Geosteering method and device based on forward modeling of seismic data

Abstract

The present invention provides a geosteering method and device based on forward modeling of seismic data. The method comprises: establishing a wave impedance model for a target block based on well logging data for the target block; determining forward reflection wave characteristics for the target block based on the seismic data and well logging data for the target block; and determining geosteering for the target block based on the wave impedance model and the forward reflection wave characteristics. The present invention is adaptable to geosteering modeling and field geosteering in various strata and depths, and is compatible with different data types. It addresses the issues of inaccurate reservoir predictions and low-precision steering models faced by horizontal well decision-makers, thereby improving reservoir encounter rates and reducing drilling operation risks.

Description

Technical Field

[0001] The present invention relates to the technical field of oil and gas development, and in particular to a geosteering method and device based on seismic data forward simulation. Background Art

[0002] Conventional geosteering methods, addressing the difficulties of ultra-deep reservoir prediction and low seismic resolution, typically use adjacent wells to establish a two-dimensional, layered geosteering model of the water layer. The model's structural morphology is then adjusted based on depth-domain seismic profiles. The physical properties of the interwell formations are predicted based on seismic waveform variations to determine the rationality of the wellbore trajectory design and optimize it. During drilling, measurement-while-drilling data is used to adjust the steering model and the wellbore trajectory, guiding drilling decisions. However, due to issues with seismic data resolution and uncertainty, this method results in multiple solutions for the predicted formation properties and insufficient accuracy in the established geosteering model, which can easily lead to drilling failures. Summary of the Invention

[0003] In response to the problems in the existing technology, the geosteering method and device based on forward simulation of seismic data proposed in the present invention can be adapted to geosteering modeling and on-site geosteering in various strata and at different depths, and can be compatible with different data types. It solves the problems of inaccurate reservoir prediction and low precision of steering models for horizontal well decision makers, thereby achieving the purpose of improving the reservoir drilling rate and reducing the risk of drilling operations.

[0004] In a first aspect, the present invention provides a geosteering method based on seismic data forward modeling, comprising:

[0005] Establishing a wave impedance model of the target block according to the well logging data of the target block;

[0006] Determining forward reflection wave characteristics of the target block based on the seismic data of the target block and the well logging data;

[0007] The geosteering of the target block is determined according to the wave impedance model and the forward reflection wave characteristics.

[0008] In one embodiment, establishing the wave impedance model of the target block based on the well logging data of the target block includes:

[0009] Determining the well logging curve characteristics of the target layer in the target block;

[0010] constructing a single-well rock physics model according to the logging curve characteristics;

[0011] Based on the seismic structure of the target block and the sedimentary data of the target block, establishing an inter-well stratigraphic lithologic-sedimentary combination model and a lithologic combination model of the target block;

[0012] The wave impedance model is established based on the single well rock physics model, the inter-well stratum lithology-sedimentation combination model and the lithology combination model.

[0013] In one embodiment, determining the forward reflection wave characteristics of the target block based on the seismic data of the target block and the well logging data includes:

[0014] Establishing a reflection coefficient model of the target block according to the seismic data and the well logging data;

[0015] The reflection coefficient model is forward-modeled to determine the forward-modeled reflection wave characteristics.

[0016] In one embodiment, determining the geosteering of the target block according to the wave impedance model and the forward reflection wave characteristics includes:

[0017] Correcting the wave impedance model according to the forward modeled reflection wave characteristics to establish a final wave impedance model;

[0018] The geosteering of the target block is determined according to the final wave impedance model.

[0019] In one embodiment, the correcting the wave impedance model according to the forward reflection wave characteristics to establish a final wave impedance model includes:

[0020] The wave impedance model and the reflection coefficient model are adjusted until the error between the seismic forward reflection wave of the target layer and the actual seismic reflection wave is less than a preset threshold, so as to establish the final wave impedance model.

[0021] In one embodiment, determining the geosteering of the target block according to the final wave impedance model includes:

[0022] determining the seismic reflection characteristics of the target layer according to the final wave impedance model;

[0023] Establishing a three-dimensional geosteering framework model of the target layer according to the seismic reflection characteristics;

[0024] The geosteering is determined according to the three-dimensional geosteering framework model.

[0025] In one embodiment, determining the geosteering according to the three-dimensional geosteering framework model includes:

[0026] Constructing a horizontal well geosteering attribute model for the target layer according to the three-dimensional geosteering framework model;

[0027] Determining the horizontal well logging response characteristics of the target layer according to the horizontal well geosteering attribute model;

[0028] The geosteering is determined according to the horizontal well logging response characteristics.

[0029] In a second aspect, the present invention provides a geosteering device based on seismic data forward modeling, the device comprising:

[0030] A wave impedance model building module is used to build a wave impedance model of the target block based on the well logging data of the target block;

[0031] a reflection wave feature determination module, configured to determine the forward modeled reflection wave feature of the target block based on the seismic data of the target block and the well logging data;

[0032] The geosteering determination module is used to determine the geosteering of the target block according to the wave impedance model and the forward reflection wave characteristics.

[0033] In one embodiment, the wave impedance model building module includes:

[0034] a well logging curve feature determination unit, configured to determine the well logging curve feature of the target layer in the target block;

[0035] A rock physics model building unit, configured to build a single-well rock physics model based on the logging curve characteristics;

[0036] a combination model building unit, configured to build an inter-well stratigraphic lithologic-sedimentary combination model and a lithologic combination model of the target block based on the seismic structure of the target block and the sedimentary data of the target block;

[0037] The wave impedance model establishing unit is used to establish the wave impedance model according to the single well rock physics model, the inter-well stratum lithology-sedimentation combination model and the lithology combination model.

