CN114545507A

CN114545507A - Coring depth determination method and device, terminal and storage medium

Info

Publication number: CN114545507A
Application number: CN202011327279.6A
Authority: CN
Inventors: 郑超; 张本健; 尹宏; 邓波; 王宇峰; 罗洋; 杨跃明; 孙志昀; 胡欣; 裴森奇; 赵漾; 曾琪; 王旭丽; 汤兴宇; 杨鉴; 薛小红; 张砚; 胡婧; 龙虹宇; 牟兴羽
Original assignee: Petrochina Co Ltd
Current assignee: Petrochina Co Ltd
Priority date: 2020-11-24
Filing date: 2020-11-24
Publication date: 2022-05-27
Anticipated expiration: 2040-11-24
Also published as: CN114545507B

Abstract

The disclosure provides a coring depth determination method, a coring depth determination device, a coring depth determination terminal and a coring depth determination storage medium, and relates to the technical field of geological exploration and development. The method comprises the following steps: according to the first geological model, performing geosteering forward modeling on a well zone where a first mining well which is drilling is located to obtain theoretical waveform response characteristics; adjusting a first geological model according to the actual waveform response characteristics and the theoretical waveform response characteristics of the target lithology section; determining at least one sensitive attribute according to the adjusted second geological model; marking the second geological model based on the attribute characterization of the at least one sensitive attribute; and carrying out depth calibration on the well region where the first mining well is located based on the third geological model obtained by labeling to obtain the coring depth. The third geological model is obtained by finely processing the first geological model, so that the third geological model can more accurately reflect the real geological layer condition, and the accuracy of the coring depth prediction through the third geological model is further improved.

Description

Coring depth determination method and device, terminal and storage medium

Technical Field

The disclosure relates to the technical field of geological exploration and development, in particular to a coring depth determining method, a coring depth determining device, a coring depth determining terminal and a coring depth determining storage medium.

Background

In geological exploration and development, well drilling and coring are common methods for understanding geological conditions. Core drilling refers to the operation of removing a core from the ground with a coring tool during drilling. The location of the target lithologic segment can be determined by well coring. In order to improve the drilling efficiency, the core depth is predicted before drilling, so that a drilling scheme is formulated according to the predicted core depth. For example, drilling is performed quickly above the predicted depth, and the drilling speed is reduced near the predicted depth so that the coring position can be accurately found.

In the related art, a prediction method based on seismic calibration is often adopted to predict the coring depth. Generally, when drilling and coring are carried out, a coring purpose is determined according to development requirements, and the coring purpose is used for indicating a target lithology section for coring. And then establishing a corresponding relation between the seismic reflection information and the geological horizon or corresponding geological information (including sequence, gyrus, sedimentary facies, lithology, physical properties and the like) by a prediction method of seismic calibration, and determining the depth of the target lithology section according to the corresponding relation to obtain the coring depth corresponding to the coring target.

In the related art, the wavelength of the seismic wave is large, so that the resolution of the corresponding relationship between the seismic reflection information generated based on the seismic wave and the geological formation or the corresponding geological information is low, the accuracy of depth prediction is low, and the accuracy of coring depth prediction is low.

Disclosure of Invention

The embodiment of the disclosure provides a coring depth determination method, a coring depth determination device, a terminal and a storage medium, which can improve the accuracy of coring depth prediction. The technical scheme is as follows:

in one aspect, a coring depth determination method is provided, the method comprising:

according to a first geological model, carrying out geosteering forward modeling on a well zone where a first mining well is located to obtain theoretical waveform response characteristics of a target lithology section, wherein the first mining well is a mining well which is drilling, the target lithology section is a lithology section corresponding to a coring target, and the coring target is the lithology of a core which is determined based on the purpose of the first mining well;

adjusting the first geological model according to the actual waveform response characteristics and the theoretical waveform response characteristics of the target lithology section under different influence factors to obtain a second geological model;

determining at least one sensitive attribute of the target lithology section according to the second geological model;

marking the second geological model based on the attribute characterization of the at least one sensitive attribute to obtain a third geological model;

and carrying out depth calibration on the well zone where the first mining well is located based on the third geological model to obtain the coring depth of the target lithology section.

In some embodiments, the performing geosteering forward modeling on the well region where the first mining well is located according to the first geological model to obtain the theoretical waveform response characteristics of the target lithology section includes:

performing sedimentary microfacies analysis on target lithologic sections of a plurality of second production wells to obtain a sedimentary longitudinal superposition relationship of the first geological model, wherein the second production wells are completed and adjacent wells of the first production wells;

comparing the target depositional facies of the target lithologic segments in the second plurality of production wells in the longitudinally stacked relationship;

performing single-factor analysis on the target sedimentary facies corresponding to the second mining wells, and determining waveform response characteristics of the target sedimentary facies under different influence factors;

and analyzing the waveform response characteristics of the target sedimentary facies to obtain the theoretical waveform response characteristics of the target lithology section.

