ray for reservoir boundary identification results in limited data, affecting identification efficiency and accuracy, and significantly impacting trajectory control and reservoir encounter rate.

[0008] Existing technologies disclose a rapid and precise geological steering method for shale gas horizontal wells. This method involves establishing two-dimensional and three-dimensional geological steering models of the well area, comparing the lithology, well inclination, and gamma-ray while drilling characteristics of the well to be steered with those of standard and reference wells, and employing three... Figure 1 The method determines the drill bit's location, evaluates whether it's within a high-quality shale gas formation while drilling, assesses the applicability of the initial geological model, uses the equal thickness comparison method to determine and adjust target point A, predicts target point B, and controls the wellbore trajectory in the horizontal section. While this method uses marker layer gamma curve comparison to assess the geological model and determines target locations and adjusts trajectories based on the equal thickness method, it can only determine target locations and guide the trajectory to hit the target. It cannot efficiently predict whether the trajectory will exit a formation, its position within the formation, or provide a method for pre-adjustment and optimization of the trajectory. Summary of the Invention

[0009] To address the problems existing in the prior art, the main objective of this invention is to provide a method and apparatus for determining the relationship between a trajectory and a reservoir based on entry feature recognition, thereby enabling advance trajectory optimization and improving reservoir drilling efficiency.

[0010] To achieve the above objectives, embodiments of the present invention provide a method for determining the relationship between a trajectory and a reservoir based on entry and exit layer feature recognition, the method comprising:

[0011] Obtain the basic data of the drilled wells in the target block, classify and statistically analyze the basic data according to the angle difference value, and obtain the first feature set when drill bit 5 encounters the top and bottom interfaces of the target layer;

[0012] Using a pre-established geological model, the drilling parameters at the entry and exit times of the drill bit are simulated to obtain drilling parameters at the entry and exit times. The measurement-while-drilling and logging data corresponding to the entry and exit times are then subjected to regression calibration to obtain a second feature set corresponding to the entry and exit times of the drill bit.

[0013] Using the first and second feature sets, the pre-established geological model is corrected; using the corrected geological model, the drill bit is simulated to enter and exit the top and bottom of the target layer at different angle differences, and drilling parameters, logging-while-drilling data, and logging data corresponding to the entry and exit times of the target layer are obtained. The drilling parameters corresponding to the entry and exit times of the target layer are then converted and calibrated using logging-while-drilling data to obtain the third feature set.

[0014] The actual drilling process is used to obtain measured data, and the third feature set is used to compare the measured data to perform trajectory adjustment processing in order to complete trajectory optimization.

[0015] 5. Optionally, in one embodiment of the present invention, the basic data is classified and statistically analyzed according to the angle difference value to obtain a first feature set when the drill bit encounters the top and bottom interfaces of the target layer, including:

[0016] Divide the basic data into layers and determine the range of angle difference between entering and exiting layers;

[0017] The range of angle difference between the entry and exit layers is divided into segments of a certain degree interval to obtain the first feature set when the drill bit encounters the top and bottom interfaces of the target layer in different angle difference segments; wherein, the first feature set consists of drilling parameters for entering and exiting the layer under the preset angle difference, logging parameters, logging parameters and logging parameters.

[0018] Optionally, in one embodiment of the present invention, the method further includes:

[0019] Obtain seismic and well completion logging data, and use the seismic and well completion logging data to establish the geological model.

[0020] Based on seismic and well logging data, determine the angle of entry into the formation when the trajectory lands;

[0021] 5. Determine the spatial relationship between the drill bit and the measuring instrument based on the orientation and measuring tools.

[0022] Optionally, in one embodiment of the present invention, the model correction process for the pre-established geological model using the first feature set and the second feature set includes:

[0023] By comparing the first feature set with the second feature set, the set comparison accuracy rate is obtained;

[0024] If the set comparison accuracy is not greater than the preset threshold, the pre-established geological model will be corrected.

[0025] This invention also provides a device for determining the relationship between a trajectory and a reservoir based on entry and exit layer feature recognition. The device includes:

[0026] The first feature set module is used to obtain the basic data of the drilled wells in the target block, classify and statistically analyze the basic data according to the angle difference value, and obtain the first feature set when the drill bit encounters the top and bottom interfaces of the target layer.

[0027] The second feature set module is used to simulate the entry and exit of the drill bit into and out of the formation using a pre-established geological model, obtain the drilling parameters at the entry and exit times, and perform regression calibration processing on the measurement while drilling and logging data corresponding to the entry and exit times to obtain the second feature set corresponding to the entry and exit times of the drill bit.

[0028] The model correction module is used to correct the pre-established geological model using the first feature set and the second feature set.

[0029] The third feature set module is used to simulate the time when the drill bit enters and exits the top and bottom of the target layer at different angle differences using the modified geological model, to obtain drilling parameters, logging while drilling and logging data corresponding to the time of entering and exiting the top and bottom of the target layer, and to perform logging while drilling and logging data conversion and calibration processing on the drilling parameters corresponding to the time of entering and exiting the top and bottom of the target layer to obtain the third feature set.