[0038] In one embodiment, the reflected wave feature determination module includes:

[0039] a reflection coefficient model establishing unit, configured to establish a reflection coefficient model of the target block based on the seismic data and the well logging data;

[0040] The reflection wave characteristic determination unit is used to perform forward modeling on the reflection coefficient model to determine the forward modeled reflection wave characteristic.

[0041] In one embodiment, the geosteering determination module includes:

[0042] A final model establishing unit, configured to correct the wave impedance model according to the forward reflection wave characteristics to establish a final wave impedance model;

[0043] The geosteering determination unit is used to determine the geosteering of the target block according to the final wave impedance model.

[0044] In one embodiment, the final model building unit includes:

[0045] The final model establishment subunit is used to adjust the wave impedance model and the reflection coefficient model until the error value between the seismic forward reflection wave of the target layer and its actual seismic reflection wave is less than a preset threshold, so as to establish the final wave impedance model.

[0046] In one embodiment, the geosteering determination unit includes:

[0047] a seismic reflection characteristic determining unit, configured to determine the seismic reflection characteristic of the target layer according to the final wave impedance model;

[0048] A framework model building unit, configured to build a three-dimensional geosteering framework model of the target layer according to the seismic reflection characteristics;

[0049] The geosteering determination subunit is configured to determine the geosteering according to the three-dimensional geosteering framework model.

[0050] In one embodiment, the geosteering determination subunit includes:

[0051] An attribute model building unit, configured to build a horizontal well geosteering attribute model for the target layer based on the three-dimensional geosteering framework model;

[0052] a well logging response characteristic determination unit, configured to determine the horizontal well logging response characteristic of the target layer according to the horizontal well geosteering attribute model;

[0053] A horizontal geosteering determination unit is configured to determine the geosteering according to the horizontal well logging response characteristics.

[0054] In a third aspect, the present invention provides a computer program product comprising a computer program / instruction, which, when executed by a processor, implements the steps of a geosteering method based on forward modeling of seismic data.

[0055] In a fourth aspect, the present invention provides an electronic device comprising a memory, a processor and a determination program stored in the memory and executable on the processor, wherein when the processor executes the program, the steps of a geological steering method based on forward modeling of seismic data are implemented.

[0056] In a fifth aspect, the present invention provides a determination machine readable storage medium having a determination machine program stored thereon, which, when executed by a processor, implements the steps of a geological steering method based on forward modeling of seismic data.

[0057] From the above description, it can be seen that the geological steering method and device based on forward modeling of seismic data provided by the embodiment of the present invention first establishes a wave impedance model of the target block based on the well logging data of the target block; then, determines the forward reflection wave characteristics of the target block based on the seismic data and well logging data of the target block; finally, determines the geological steering of the target block based on the wave impedance model and the forward reflection wave characteristics. The present invention first refers to the data of the pilot well or the adjacent well, analyzes the seismic response corresponding to the lithologic combination pattern or the oil and gas combination pattern, and compares and analyzes it with the actual seismic reflection wave to determine the seismic characteristics of high-quality reservoirs. On this basis, a horizontal well geological steering model is established to guide real-time decision-making of horizontal wells. After the actual application of multiple horizontal wells in ultra-deep formations, the reservoir drilling rate has increased by an average of 10 percentage points, effectively improving the recovery rate and development effect of horizontal wells. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0059] Figure 1 Schematic diagram of the flow of a geosteering method based on seismic data forward modeling in an embodiment of the present invention;

[0060] Figure 2 100 is a flow chart of step 100 in an embodiment of the present invention;

[0061] Figure 3 200 is a flow chart of step 200 in an embodiment of the present invention;

[0062] Figure 4 300 is a flowchart of an embodiment of the present invention;

[0063] Figure 5 301 is a flow chart of step 301 in an embodiment of the present invention;

[0064] Figure 6 302 is a flowchart of an embodiment of the present invention;

[0065] Figure 7 This is a flow chart of step 3023 in an embodiment of the present invention;

[0066] Figure 8 Schematic diagram of the flow of a geosteering method based on seismic data forward modeling in a specific application example of the present invention;

[0067] Figure 9A mind map of a geosteering method based on forward modeling of seismic data in a specific application example of the present invention;

[0068] Figure 10 Schematic diagram of regional evaluation analysis and single well modeling in a specific application example of the present invention;

[0069] Figure 11 Schematic diagram of earthquake forward modeling results in a specific application example of the present invention;

[0070] Figure 12 Schematic diagram of the pilot well logging evaluation results in a specific application example of the present invention;

[0071] Figure 13 A schematic diagram of azimuthal seismic reflection characteristics in a specific application example of the present invention;

[0072] Figure 14 This is a schematic diagram of seismic forward modeling results corresponding to the lithologic combination at 225° azimuth of an example well in a specific application example of the present invention;

[0073] Figure 15 Schematic diagram of a completed drilling geosteering model in a specific application example of the present invention;

[0074] Figure 16 Schematic diagram of the composition of a geosteering device based on seismic data forward modeling in an embodiment of the present invention;

[0075] Figure 17 Schematic diagram of the composition of the wave impedance model building module 10 in an embodiment of the present invention;

[0076] Figure 18 Schematic diagram of the composition of the reflected wave feature determination module 20 in an embodiment of the present invention;