In some embodiments, the adjusting the first geological model according to the actual waveform response characteristics and the theoretical waveform response characteristics of the target lithology section under different influence factors to obtain a second geological model includes:

adjusting the positions and the thicknesses of different lithologic sections in the first geological model according to the actual waveform response characteristics and the theoretical waveform response characteristics to obtain a fourth geological model;

determining theoretical waveform response characteristics of the fourth geological model;

and responding to the mismatching of the actual waveform response characteristic and the theoretical waveform response characteristic of the fourth geological model, and continuously adjusting the positions and the thicknesses of different lithologic sections in the fourth geological model until the theoretical waveform response characteristic of the fourth geological model is matched with the actual waveform response characteristic, so as to obtain the second geological model.

In some embodiments, said determining at least one sensitive attribute of said target lithology section from said second geological model comprises:

determining a plurality of seismic attributes to be detected;

respectively determining the waveform response characteristics of the second geological model under each seismic attribute;

at least one sensitivity attribute is determined from the plurality of seismic attributes that the waveform response characteristic matches the actual waveform response characteristic.

In some embodiments, the determining a plurality of seismic attributes to detect includes:

determining a target lithology section corresponding to the coring purpose according to the coring purpose;

and determining a plurality of seismic attributes of the target lithology section according to the properties of the target lithology section.

inputting the position and the thickness of the lithologic section corresponding to the second geological model into an attribute determination model;

outputting, by the attribute determination model, at least one sensitive attribute of the target lithology segment.

In some embodiments, said tagging the second geological model based on the attribute characterization of the at least one sensitive attribute, resulting in a third geological model, comprises:

determining attribute characterization of each sensitive attribute;

determining the weight of each sensitive attribute according to the coring purpose;

and according to the weight of each sensitive attribute, fusing the attribute characterization of the at least one sensitive attribute to obtain the third geological model.

In another aspect, there is provided a coring depth determination apparatus, the apparatus comprising:

the system comprises a forward modeling module, a data processing module and a data processing module, wherein the forward modeling module is used for performing geosteering forward modeling on a well zone where a first mining well is located according to a first geological model to obtain theoretical waveform response characteristics of a target lithology section, the first mining well is a mining well which is drilling, the target lithology section is a lithology section corresponding to a coring target, and the coring target is the lithology of a core which is determined based on the purpose of the first mining well;

the adjusting module is used for adjusting the first geological model according to the actual waveform response characteristics and the theoretical waveform response characteristics of the target lithology section under different influence factors to obtain a second geological model;

a determination module for determining at least one sensitive attribute of the target lithology section according to the second geological model;

the marking module is used for marking the second geological model based on the attribute representation of the at least one sensitive attribute to obtain a third geological model;

and the depth calibration module is used for performing depth calibration on the well zone where the first mining well is located based on the third geological model to obtain the coring depth of the target lithology section.

In some embodiments, the forward modeling module comprises:

the analysis unit is used for carrying out sedimentary microfacies analysis on target lithologic sections of a plurality of second production wells to obtain a sedimentary longitudinal superposition relation of the first geological model, wherein the second production wells are completed and adjacent wells of the first production wells;

a comparison unit for comparing target dephasing of target lithologic segments in the plurality of second production wells in the longitudinally stacked relationship;

the first determining unit is used for performing single-factor analysis on the target sedimentary facies corresponding to the second mining wells and determining the waveform response characteristics of the target sedimentary facies under different influence factors;

and the characteristic analysis unit is used for analyzing the waveform response characteristic of the target sedimentary facies to obtain the theoretical waveform response characteristic of the target lithology section.

In some embodiments, the adjustment module comprises:

the adjusting unit is used for adjusting the positions and the thicknesses of different lithologic sections in the first geological model according to the actual waveform response characteristics and the theoretical waveform response characteristics to obtain a fourth geological model;

the second determining unit is used for determining theoretical waveform response characteristics of the fourth geological model;

and the adjusting unit is used for responding to the mismatching of the actual waveform response characteristic and the theoretical waveform response characteristic of the fourth geological model, and continuously adjusting the positions and the thicknesses of different lithologic sections in the fourth geological model until the theoretical waveform response characteristic of the fourth geological model is matched with the actual waveform response characteristic, so that the second geological model is obtained.

In some embodiments, the determining module comprises:

the third determining unit is used for determining multiple seismic attributes to be detected;

the fourth determining unit is used for respectively determining the waveform response characteristics of the second geological model under each seismic attribute;

and the fifth determining unit is used for determining at least one sensitive attribute of the waveform response characteristic matched with the actual waveform response characteristic from the plurality of seismic attributes.

In some embodiments, the third determining unit is configured to determine, according to the coring purpose, a corresponding target lithology section of the coring purpose; determining a plurality of seismic attributes of the target lithology segment according to the properties of the target lithology segment.