[0030] The trajectory optimization module is used to acquire measured data during the actual drilling process and use a third feature set to compare the measured data to perform trajectory adjustment processing in order to complete trajectory optimization.

[0031] Optionally, in one embodiment of the present invention, the first feature set module includes:

[0032] Angle difference range unit is used to divide the basic data into layers and determine the angle difference range of entering and exiting the layer;

[0033] The first feature set unit is used to segment the range of entry and exit angle difference into a certain degree interval to obtain the first feature set when the drill bit encounters the top and bottom interfaces of the target layer in different angle difference segments; wherein, the first feature set consists of drilling parameters, logging-while-drilling parameters, logging parameters and well logging parameters under the preset angle difference.

[0034] Optionally, in one embodiment of the present invention, the apparatus further includes:

[0035] The geological model module is used to acquire seismic and well completion logging data, and to establish the geological model using the seismic and well completion logging data;

[0036] The entry angle module is used to determine the entry angle of the trajectory when landing, based on seismic and well logging data.

[0037] The spatial relationship module is used to determine the spatial relationship between the drill bit and the measuring instrument based on the orientation and measuring tools.

[0038] Optionally, in one embodiment of the present invention, the model correction module includes:

[0039] The comparison matching rate unit is used to compare the first feature set with the second feature set to obtain the set comparison matching rate;

[0040] The model correction unit is used to correct the pre-established geological model if the set comparison accuracy is not greater than a preset threshold.

[0041] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the above-described method.

[0042] The present invention also provides a computer-readable storage medium storing a computer program for performing the above-described methods.

[0043] The present invention also provides a computer program product, including a computer program / instructions, which, when executed by a processor, implement the steps of the above-described method.

[0044] This invention can solve the problems of low identification efficiency after drilling thin reservoirs and heterogeneous reservoirs, slow trajectory adjustment cycle, and many invalid footage in horizontal sections. It has broad application prospects for guiding horizontal wells to optimize and adjust the trajectory in advance and improve the reservoir drilling effect. It is of great significance for realizing the efficient development of unconventional oil and gas resources. Attached Figure Description

[0045] 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 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.

[0046] Figure 1This is a flowchart of a method for determining the relationship between a trajectory and a reservoir based on entry and exit layer feature recognition, according to an embodiment of the present invention.

[0047] Figure 2 This is a flowchart illustrating the process of determining the feature set in an embodiment of the present invention;

[0048] Figure 3 This is a flowchart of establishing a geological model in an embodiment of the present invention;

[0049] Figure 4 This is a flowchart of the model correction process in an embodiment of the present invention;

[0050] Figure 5 This is a flowchart illustrating the determination of the relationship between the trajectory and the reservoir in a specific embodiment of the present invention;

[0051] Figure 6 This is a flowchart illustrating the establishment of a feature set when the drill bit encounters the top and bottom interfaces of the target layer in an embodiment of the present invention.

[0052] Figure 7 This is a flowchart illustrating the determination of the pre-drilling geological model, trajectory, and drill string assembly in an embodiment of the present invention.

[0053] Figure 8 This is a flowchart illustrating the establishment of calibration parameters for the interface feature set of the drilled layer in this embodiment of the invention.

[0054] Figure 9 This is a flowchart simulating drilling and measurement-while-drilling parameters under different angle differences in an embodiment of the present invention;

[0055] Figure 10 This is a flowchart of the simulation feature data combination accuracy judgment and actual drilling verification in an embodiment of the present invention;

[0056] Figure 11 This is a schematic diagram of a device for determining the relationship between a trajectory and a reservoir based on entry and exit layer feature recognition, according to an embodiment of the present invention.

[0057] Figure 12 This is a schematic diagram of the structure of the first feature set module in an embodiment of the present invention;

[0058] Figure 13 This is a schematic diagram of the structure of a trajectory and reservoir relationship determination device based on entry and exit layer feature recognition in another embodiment of the present invention;

[0059] Figure 14 This is a schematic diagram of the model correction module in an embodiment of the present invention;

[0060] Figure 15 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0061] This invention provides a method and apparatus for determining the relationship between a trajectory and a reservoir based on entry and exit layer feature recognition.

[0062] 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.

[0063] like Figure 1 The diagram shows a flowchart of a method for determining the relationship between a trajectory and a reservoir based on entry / exit layer feature recognition, according to an embodiment of the present invention. The execution subject of this method includes, but is not limited to, a computer. This invention can solve problems such as low identification efficiency after encountering a layer, slow trajectory adjustment cycle, and numerous invalid penetrations in horizontal sections during drilling in thin or heterogeneous reservoirs. It has broad application prospects for guiding horizontal wells to optimize and adjust their trajectories in advance, improving reservoir encounter effectiveness, and is of great significance for the efficient development of unconventional oil and gas resources. The method shown in the diagram includes:

[0064] Step S1: Obtain the basic data of the drilled wells in the target block, classify and statistically analyze the basic data according to the angle difference value, and obtain the first feature set when the drill bit encounters the top and bottom interfaces of the target layer.