[0077] Figure 19 Schematic diagram of the composition of the geosteering determination module 30 in an embodiment of the present invention;

[0078] Figure 20 Schematic diagram of the composition of the final model building unit 301 in an embodiment of the present invention;

[0079] Figure 21 Schematic diagram of the composition of the geosteering determination unit 302 in an embodiment of the present invention;

[0080] Figure 22 Schematic diagram of the composition of the geosteering determination subunit 3023 in an embodiment of the present invention;

[0081] Figure 23 Schematic diagram of the structure of an electronic device in an embodiment of the present invention. DETAILED DESCRIPTION

[0082] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0083] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0084] It should be noted that the terms "including" and "having" and any variations thereof in the specification and claims of this application and the above-mentioned drawings are intended to cover non-exclusive inclusions. For example, a process, method, system, product or apparatus that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or are inherent to these processes, methods, products or apparatuses.

[0085] It should be noted that, in the absence of conflict, the embodiments and features of the embodiments in this application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0086] The embodiment of the present invention provides a specific implementation of a geosteering method based on seismic data forward simulation, see Figure 1 , the method specifically includes the following contents:

[0087] Step 100: establishing a wave impedance model of the target block based on the well logging data of the target block;

[0088] Wave impedance refers to the stress required to induce a disturbance in rock that causes a particle to vibrate at a specific unit velocity. The greater the wave impedance, the greater the stress required to produce a specific unit velocity; conversely, the smaller the wave impedance, the smaller the stress required to produce a specific unit velocity.

[0089] Step 200: determining forward reflection wave characteristics of the target block based on the seismic data of the target block and the well logging data;

[0090] It can be understood that forward modeling involves deriving the distribution properties of a field from the properties of the source, while inversion involves deriving the properties of the source from the distribution of the field. In geophysics, if the properties of the Earth's medium, such as the velocity of seismic waves, are known, calculating the travel time of seismic waves (i.e., the time it takes for seismic waves to propagate through the Earth) is forward modeling. Similarly, if the structure and material properties of the underground medium are known, calculating the wave velocity, gravity, electromagnetics, geothermal parameters, and other indicators is also forward modeling. Conversely, if the properties of the Earth's medium, such as the velocity of seismic waves, are known, then inversion is used. For example, if the gravity anomaly at a particular location is known, then inversion is used to determine the subsurface material properties in that area. In remote sensing image interpretation, inversion involves determining the ground objects in the image based on spectral information, even if the ground objects are unknown.

[0091] Step 300: Determine the geosteering of the target block according to the wave impedance model and the forward reflection wave characteristics.

[0092] Specifically, the actual drilling logging curve and the forward logging curve are compared, and the shape of the forward logging curve is changed by adjusting the inclination and thickness to match the actual drilling logging curve. Based on steps 100 and 200, the sweet spot position of the undrilled formation is predicted, and the subsequent wellbore trajectory direction is designed to make the correct drilling decision. This process is repeated until drilling is completed.

[0093] As can be seen from the foregoing description, the geosteering method based on seismic data forward modeling provided in an embodiment of the present invention first establishes a wave impedance model for the target block based on the target block's well logging data; then, the forward-modeled reflection wave characteristics of the target block are determined based on the seismic and well logging data; and finally, the geosteering direction for the target block is determined based on the wave impedance model and the forward-modeled reflection wave characteristics. This method overcomes a number of exploration and development challenges, such as inaccurate ultra-deep reservoir predictions, low precision of horizontal well steering models, and low reservoir encounter rates. By constructing a precise geosteering model, the method optimizes wellbore trajectory design, guides real-time geosteering decisions on-site, improves drilling efficiency, reduces drilling risks, and achieves both exploration and evaluation results and development objectives.

[0094] In one embodiment, see Figure 2 , step 100 includes:

[0095] Step 101: determining the well logging curve characteristics of the target layer in the target block;

[0096] Step 102: constructing a single well rock physics model based on the logging curve characteristics;

[0097] Step 103: Based on the seismic structure of the target block and the sedimentary data of the target block, establish an inter-well stratum lithologic-sedimentary combination model and a lithologic combination model of the target block;

[0098] Step 104: Establish the wave impedance model based on the single well rock physics model, the inter-well stratum lithology-sedimentation combination model, and the lithology combination model.

[0099] In steps 101 to 104, first, regional logging data are collected and organized, and the logging curve characteristics of the target layer and its adjacent layers are analyzed. Through multi-well formation comparison, the physical property parameters of the target reservoir and surrounding rock, including characteristic parameters such as velocity, density, porosity and resistivity, are statistically analyzed to construct a single-well rock physics model. At the same time, combined with the geological sedimentary background and under the constraints of seismic structure, the inter-well stratum lithologic sedimentary combination pattern and lithologic combination model are constructed, and the inter-well interpolation algorithm is used to establish a wave impedance model.

[0100] In one embodiment, see Figure 3 , step 200 includes:

[0101] Step 201: establishing a reflection coefficient model of the target block based on the seismic data and the well logging data;

[0102] With the original acquired seismic data as a reference, based on the wave impedance data calculated from the original logging data, reflection coefficient models were established for different thicknesses, different dip angles, and different lithologic combinations.

[0103] Step 202: forward modeling the reflection coefficient model to determine the forward modeled reflection wave characteristics.

[0104] Specifically, the seismic forward modeling algorithm (convolution model algorithm is selected) is used to forward model the seismic forward reflection wave characteristics under various modes; the seismic response characteristics of various oil and gas production wells in the region are analyzed in detail, and the forward reflection wave laws of wells with different production rates are summarized.