[0065] Step S2: Use a pre-established geological model to simulate the entry and exit of the drill bit into and out of the formation, obtain the drilling parameters at the entry and exit times, and perform regression calibration on the measurement while drilling and logging data corresponding to the entry and exit times to obtain the second feature set corresponding to the entry and exit times of the drill bit.

[0066] Step S3: Use the first feature set and the second feature set to perform model correction processing on the pre-established geological model;

[0067] Step S4: Using the corrected geological model, simulate the time when the drill bit enters and exits the top and bottom of the target layer at different angle differences, obtain drilling parameters, logging while drilling and logging data corresponding to the time when entering and exiting the top and bottom of the target layer, and perform logging while drilling and logging data conversion and calibration processing on the drilling parameters corresponding to the time when entering and exiting the top and bottom of the target layer to obtain the third feature set.

[0068] Step S5: Obtain the measured data during the actual drilling process, and use the third feature set to compare the measured data to perform trajectory adjustment processing in order to complete trajectory optimization.

[0069] As one embodiment of the present invention, such as Figure 2As shown, the basic data are classified and statistically analyzed according to the angle difference value. The first feature set when the drill bit encounters the top and bottom interfaces of the target layer includes:

[0070] Step S21: Divide the basic data into layers and determine the range of angle difference between the ingress and egress layers;

[0071] Step S22: Divide the angle difference range of the entry and exit layers into segments of a certain degree interval to obtain the first feature set when the drill bit encounters the top and bottom interfaces of the target layer in different angle difference segments; wherein, the first feature set consists of drilling parameters, logging-while-drilling parameters, logging parameters and well logging parameters under the preset angle difference.

[0072] Specifically, the well trajectory is statistically analyzed to determine whether it enters or exits the target formation, and is classified into four types: top entry, top exit, bottom exit, and bottom entry. The angle difference between the trajectory and the formation dip angle is statistically analyzed for the four types of cases, and the range of the angle difference between the entry and exit formation is determined without encountering faults. The drilling parameters, logging parameters, and logging-while-drilling / quantitative parameters measured under the angle difference range of the four types of cases are used to establish a feature set with an angle difference interval of 0.5 degrees.

[0073] Among these methods, seismic and well logging data are used to establish a pre-drilling geological model to determine the drilling trajectory and drill string assembly parameters.

[0074] Specifically, as one embodiment of the present invention, such as Figure 3 As shown, the method also includes:

[0075] Step S31: Obtain seismic and well completion logging data, and use the seismic and well completion logging data to establish a geological model;

[0076] Step S32: Determine the angle of entry into the formation when the trajectory lands, based on seismic and well logging data.

[0077] Step S33: Determine the spatial relationship between the drill bit and the measuring instrument based on the orientation and measuring tools.

[0078] Based on the collected seismic and well logging data, a regional geological model is established, which includes properties such as fault fractures, formation dip angles, fine stratification of the target layer, gamma ray, and resistivity. The angular difference range of the formation to be cut into by the designed well trajectory is preliminarily determined. The length from the downhole measuring tool to the drill bit zero and the angle of the directional tool are determined to determine the actual drilling position of the drill bit and the measurement position.

[0079] Specifically, drilling speed is the fastest and most intuitive parameter, identifying changes in drilling velocity as the drill bit enters / exits the formation. Measurement-while-drilling (MWD) parameters are distinguishable parameters with distinct characteristics, identifying changes in formation properties as the measurement tool enters / exits the formation. Zero length and angular difference can be used to determine the drill bit's position after entering / exiting the formation. Gas logging and cuttings logging calculate the drill bit's rock-breaking position based on the delay time, recording the characteristics of the drill bit-formation spatial position. Using drilling speed as a standard, other characteristic responses are regressed to the drill bit's rock-breaking time series, reflecting the characteristics of the drill bit entering / exiting the target formation, and establishing a feature set.

[0080] Among them, the drilling trajectory and drill string assembly parameters are used to extract the features of the drilling-through layer interface, and the resulting set of features of the drilling-through layer interface is the second feature set.

[0081] Specifically, as one embodiment of the present invention, such as Figure 4 As shown, the model correction process for the pre-established geological model using the first feature set and the second feature set includes:

[0082] Step S41: Compare the first feature set with the second feature set to obtain the set comparison accuracy.

[0083] Step S42: If the set comparison accuracy rate is not greater than the preset threshold, then the pre-established geological model is corrected.

[0084] Among them, the drill bit working conditions are simulated numerically using the set of features of the drill-through layer interface to obtain simulated feature data.

[0085] Specifically, under the formation model, numerical simulation simulates the drilling speed of the drill bit entering / exiting the formation at different angle differences; based on the zero length of the drill bit and the measurement while drilling tool, the formation position of the measurement tool under different angle differences is determined, and formation property curves such as gamma and resistivity are simulated; after removing the influence of late arrival time, based on phase change and reservoir charging characteristics, the mean method is used to determine the gas logging and cuttings logging characteristic data, i.e., simulated characteristic data, and establish a third feature set.

[0086] Among them, actual drilling verification is carried out based on the third feature set to obtain the verification results, and the trajectory optimization is performed using the verification results.

[0087] Specifically, the third set of features, after the time and target layer location are aligned, serves as a criterion for determining the position of the drill bit in the target layer and its relationship with the top and bottom interfaces during drilling. This guides the advance adjustment of the trajectory and reduces invalid footage caused by the trajectory deviating from the layer.

[0088] In addition, the specific process of actual drilling verification includes: using drilling, geological logging and well logging data obtained under a certain angle difference during the actual drilling process, determining the current drill bit position, guiding the trajectory adjustment, and predicting the spatial position of the drill bit in the target layer after adjustment; predicting the feature data of the next drill bit drilling, supplementing the third feature set, and verifying it with the actual drilling simulation data to obtain the verification results; and achieving trajectory optimization control through two iterative steps.

[0089] To address the problems in existing technologies, this invention proposes a trajectory-reservoir relationship discrimination method based on entry feature identification. This method collects geological logging, well logging, and drilling characteristics of completed vertical and horizontal wells within the region that encounter the top and bottom interfaces of the target layer. Based on the differentiated angles at which the trajectory penetrates the top and bottom of the target layer, the characteristics of the encountered layer interfaces are classified and a data set is established. By establishing geological models of the target layer and its top and bottom formations, the drilling rate, gamma ray, resistivity, and gas logging characteristics of the top and bottom interfaces of the target layer are simulated under different angle differences between the formation and the well trajectory. A feature set database of drill bit-target layer interface intersections under different angle differences is established. By analyzing the combined features of measurements while drilling, the relationship between the drill bit and the reservoir boundary is determined, the trajectory adjustment direction is determined in advance, and the trajectory is effectively controlled within the reservoir, improving reservoir drilling efficiency.

[0090] This invention addresses the challenges of low efficiency in identifying reservoir layers after drilling in thin or heterogeneous reservoirs, slow trajectory adjustment cycles, and numerous ineffective shots in horizontal sections. It fully utilizes geological, logging, and drilling data recorded at the upper and lower interfaces of the encountered reservoir in already drilled wells to quickly determine the spatial relationship between the drill bit and the reservoir boundary. This invention has broad application prospects for guiding the early trajectory optimization and adjustment of horizontal wells, improving reservoir drilling effectiveness, and is of great significance for the efficient development of unconventional oil and gas resources.

[0091] This invention, based on the geological, logging, and drilling characteristics of the top and bottom interfaces of the target formation encountered in completed vertical and horizontal wells, classifies the cases of the trajectory penetrating the top and bottom of the target formation within a limited angle difference range and establishes corresponding feature sets. By simulating and establishing a feature set database under different angle differences, it solves the spatiotemporal delay effect between the recording of measurement-while-drilling data and the interface encountered by the drill bit, determines the relationship between the drill bit and the reservoir boundary, and determines the direction of trajectory adjustment in advance, thereby promoting the increase of the drilling rate of unconventional oil and gas reservoirs and achieving improved quality and efficiency in horizontal well drilling.

[0092] This invention pertains to drilling exploration and development technology, specifically relating to a method for determining the relationship between a drilling trajectory and a reservoir based on entry feature identification. The method involves establishing a set of combined features of the target layer and the top and bottom interfaces of the formation encountered by the well trajectory within a limited angular difference range, based on geological, logging, and drilling data from completed vertical and horizontal wells. By simulating and establishing a database of these feature sets under different angular differences, the method addresses the spatiotemporal delay effect between measurement-while-drilling data recording and the layer interfaces encountered by the drill bit. This multi-source data allows for efficient judgment of the formation interface conditions encountered by the drill bit, enabling early trajectory adjustment and prediction, and achieving a high drilling success rate for unconventional reservoirs.

[0093] In a specific embodiment of the present invention, such as Figure 5 The diagram shown is a flowchart of a trajectory and reservoir relationship discrimination method based on entry and exit layer feature recognition according to an exemplary embodiment of the present invention.

[0094] like Figure 5 As shown, based on the collected well trajectories, drilling parameters, bottom hole assembly, geological stratification, lithological description, measurement while drilling, and logging data of drilled vertical and horizontal wells, in step N100, a set of features is established using the drilled data to determine the top and bottom interfaces of the target layer when the drill bit encounters them, within a limited angular difference range between the formation and the well trajectory.

[0095] The following will combine Figure 6 The steps of the feature set partitioning method when a drill bit encounters the top and bottom interface of a target layer according to an exemplary embodiment of the present invention are described.