[0105] In one embodiment, see Figure 4 , step 300 includes:

[0106] Step 301: Correcting the wave impedance model according to the forward reflection wave characteristics to establish a final wave impedance model;

[0107] By comparing the characteristics of the seismic forward reflection wave and the actual seismic reflection wave, and ensuring that the model matches the well data, the initial wave impedance and reflection coefficient model are fine-tuned to achieve the optimal match between the seismic forward reflection wave and the actual seismic reflection wave, even if the comparison error between the two is less than the preset threshold, the final wave impedance model is obtained.

[0108] Step 302: Determine the geosteering of the target block according to the final wave impedance model.

[0109] The seismic reflection characteristics of high-quality reservoirs are determined based on the final wave impedance model, and compared with actual seismic data, the reservoir development location of horizontal wells is predicted.

[0110] In one embodiment, see Figure 5 , step 301 includes:

[0111] Step 3011: Adjust the wave impedance model and the reflection coefficient model until the error between the seismic forward reflection wave of the target layer and its actual seismic reflection wave is less than a preset threshold, so as to establish the final wave impedance model.

[0112] Preferably, the preset threshold in step 3011 is 10%.

[0113] In one embodiment, see Figure 6 , step 302 includes:

[0114] Step 3021: determining the seismic reflection characteristics of the target layer according to the final wave impedance model;

[0115] Step 3022: establishing a three-dimensional geosteering framework model of the target layer according to the seismic reflection characteristics;

[0116] In steps 3021 and 3022, based on the determined seismic reflection characteristics of the high-quality reservoir and with reference to the waveform changes of the seismic profile, a three-dimensional geosteering framework model for horizontal wells is established under the constraints of the structural trend.

[0117] Step 3023: Determine the geosteering according to the three-dimensional geosteering framework model.

[0118] In one embodiment, see Figure 7 , step 3023 further includes:

[0119] Step 30231: constructing a horizontal well geosteering attribute model for the target layer based on the three-dimensional geosteering framework model;

[0120] Step 30232: determining the horizontal well logging response characteristics of the target layer according to the horizontal well geosteering attribute model;

[0121] Step 30233: Determine the geosteering according to the horizontal well logging response characteristics.

[0122] In steps 30231 to 30233, a finite element interpolation algorithm is used to construct a horizontal well geosteering attribute model (gamma, resistivity, acoustic wave, density, etc. models) under the constraints of the structural model; according to the response principles and parameters of different measuring instruments, the logging response characteristics of the formation drilled by the horizontal well are simulated to obtain forward logging curves, including conventional while-drilling curves such as gamma curves, resistivity curves, acoustic wave time difference curves and density curves.

[0123] Furthermore, during the drilling process of the target well, the device receives measurement while drilling data, compares the actual drilling logging curve with the forward logging curve in the device, and changes the shape of the forward logging curve by adjusting the geological steering model (inclination and thickness) to match the actual drilling logging curve; at the same time, the actual seismic reflection profile and wellbore trajectory are superimposed on the geological steering model to determine the current formation position of the wellbore trajectory. Based on the seismic response corresponding to the high-quality reservoir determined by the seismic forward modeling results, the sweet spot position of the undrilled formation is predicted, and the subsequent wellbore trajectory direction is designed to make correct drilling decisions. This process is repeated until drilling is completed.

[0124] To further illustrate this solution, the present invention also takes a horizontal well in a certain area as an example to provide a specific application example of the geosteering method based on seismic data forward simulation, see Figure 8 as well as Figure 9 , this specific application example specifically includes the following contents.

[0125] The target interval for this well is the Deng 2 Formation, located approximately 5,500 meters deep and belonging to a high-temperature, high-pressure formation. Most horizontal wells in this area face various engineering risks, including long drilling cycles, frequent uncertainties, a wide range of influencing factors, and frequent drilling accidents. Geologically, the formation drilled in this well is a carbonate formation. After the limestone dolomitized, the formation was uplifted and exposed to the surface, receiving geological processes such as weathering and karstification. This has resulted in a reservoir with strong lateral heterogeneity. This, coupled with the low seismic resolution and multi-solution issues in ultra-deep formations, results in low reservoir prediction accuracy and inaccurate geosteering models. This has led to a low reservoir encounter rate and low individual well production.

[0126] This well adopts the drilling technology of pilot well + sidetracking horizontal well. The pilot well is used to evaluate the reservoir condition and then select the appropriate layer and orientation to design the sidetracking horizontal well.

[0127] S1: Establish a single well model.

[0128] Collect and organize the logging data of the block and establish a single well rock physics model. Statistically analyze the reservoir development status of different wells in the block, statistically analyze the logging response characteristics of the surrounding rocks and reservoirs near the target layer of the block, analyze the rock combination pattern, thickness changes, logging curve characteristics of high-quality reservoirs, and finally establish a single well model, such as Figure 10 shown.

[0129] S2: Earthquake forward analysis.

[0130] According to the single well model, models of wells with different production rates are established and seismic forward analysis is performed, such as Figure 11 As shown in the figure, the response pattern of high-quality reservoirs is as follows: the peak energy at the top of the second lamp is relatively weakened (complex wave, amplitude drop); the maximum amplitude energy at the trough is relatively strong; and there is a bright spot inside the second lamp.