[0096] like Figure 6 As shown, in steps N110-N130, the drilling trajectory is statistically analyzed to determine whether it enters or exits the target layer, and is classified into four types: top entry, top exit, bottom exit, and bottom entry. The angle difference between the trajectory and the dip angle of the formation is statistically analyzed for the four types of cases, and the range of the angle difference between the entry and exit layers is determined without encountering faults. The drilling parameters, logging parameters, and logging-while-drilling / quantitative parameters measured under the angle difference range of the four types of cases are used to establish a feature set with an angle difference interval of 0.5 degrees.

[0097] like Figure 5 As shown, in step N200, a pre-drilling geological model of the pre-drilled well is established, and the drilling trajectory and drill string assembly parameters are determined in combination with the drilling design and actual drilling conditions. The usage of each parameter is also explained.

[0098] The following will combine Figure 7 This describes the steps of the pre-drilling geological model and trajectory, drilling tool assembly determination, and usage method according to exemplary embodiments of the present invention.

[0099] like Figure 7As shown, in steps N210-N230, a geological model of the region is established based on the collected seismic and well logging data. The model includes attributes such as fault fractures, formation dip angles, fine stratification of the target layer, gamma ray, and resistivity. In the directional landing section, the angular difference range of the formation to be cut into the landing area of ​​the designed well trajectory is initially determined. In the horizontal section, based on the length from the downhole measuring tool to the drill bit zero and the angle of the directional tool, the geometric relationship between the actual drilling position and the measurement position of the drill bit under the angular difference is calculated, and the corresponding measurement formation attributes when the drill bit encounters the boundary of the target layer are determined under the geological model.

[0100] like Figure 5 As shown, in step N300, the calibration method for the set of features of the drilled layer interface is determined.

[0101] The following will combine Figure 8 The steps for establishing the calibration parameters of the interface feature set of the drill-through layer according to an exemplary embodiment of the present invention are described below.

[0102] like Figure 8 As shown, in steps N310-N350, the characteristic parameters of the target layer interface are extracted. Taking the interface encountered by the drill bit as the standard, various data such as logging-while-drilling (LMD), gas logging, etc., are normalized and integrated, and time and spatial sequence calibration is performed to establish a set of characteristics of the drilled formation interface. Drilling rate is the fastest and most intuitive parameter for identifying layer penetration, and it identifies the changes in drilling speed when the drill bit enters / exits the layer. LMD parameters are distinguishable parameters for identifying layer penetration characteristics, and they identify changes in formation attribute characteristics when the measurement tool enters / exits the layer. The position of the drill bit after entering / exiting the layer can be determined through zero length and angle difference. Gas logging and cuttings logging calculate the drill bit's rock-breaking position based on the late arrival time, and then deduce the characteristics of the drill bit-formation spatial position. Using drilling rate as the standard quantity, other characteristic responses are regressed to the drill bit's rock-breaking time series to reflect the characteristics when the drill bit enters / exits the target layer, thus establishing a feature set.

[0103] like Figure 5 As shown, in step N400, the simulation method and process for drilling and measurement-while-drilling parameters under different angle differences are determined.

[0104] The following will combine Figure 9 This describes the steps for simulating drilling and measurement-while-drilling parameters under different angle differences according to an exemplary embodiment of the present invention.

[0105] like Figure 9 As shown, in steps N410-N450, numerical simulation combined with artificial intelligence methods is used to simulate the drilling speed of the drill bit entering / exiting the formation at different angle differences under the geological model; based on the zero length of the drill bit and the measurement while drilling tool, the formation position of the measurement tool under different angle differences is determined, and formation property curves such as gamma and resistivity are simulated; after removing the influence of late arrival time, based on phase change and reservoir charging characteristics, the mean method is used to determine the gas logging and cuttings logging characteristic data;

[0106] like Figure 5 As shown, in step N500, a method for judging the accuracy of simulated feature data combination is established and iteratively verified through actual drilling.

[0107] The following will combine Figure 10 This describes the steps of the method for judging the accuracy of simulated feature data combination and the iterative verification of actual drilling according to an exemplary embodiment of the present invention.

[0108] like Figure 10 As shown, in steps N510-N5100, the drilling, logging, and surveying characteristics of the target layer are identified through existing well drilling in the region. A feature combination identification standard under finite angle difference is established, and parameters such as the block geological module and drilling tools are determined. Actual drilling simulation is performed, and feature identification combinations under different angle differences are expanded. The simulation is expressed using the standard feature combination, and the simulation effect is verified through actual drilling. If the verification effect is poor, the simulation method is corrected, and the simulation is repeated. If the simulation effect is good, the simulation results can be expanded to the feature combination set under differentiated angle differences. Simultaneously, iterative comprehensive analysis of simulation and actual drilling effects can be performed to determine the spatial relationship between the trajectory and the target layer, guiding trajectory optimization in advance to achieve the goals of high reservoir encounter rate and smooth trajectory.

[0109] Compared with existing technologies, this invention has the following advantages: (1) It comprehensively judges the risk of drill bit encountering formation by using various data such as drilling, logging, and logging while drilling; (2) It uses drilling parameters to judge the drill bit encountering formation, eliminating the problem of delayed formation judgment caused by zero length in conventional logging while drilling; (3) It simulates and establishes a dataset of the top and bottom of the target formation cut by the drill bit under different angle differences, eliminating the characteristic expression of the difference in logging while drilling curves caused by angle differences; (4) Based on zero length and angle difference, it can determine the position of the logging while drilling instrument in the formation, and can further predict the risk of drill bit encountering formation by comparing the simulated formation attribute curve with the logging while drilling formation attribute curve, thereby improving the ability to predict and adjust the well trajectory. In summary, this invention can solve the problems of low identification efficiency after encountering formation, slow trajectory adjustment cycle, and many invalid footage in the horizontal section during drilling of thin reservoirs and heterogeneous reservoirs. It has broad application prospects for guiding horizontal wells to optimize and adjust the trajectory in advance and improve the reservoir drilling effect, and is of great significance for realizing the efficient development of unconventional oil and gas resources.

[0110] like Figure 11 The figure shows a schematic diagram of a device for determining the relationship between a trajectory and a reservoir based on entry and exit layer feature recognition according to an embodiment of the present invention. The device shown in the figure includes:

[0111] The first feature set module 10 is used to obtain the basic data of the drilled wells in the target block, classify and statistically analyze the basic data according to the angle difference value, and obtain the first feature set when the drill bit encounters the top and bottom interfaces of the target layer.

[0112] The second feature set module 20 is used to simulate the entry and exit of the drill bit into and out of the formation using a pre-established geological model, obtain the drilling parameters at the entry and exit times, and perform regression calibration processing on the measurement while drilling and logging data corresponding to the entry and exit times to obtain the second feature set corresponding to the entry and exit times of the drill bit.

[0113] The model correction module 30 is used to perform model correction processing on the pre-established geological model using the first feature set and the second feature set;

[0114] The third feature set module 40 is used to simulate the time when the drill bit enters and exits the top and bottom of the target layer at different angle differences using the modified geological model, to obtain drilling parameters, logging while drilling and logging data corresponding to the time when entering and exiting the top and bottom of the target layer, and to perform logging while drilling and logging data conversion and calibration processing on the drilling parameters corresponding to the time when entering and exiting the top and bottom of the target layer to obtain the third feature set.

[0115] The trajectory optimization module 50 is used to acquire measured data during the actual drilling process and use a third feature set to compare the measured data to perform trajectory adjustment processing in order to complete trajectory optimization.

[0116] As one embodiment of the present invention, such as Figure 12 As shown, the first feature set module 10 includes:

[0117] Angle difference range unit 11 is used to divide the basic data into layers and determine the angle difference range of entering and exiting the layer;

[0118] The first feature set unit 12 is used to segment the range of entry and exit angle difference into a certain degree interval to obtain the first feature set when the drill bit encounters the top and bottom interfaces of the target layer in different angle difference segments; wherein, the first feature set consists of drilling parameters, logging-while-drilling parameters, logging parameters and logging parameters under the preset angle difference.

[0119] As one embodiment of the present invention, such as Figure 13 As shown, the device also includes:

[0120] The geological model module 60 is used to acquire seismic and well completion logging data, and to establish a geological model using the seismic and well completion logging data.

[0121] The entry angle module 70 is used to determine the entry angle of the trajectory when landing based on seismic and well logging data.

[0122] The spatial relationship module 80 is used to determine the spatial relationship between the drill bit and the measuring instrument based on the orientation and measuring tools.

[0123] As one embodiment of the present invention, such as Figure 14As shown, the model correction module 30 includes:

[0124] The comparison matching rate unit 31 is used to compare the first feature set with the second feature set to obtain the set comparison matching rate;

[0125] Model correction unit 32 is used to perform model correction processing on the pre-established geological model if the set comparison consistency rate is not greater than a preset threshold.

[0126] Based on the same concept as the aforementioned method for determining the trajectory-reservoir relationship based on entry-exit layer feature identification, this invention also provides a device for determining the trajectory-reservoir relationship based on entry-exit layer feature identification. Since the principle underlying this device for determining the trajectory-reservoir relationship based on entry-exit layer feature identification is similar to that of the aforementioned method, its implementation can refer to the implementation of the aforementioned method, and will not be repeated here.

[0127] This invention can solve the problems of low identification efficiency after drilling thin reservoirs and heterogeneous reservoirs, slow trajectory adjustment cycle, and many invalid footage in horizontal sections. It has broad application prospects for guiding horizontal wells to optimize and adjust the trajectory in advance and improve the reservoir drilling effect. It is of great significance for realizing the efficient development of unconventional oil and gas resources.

[0128] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the above-described method.