[0131] Based on the single-well rock physics model and under the lateral constraints of the seismic horizon, an interwell wave impedance model is constructed and converted into a reflection coefficient model. Using the seismic convolution algorithm, the wavelet is convolved with the reflection coefficient model to obtain the seismic forward modeling results, namely the seismic forward reflection waves. These seismic forward modeling results are then compared and analyzed with the actual seismic reflection waves. The wave impedance model and reflection coefficient model are continuously modified to ensure that the seismic forward modeling results match the actual seismic reflection waves. The final seismic forward modeling results corresponding to the wave impedance model can determine the seismic reflection wave characteristics corresponding to high-quality reservoirs, thereby predicting the development location and morphology of the reservoir drilled by the horizontal well.

[0132] S3: Analyze the seismic forward modeling characteristics corresponding to wells with different production rates and compare them with actual seismic data. It is believed that the top weak-amplitude reflection, strong trough, and underlying peak reflection highlights are high-quality reservoir development areas.

[0133] S4: Analyze the formation evaluation results of the target pilot well.

[0134] like Figure 12 As shown in the figure, the second section of the Deng River has a set of gas layers with an oblique thickness of 5.4m (vertical thickness of 2.37m), two sets of poor gas layers, and a set of water layers at the bottom (Table 1). The evaluation results reveal that the reservoir condition in this well area is poor. According to the seismic forward modeling results of high-yield neighboring wells in this area, the seismic response characteristics corresponding to the high-quality reservoirs in the second section of the Deng River are strong energy in the strong trough at the top of the Deng River and bright reflections at the underlying wave crest. By comparing the seismic reflection characteristics of the example wells in various directions, it is believed that the seismic wave reflection characteristics at the 225° direction are the development characteristics of the high-quality reservoir, such as Figure 13 shown. Figure 14 The logging data of the example wells were used to establish a lithologic combination model and forward model the seismic reflection wave characteristics. As the thickness of the high-quality reservoir increased and approached the top, the top crest weakened, the trough energy increased, and the underlying crest reflection bright spot strengthened, which was basically consistent with the actual seismic reflection. This shows that the reservoir is relatively developed at the 225° azimuth, and the horizontal well trajectory can be designed, and a geological steering model can be established to guide drilling.

[0135] Table 1 Lamp second stage interpretation results

[0136]

[0137] S5: Establish an initial geosteering model based on the pilot well data and seismic reflection wave characteristics;

[0138] S6: Forward model the LWD curve based on the initial geosteering model and determine the geosteering according to the LWD curve.

[0139] Based on well logging data and seismic interpretation, an initial geosteering framework model is constructed. Finite element methods are used to model interwell properties under seismic reflection wave constraints. Combined with measurement-while-drilling (MWD) tool parameters, forward modeling of the formation logging response curves for the horizontal well is performed. During drilling, MWD and directional measurement data are received from the drilling site. The geosteering model (inclination and azimuth) is adjusted to align the MWD data with the forward modeled logging curves. Finally, under seismic wave constraints, a final geosteering model is generated. The actual drilling trajectory is projected onto the geosteering model, and seismic profiles are superimposed on the model. This information is used to determine the formation location and reservoir properties of the current wellbore trajectory, and to predict the structural morphology, physical property changes, and reservoir development of the formation ahead of the drill bit. Furthermore, based on drilling project requirements, accurate drilling decisions are made and communicated to the directional well controller. Based on these decisions, the directional well controller issues commands to the drilling instrument, advancing the wellbore, thereby increasing the reservoir encounter rate and reducing drilling risks.

[0140] The initial geosteering model is established based on the pilot well data and seismic reflection wave characteristics. Figure 15 As shown in the figure, the LWD curve is forward-modeled. During the drilling process, the steering model is updated based on the LWD results and combined with seismic reflection characteristics to make drilling decisions, adjust the wellbore trajectory in real time, and drill forward.

[0141] exist Figure 15 The actual drilling trajectory did not undergo significant adjustments relative to the planned trajectory, resulting in a relatively smooth wellbore trajectory and subsequent completion. The well drilled a 712-meter horizontal section, encountered 620 meters of interbedded layers, and achieved an 87.07% penetration rate, an 11 percentage point improvement over neighboring wells. Subsequent fracturing operations opened up the lower reservoir, resulting in a tested gas production of 282,800 cubic meters per day, ranking third in production within the block and making it a highly productive well.

[0142] As can be seen from the foregoing description, the geosteering method based on seismic data forward modeling provided in an embodiment of the present invention first establishes a wave impedance model for the target block based on the target block's well logging data; then, the forward reflection wave characteristics of the target block are determined based on the seismic data and well logging data of the target block; and finally, the geosteering direction for the target block is determined based on the wave impedance model and the forward reflection wave characteristics. The present invention is adaptable to geosteering modeling and on-site geosteering analysis and decision-making in various strata and depths, and is compatible with different data types. It solves the problems of inaccurate reservoir predictions and low steering model accuracy that plague horizontal well decision-makers, thereby achieving the goal of improving reservoir encounter rates and reducing drilling operation risks.

[0143] Based on the same inventive concept, the embodiments of the present application also provide a geosteering device based on seismic data forward modeling, which can be used to implement the method described in the above embodiments, such as the following embodiments. Since the principle of solving the problem by the geosteering device based on seismic data forward modeling is similar to that of the geosteering method based on seismic data forward modeling, the implementation of the geosteering device based on seismic data forward modeling can refer to the implementation of the geosteering method based on seismic data forward modeling, and the repeated parts will not be repeated. As used below, the term "unit" or "module" can be a combination of software and / or hardware that implements a predetermined function. Although the system described in the following embodiments is preferably implemented in software, implementation in hardware, or a combination of software and hardware, is also possible and conceived.