[0129] The present invention also provides a computer program product, including a computer program / instructions, which, when executed by a processor, implement the steps of the above-described method.

[0130] The present invention also provides a computer-readable storage medium storing a computer program for performing the above-described methods.

[0131] like Figure 15 As shown, the electronic device 600 may also include: a communication module 110, an input unit 120, an audio processor 130, a display 160, and a power supply 170. It is worth noting that the electronic device 600 does not necessarily need to include these components. Figure 15 All components shown; in addition, the electronic device 600 may also include Figure 15 For components not shown, please refer to existing technologies.

[0132] like Figure 15As shown, the central processing unit 100, sometimes also referred to as a controller or operating control, may include a microprocessor or other processor device and / or logic device. The central processing unit 100 receives inputs and controls the operation of various components of the electronic device 600.

[0133] The memory 140 may be, for example, one or more of a cache, flash memory, hard drive, removable media, volatile memory, non-volatile memory, or other suitable devices. It may store the aforementioned failure-related information, and also store a program for executing that information. The central processing unit 100 may execute the program stored in the memory 140 to perform information storage or processing, etc.

[0134] Input unit 120 provides input to central processing unit 100. Input unit 120 may be, for example, a keypad or touch input device. Power supply 170 provides power to electronic device 600. Display 160 displays images and text. Display may be, for example, an LCD display, but is not limited thereto.

[0135] The memory 140 can be a solid-state memory, such as a read-only memory (ROM), random access memory (RAM), a SIM card, etc. It can also be a memory that retains information even when power is off, can be selectively erased, and contains more data; examples of this type of memory are sometimes referred to as EPROMs. The memory 140 can also be some other type of device. The memory 140 includes a buffer memory 141 (sometimes referred to as a buffer). The memory 140 may include an application / function storage unit 142 for storing application programs and function programs or processes for executing the operation of the electronic device 600 via the central processing unit 100.

[0136] The memory 140 may also include a data storage unit 143 for storing data, such as contacts, digital data, pictures, sounds, and / or any other data used by the electronic device. The driver storage unit 144 of the memory 140 may include various drivers for the electronic device's communication functions and / or for performing other functions of the electronic device (such as messaging applications, address book applications, etc.).

[0137] The communication module 110 is a transmitter / receiver 110 that transmits and receives signals via antenna 111. The communication module (transmitter / receiver) 110 is coupled to the central processing unit 100 to provide input signals and receive output signals, which can be the same as in a conventional mobile communication terminal.

[0138] Based on different communication technologies, multiple communication modules 110 can be configured in the same electronic device, such as cellular network modules, Bluetooth modules, and / or wireless LAN modules. The communication module (transmitter / receiver) 110 is also coupled to a speaker 131 and a microphone 132 via an audio processor 130 to provide audio output via the speaker 131 and receive audio input from the microphone 132, thereby enabling typical telecommunications functions. The audio processor 130 may include any suitable buffer, decoder, amplifier, etc. Additionally, the audio processor 130 is coupled to a central processing unit 100, enabling on-device recording via the microphone 132 and on-device playback of stored audio via the speaker 131.

[0139] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0140] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0141] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0142] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0143] Specific embodiments have been used to illustrate the principles and implementation methods of this invention. The descriptions of the embodiments above are only for the purpose of helping to understand the method and core ideas of this invention. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this invention. Therefore, the content of this specification should not be construed as a limitation of this invention.

Claims

1. A method for determining the relationship between a trajectory and a reservoir based on the identification of entry and exit layer characteristics, characterized in that, The method comprises: obtaining basic data of a drilled well in a target block, performing classified statistics on the basic data according to an angle difference value, and obtaining a first feature set when a drill bit drills a top and bottom interface of a target layer; the angle difference value is an angle difference between a trajectory and a stratum dip angle in four cases of drilling into or out of the top and bottom interfaces of the target layer; simulating drilling in and out of a layer by using a pre-established geological model, obtaining drilling parameters at the time of drilling in and out of the layer, and performing regression calibration processing on measurement-while-drilling (MWD) and logging data corresponding to the time of drilling in and out of the layer, to obtain a second feature set corresponding to the time of drilling in and out of the layer; performing model correction processing on the pre-established geological model by using the first feature set and the second feature set; simulating drilling in and out of the top and bottom interfaces of the target layer at different angle differences by using the geological model after the correction processing, obtaining drilling parameters, MWD and logging data corresponding to the time of drilling in and out of the top and bottom interfaces of the target layer, and performing MWD and logging data conversion calibration processing on the drilling parameters corresponding to the time of drilling in and out of the top and bottom interfaces of the target layer, to obtain a third feature set; obtaining measured data in a real drilling process, and performing trajectory adjustment processing on the measured data by using the third feature set, to complete trajectory optimization; the calibration method of determining a feature set parameter of drilling through a layer interface comprises: extracting a feature parameter of drilling through a target layer interface, performing normalization and integration on MWD, logging and gas logging data at the time of drilling through the target layer interface, performing time and space sequence calibration, and establishing a feature set of drilling through a stratum interface; taking drilling speed as a standard quantity, and reflecting features of drilling into or out of the target layer by regression of other features to a drilling time sequence of a drill bit, to establish a feature set.