[0144] The embodiment of the present invention provides a specific implementation of a geosteering device based on seismic data forward simulation that can implement a geosteering method based on seismic data forward simulation, see Figure 16 The geosteering device based on forward modeling of seismic data specifically includes the following contents:

[0145] The wave impedance model establishment module 10 is used to establish the wave impedance model of the target block according to the well logging data of the target block;

[0146] A reflection wave feature determination module 20 is configured to determine the forward modeled reflection wave feature of the target block based on the seismic data of the target block and the well logging data;

[0147] The geosteering determination module 30 is configured to determine the geosteering of the target block according to the wave impedance model and the forward reflection wave characteristics.

[0148] In one embodiment, see Figure 17 , the wave impedance model building module 10 includes:

[0149] The well logging curve feature determination unit 101 is used to determine the well logging curve feature of the target layer in the target block;

[0150] A rock physics model building unit 102 is used to build a single well rock physics model according to the logging curve characteristics;

[0151] A combination model building unit 103 is configured to build an inter-well stratigraphic lithologic-sedimentary combination model and a lithologic combination model of the target block based on the seismic structure of the target block and the sedimentary data of the target block;

[0152] The wave impedance model establishing unit 104 is configured to establish the wave impedance model according to the single well rock physics model, the inter-well stratum lithology-sedimentation combination model, and the lithology combination model.

[0153] In one embodiment, see Figure 18 , the reflected wave feature determination module 20 includes:

[0154] A reflection coefficient model building unit 201 is configured to build a reflection coefficient model of the target block based on the seismic data and the well logging data;

[0155] The reflection wave characteristic determination unit 202 is configured to perform forward modeling on the reflection coefficient model to determine the forward modeled reflection wave characteristic.

[0156] In one embodiment, see Figure 19 , the geosteering determination module 30 includes:

[0157] A final model building unit 301 is used to calibrate the wave impedance model according to the forward reflection wave characteristics to establish a final wave impedance model;

[0158] The geosteering determination unit 302 is configured to determine the geosteering of the target block according to the final wave impedance model.

[0159] In one embodiment, see Figure 20 , the final model building unit 301 includes:

[0160] The final model establishment subunit 3011 is used to adjust the wave impedance model and the reflection coefficient model until the error value between the seismic forward reflection wave of the target layer and its actual seismic reflection wave is less than a preset threshold, so as to establish the final wave impedance model.

[0161] In one embodiment, see Figure 21 , the geosteering determination unit 302 includes:

[0162] A seismic reflection characteristic determining unit 3021 is configured to determine the seismic reflection characteristic of the target layer according to the final wave impedance model;

[0163] A framework model building unit 3022 is configured to build a three-dimensional geosteering framework model of the target layer according to the seismic reflection characteristics;

[0164] The geosteering determination subunit 3023 is configured to determine the geosteering according to the three-dimensional geosteering framework model.

[0165] In one embodiment, see Figure 22 The geosteering determination subunit 3023 includes:

[0166] An attribute model building unit 30231 is configured to build a horizontal well geosteering attribute model for the target layer based on the three-dimensional geosteering framework model;

[0167] The logging response characteristic determination unit 30232 is configured to determine the horizontal well logging response characteristic of the target layer according to the horizontal well geosteering attribute model;

[0168] The horizontal geosteering determination unit 30233 is configured to determine the geosteering according to the horizontal well logging response characteristics.

[0169] From the above description, it can be seen that the geological guidance device based on forward modeling of seismic data provided by the embodiment of the present invention first establishes a wave impedance model of the target block based on the well logging data of the target block; then, the forward reflection wave characteristics of the target block are determined based on the seismic data and well logging data of the target block; finally, the geological guidance of the target block is determined based on the wave impedance model and the forward reflection wave characteristics. The present invention first refers to the data of the pilot well or the adjacent well, analyzes the seismic response corresponding to the lithologic combination pattern or the oil and gas combination pattern, and compares and analyzes it with the actual seismic reflection wave to determine the seismic characteristics of the high-quality reservoir. On this basis, a horizontal well geological guidance model is established to guide real-time decision-making of horizontal wells. After the actual application of multiple horizontal wells in ultra-deep formations, the reservoir drilling rate has increased by an average of 10 percentage points, effectively improving the recovery rate and development effect of the horizontal wells.

[0170] The embodiments of the present application also provide a specific implementation of an electronic device capable of implementing all steps of the geosteering method based on seismic data forward simulation in the above embodiments, see Figure 23 , electronic equipment specifically includes the following:

[0171] Processor 1201, memory 1202, communications interface 1203, and bus 1204;

[0172] The processor 1201, the memory 1202, and the communication interface 1203 communicate with each other via the bus 1204; the communication interface 1203 is used to implement information transmission between the server device and the client device and other related devices;

[0173] The processor 1201 is used to call the determination machine program in the memory 1202. When the processor executes the determination machine program, all steps of the geosteering method based on seismic data forward modeling in the above embodiment are implemented. For example, when the processor executes the determination machine program, the following steps are implemented:

[0174] Step 100: establishing a wave impedance model of the target block based on the well logging data of the target block;

[0175] Step 200: determining forward reflection wave characteristics of the target block based on the seismic data of the target block and the well logging data;

[0176] Step 300: Determine the geosteering of the target block according to the wave impedance model and the forward reflection wave characteristics.

[0177] The embodiments of the present application also provide a determination machine-readable storage medium capable of implementing all steps of the geosteering method based on forward modeling of seismic data in the above-mentioned embodiments. The determination machine-readable storage medium stores a determination machine program. When the determination machine program is executed by a processor, all steps of the geosteering method based on forward modeling of seismic data in the above-mentioned embodiments are implemented. For example, when the processor executes the determination machine program, the following steps are implemented:

[0178] Step 100: establishing a wave impedance model of the target block based on the well logging data of the target block;

[0179] Step 200: determining forward reflection wave characteristics of the target block based on the seismic data of the target block and the well logging data;

[0180] Step 300: Determine the geosteering of the target block according to the wave impedance model and the forward reflection wave characteristics.

[0181] The various embodiments in this specification are described in a progressive manner. Similar portions between the various embodiments can be referenced to each other. Each embodiment focuses on the differences between the other embodiments. In particular, the hardware + program embodiments are generally similar to the method embodiments, so their description is relatively simple. For relevant portions, refer to the description of the method embodiments.

[0182] The foregoing description of this specification describes specific embodiments. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims can be performed in an order different from that described in the embodiments and still achieve the desired results. Furthermore, the processes depicted in the accompanying drawings do not necessarily require the specific order shown or the sequential order to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0183] Although the present application provides method operation steps such as embodiments or flowcharts, more or fewer operation steps may be included based on conventional or non-creative work. The order of steps listed in the embodiments is only one way of executing the steps among many steps and does not represent the only execution order. When an actual device or client product is executed, it can be executed in the order shown in the embodiments or the drawings or in parallel (for example, in a parallel processor or multi-threaded processing environment).

[0184] For the convenience of description, the above devices are described in terms of functions divided into various modules. Of course, when implementing the embodiments of this specification, the functions of each module can be implemented in the same or multiple software and / or hardware, or the modules that implement the same function can be implemented by a combination of multiple sub-modules or sub-units, etc. The device embodiments described above are merely schematic. For example, the division of the units is only a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0185] Those skilled in the art will also appreciate that, in addition to implementing the controller purely in machine-readable program code, it is entirely possible to implement the same functionality by programming the method steps logically, such as in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers. Therefore, such a controller can be considered a hardware component, and the devices included therein for implementing various functions can also be considered structures within the hardware component. Alternatively, the devices for implementing various functions can be considered both software modules implementing the method and structures within the hardware component.

[0186] In a typical configuration, the determination device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0187] The memory may include non-permanent storage in a certain machine-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. Memory is an example of a certain machine-readable medium.

[0188] Embodiments of this specification may be described in the general context of machine-executable instructions executed by a machine, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, and the like that perform specific tasks or implement specific abstract data types. Embodiments of this specification may also be practiced in distributed machine environments, where tasks are performed by remote processing devices connected via a communications network. In distributed machine environments, program modules may reside in local and remote machine storage media, including storage devices.

[0189] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between the various embodiments can be referenced across them. Each embodiment focuses on the differences from the other embodiments. In particular, since the system embodiments are generally similar to the method embodiments, their description is relatively simple. For relevant parts, reference can be made to the description of the method embodiments. Throughout this specification, reference to the terms "one embodiment," "some embodiments," "example," "specific example," or "some examples" means that the specific features, structures, materials, or characteristics described in conjunction with that embodiment or example are included in at least one embodiment or example of the embodiments in this specification. In this specification, the schematic representations of these terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, those skilled in the art may combine and integrate the different embodiments or examples, and features of different embodiments or examples, described in this specification, without conflict.

[0190] The above description is merely an example of the embodiments of this specification and is not intended to limit the embodiments of this specification. For those skilled in the art, various modifications and variations of the embodiments of this specification are possible. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the embodiments of this specification shall be included within the scope of the claims of the embodiments of this specification.

Claims

1. A geosteering method based on forward modeling of seismic data, characterized in that: include: Establishing a wave impedance model of the target block according to the well logging data of the target block; Determining forward reflection wave characteristics of the target block based on the seismic data of the target block and the well logging data; Determining the geosteering of the target block according to the wave impedance model and the forward reflection wave characteristics; Determining the geosteering of the target block according to the wave impedance model and the forward reflection wave characteristics includes: correcting the wave impedance model according to the forward reflection wave characteristics to establish a final wave impedance model; and determining the geosteering of the target block according to the final wave impedance model; Determining the geosteering of the target block according to the final wave impedance model includes: determining the seismic reflection characteristics of the target layer according to the final wave impedance model; establishing a three-dimensional geosteering framework model of the target layer according to the seismic reflection characteristics; and determining the geosteering according to the three-dimensional geosteering framework model; Determining the geosteering according to the three-dimensional geosteering framework model includes: constructing a horizontal well geosteering attribute model of the target layer according to the three-dimensional geosteering framework model; determining the horizontal well logging response characteristics of the target layer according to the horizontal well geosteering attribute model; and determining the geosteering according to the horizontal well logging response characteristics, specifically: Using the finite element interpolation algorithm, a horizontal well geosteering attribute model is constructed under the constraints of the structural model. Based on the response principles and parameters of different measuring instruments, the logging response characteristics of the formation drilled by the horizontal well are simulated to obtain forward logging curves, including conventional while-drilling curves such as gamma curves, resistivity curves, acoustic travel time curves, and density curves. During the drilling process of the target well, the actual drilling logging curve and the forward logging curve are compared. The forward logging curve is changed by adjusting the geosteering model to match the actual drilling logging curve. The actual seismic reflection profile and wellbore trajectory are superimposed on the geosteering model to determine the current formation position of the wellbore trajectory. Based on the seismic response corresponding to the high-quality reservoir determined by the seismic forward modeling results, the sweet spot position of the undrilled formation is predicted, and the subsequent wellbore trajectory direction is designed to make correct drilling decisions.