2. The method of claim 1, wherein, The classified statistics on the basic data according to the angle difference value comprises: performing in and out of layer angle division on the basic data, and determining an in and out of layer angle difference range; segmenting the in and out of layer angle difference range in a certain degree interval, and obtaining the first feature set when the drill bit drills the top and bottom interfaces of the target layer in different angle difference segments; the first feature set comprises drilling parameters, logging parameters and logging parameters of drilling in and out of the layer at a preset angle difference; the logging parameters comprise MWD parameters.

3. The method of claim 1, wherein, The method further comprises: obtaining seismic and drilled well logging data, and establishing the geological model by using the seismic and drilled well logging data; determining an angle of drilling into a layer when landing according to the seismic and drilled well logging data; determining a spatial relationship between the drill bit and a measuring instrument according to a directional and measuring tool.

4. The method of claim 1, wherein, The model correction processing on the pre-established geological model by using the first feature set and the second feature set comprises: comparing the first feature set and the second feature set, and obtaining a set comparison coincidence rate; if the set comparison coincidence rate is not greater than a preset threshold, performing model correction processing on the pre-established geological model.

5. A device for determining the relationship between a trajectory and a reservoir based on the recognition of entry and exit layer characteristics, characterized in that, The device comprises: The first feature set module is configured to obtain basic data of a drilled well in a target block, and perform classified statistics on the basic data according to an angle difference value, to obtain a first feature set of a drill bit when drilling through a top and bottom interface of a target layer; the angle difference value is an angle difference between a trajectory and a stratum dip angle in four cases of drilling out or drilling into the top and bottom interface of the target layer. The second feature set module is configured to simulate drilling in and out of a layer by using a pre-established geological model, to obtain drilling parameters at a time of drilling in and out of the layer, and to perform regression calibration processing on logging-while-drilling and logging data corresponding to the time of drilling in and out of the layer, to obtain a second feature set corresponding to the time of drilling in and out of the layer. The model correction module is configured to perform model correction processing on the pre-established geological model by using the first feature set and the second feature set. The third feature set module is configured to simulate drilling in and out of a top and bottom interface of a target layer at different angle differences by using the corrected geological model, to obtain drilling parameters, logging-while-drilling and logging data corresponding to the time of drilling in and out of the top and bottom interface of the target layer, and to perform logging-while-drilling and logging data conversion calibration processing on the drilling parameters corresponding to the time of drilling in and out of the top and bottom interface of the target layer, to obtain a third feature set. The trajectory optimization module is configured to obtain measured data in a real drilling process, and to perform trajectory adjustment processing on the measured data by using the third feature set, to complete trajectory optimization. The calibration method for determining a feature set parameter of drilling through a layer interface comprises: Feature parameters of drilling through a target layer interface are extracted, and logging-while-drilling, logging and gas logging data at the time of drilling through the target layer interface are integrated and calibrated in time and space sequences, to establish a feature set of drilling through a stratum interface; other features are regressed to a rock breaking time sequence of a drill bit by taking a drilling speed as a standard quantity, to reflect features of drilling out or drilling into a target layer, and to establish a feature set.

6. The apparatus of claim 5, wherein, The first feature set module comprises: An angle difference range unit is configured to divide an in and out layer angle, and to determine an in and out layer angle difference range. A first feature set unit is configured to segment a certain degree interval of the in and out layer angle difference range, to obtain a first feature set of a drill bit when drilling through a top and bottom interface of a target layer in different angle difference segments; the first feature set comprises drilling parameters, logging-while-drilling parameters and logging parameters of drilling in and out of a layer at a pre-set angle difference.

7. The apparatus of claim 5, wherein, The device further comprises: A geological model module is configured to obtain seismic and drilled well logging data, and to establish the geological model by using the seismic and drilled well logging data. An in layer angle module is configured to determine an in layer angle when a trajectory lands according to the seismic and drilled well logging data. A spatial relationship module is configured to determine a spatial relationship between a drill bit and a measuring instrument according to a direction and a measuring tool.

8. The apparatus of claim 5, wherein, The model correction module comprises: A comparison coincidence rate unit is configured to compare the first feature set and the second feature set, to obtain a set comparison coincidence rate. A model correction unit is configured to perform model correction processing on the pre-established geological model if the set comparison coincidence rate is not greater than a pre-set threshold value.

9. An electronic device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, The processor executes the computer program to implement the method of any one of claims 1 to 4.

10. A computer-readable storage medium, characterized in that, The computer readable storage medium stores a computer program for performing the method of any one of claims 1 to 4.

11. A computer program product comprising computer programs or instructions, characterized in that, The computer program or instructions, when executed by a processor, implement the steps of the method of any one of claims 1 to 4.

Images