2. The geosteering method according to claim 1, wherein: The step of establishing the wave impedance model of the target block according to the well logging data of the target block includes: Determining the well logging curve characteristics of the target layer in the target block; constructing a single-well rock physics model according to the logging curve characteristics; Based on the seismic structure of the target block and the sedimentary data of the target block, establishing an inter-well stratigraphic lithologic-sedimentary combination model and a lithologic combination model of the target block; The wave impedance model is established based on the single well rock physics model, the inter-well stratum lithology-sedimentation combination model and the lithology combination model.

3. The geosteering method according to claim 1, wherein: Determining forward reflection wave characteristics of the target block according to the seismic data of the target block and the well logging data includes: Establishing a reflection coefficient model of the target block according to the seismic data and the well logging data; The reflection coefficient model is forward-modeled to determine the forward-modeled reflection wave characteristics.

4. The geosteering method according to claim 1, wherein: The wave impedance model is corrected according to the forward reflection wave characteristics to establish a final wave impedance model, including: The wave impedance model and the reflection coefficient model are adjusted until the error between the seismic forward reflection wave of the target layer and the actual seismic reflection wave is less than a preset threshold, so as to establish the final wave impedance model.

5. A geosteering device based on forward modeling of seismic data, characterized in that: include: A wave impedance model building module is used to build a wave impedance model of the target block based on the well logging data of the target block; a reflection wave feature determination module, configured to determine the forward modeled reflection wave feature of the target block based on the seismic data of the target block and the well logging data; A geosteering determination module, configured to determine the geosteering of the target block according to the wave impedance model and the forward reflection wave characteristics; The geosteering determination module includes: a final model establishment unit, configured to calibrate the wave impedance model according to the forward reflection wave characteristics to establish a final wave impedance model; a geosteering determination unit, configured to determine the geosteering of the target block according to the final wave impedance model; The geosteering determination unit includes: a seismic reflection characteristic determination unit, configured to determine the seismic reflection characteristics of the target layer according to the final wave impedance model; a framework model establishment unit, configured to establish a three-dimensional geosteering framework model of the target layer according to the seismic reflection characteristics; and a geosteering determination subunit, configured to determine the geosteering according to the three-dimensional geosteering framework model. The geosteering determination subunit includes: an attribute model establishment unit, configured to construct a horizontal well geosteering attribute model for the target layer according to the three-dimensional geosteering framework model; a logging response characteristic determination unit, configured to determine the horizontal well logging response characteristics of the target layer according to the horizontal well geosteering attribute model; and a horizontal geosteering determination unit, configured to determine the geosteering according to the horizontal well logging response characteristics. The geosteering determination subunit is specifically configured to: Using the finite element interpolation algorithm, a horizontal well geosteering attribute model is constructed under the constraints of the structural model. Based on the response principles and parameters of different measuring instruments, the logging response characteristics of the formation drilled by the horizontal well are simulated to obtain forward logging curves, including conventional while-drilling curves such as gamma curves, resistivity curves, acoustic travel time curves, and density curves. During the drilling process of the target well, the actual drilling logging curve and the forward logging curve are compared. The forward logging curve is changed by adjusting the geosteering model to match the actual drilling logging curve. At the same time, the actual seismic reflection profile and wellbore trajectory are superimposed on the geosteering model to determine the current formation position of the wellbore trajectory. Based on the seismic response corresponding to the high-quality reservoir determined by the seismic forward modeling results, the sweet spot position of the undrilled formation is predicted, and the subsequent wellbore trajectory direction is designed to make correct drilling decisions.

6. The geosteering device according to claim 5, characterized in that: The wave impedance model building module includes: a well logging curve feature determination unit, configured to determine the well logging curve feature of the target layer in the target block; A rock physics model building unit, configured to build a single-well rock physics model based on the logging curve characteristics; a combination model building unit, configured to build an inter-well stratigraphic lithologic-sedimentary combination model and a lithologic combination model of the target block based on the seismic structure of the target block and the sedimentary data of the target block; The wave impedance model establishing unit is used to establish the wave impedance model according to the single well rock physics model, the inter-well stratum lithology-sedimentation combination model and the lithology combination model.

7. The geosteering device according to claim 5, characterized in that: The reflected wave feature determination module includes: a reflection coefficient model establishing unit, configured to establish a reflection coefficient model of the target block based on the seismic data and the well logging data; The reflection wave characteristic determination unit is used to perform forward modeling on the reflection coefficient model to determine the forward modeled reflection wave characteristic.

8. The geosteering device according to claim 5, characterized in that: The final model building unit includes: The final model establishment subunit is used to adjust the wave impedance model and the reflection coefficient model until the error value between the seismic forward reflection wave of the target layer and its actual seismic reflection wave is less than a preset threshold, so as to establish the final wave impedance model.

9. A computer program product comprising a computer program / instructions, characterized in that When the computer program / instruction is executed by a processor, the geosteering method based on seismic data forward modeling according to any one of claims 1 to 5 is implemented.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the steps of the geosteering method based on seismic data forward modeling according to any one of claims 1 to 5 are implemented.

11. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the geosteering method based on seismic data forward modeling according to any one of claims 1 to 5 are implemented.

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