In some embodiments, the determining module comprises:

the input unit is used for inputting the position and the thickness of the lithologic section corresponding to the second geological model into the attribute determination model;

a sixth determining unit, configured to output at least one sensitive attribute of the target lithology segment through the attribute determination model.

In some embodiments, the annotation module comprises:

a seventh determining module unit, configured to determine an attribute characterization of each of the sensitive attributes;

an eighth determining unit, configured to determine a weight of each sensitive attribute according to the coring purpose;

and the marking unit is used for marking the second geological model according to the weight of each sensitive attribute and the attribute representation of at least one sensitive attribute to obtain the third geological model.

In another aspect, a terminal is provided that includes a processor and a memory; the memory stores at least one program code for execution by the processor to implement the coring depth determination method as described above.

In another aspect, a computer readable storage medium is provided, the storage medium having stored thereon at least one program code for execution by a processor to implement the coring depth determination method as described above.

In another aspect, a computer program product is provided, which stores at least one program code, which is loaded and executed by a processor to implement the coring depth determination method of the above aspect.

In the embodiment of the disclosure, the first geological model is refined by performing geosteering forward modeling simulation and sensitive attribute intersection on the first geological model to obtain a third geological model, so that the third geological model can more accurately reflect the real geological layer condition, the coring depth is predicted through the third geological model, and the accuracy of predicting the coring depth can be improved.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the disclosure and together with the description, serve to explain the principles of the disclosure.

FIG. 1 is a flow diagram illustrating a method of coring depth determination, according to an exemplary embodiment;

FIG. 2 is a flow diagram illustrating a method of coring depth determination, according to an exemplary embodiment;

FIG. 3 is a schematic diagram illustrating a geological model according to an exemplary embodiment;

FIG. 4 is a schematic diagram illustrating a dephase plane spread pattern in accordance with an exemplary embodiment;

FIG. 5 is a schematic diagram illustrating a forward simulation in accordance with an exemplary embodiment;

FIG. 6 is a schematic diagram illustrating a geological model according to another exemplary embodiment;

FIG. 7 is a schematic diagram illustrating a geological model according to another exemplary embodiment;

FIG. 8 is a schematic diagram illustrating a coring depth prediction, according to another exemplary embodiment;

FIG. 9 is a block diagram illustrating a coring depth determination apparatus in accordance with an exemplary embodiment;

fig. 10 is a block diagram illustrating a terminal according to an example embodiment.

Detailed Description

Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the exemplary embodiments below are not intended to represent all implementations consistent with the present disclosure. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present disclosure, as detailed in the appended claims.

For the sake of understanding, the terms and application scenarios related to the embodiments of the present disclosure are first briefly described below.

Coring: i.e. drilling and coring. And (4) the operation of taking out the core from the underground by using a coring tool.

Core: the core is essential basic data in the exploration, development and research work of petroleum and natural gas. The method is used for researching the characteristics of the stratum, the sediment, the hydrocarbon source rock, the reservoir and the like, deepening the geological understanding and the like.

Producing a well: refers to a well drilled in geological exploration, such as an oil well, a gas well, or other exploration well.

In recent years, with the increase in demand for natural gas, it is important to accelerate the exploration and development of natural gas. Areas with rich natural gas storage often have the characteristic of complex and variable geological conditions, so that the following difficulties exist when coring is performed on the areas with buried biomass, thin thickness and complex geological conditions:

first, geological aspect. The target lithologic section is deep in buried depth and thin in thickness and is influenced by factors such as sedimentary rock action, and the combination of longitudinal lithology and transverse lithology of the stratum is complex and changeable. This has resulted in some geological conditions where conventional methods cannot be used to predict the depth and horizon of the core. Particularly, when the core is taken at the positions of lithology, stratum, reservoir interface and the like, the difficulty in predicting the core depth is greatly improved, and the accuracy is reduced.

Such as volcanic rock development areas. The volcanic development area is influenced by the landform besides volcanic eruption, so that the thickness and the distribution area of the volcanic rock stratum can be irregularly circulated. As another example, a lithofacies transformation zone. Because the lithofacies phase transition zone is a transition zone of stratum deposition, the lithology combination and the lithology combination of normal stratum have larger difference, and therefore, the logging curve characteristics, carbonate analysis data and seismic response characteristics of the lithofacies phase transition zone have larger difference with the adjacent well zone. As another example, an unstable precipitation zone. The unstable precipitation zone includes two cases. Firstly, the changeable district of little ancient landform, the fluctuation of the changeable district of little ancient landform has caused the sedimentary difference of deposit, if be difficult to deposit thick layer stratum in the eminence, then can deposit the thicker stratum of relatively more normal stratum in the low department. The second is the unstable area of source supply, because of the difference of source supply in the unstable area of source supply, deposit amount is different in different areas. Thus, the formation thickness varies.

In addition, the oil and gas favorable area is often a fault development standby, and is influenced by a fracture zone, so that the layer boundary determination of the corresponding target lithologic section of the coring target becomes complicated and difficult to judge, the difficulty of coring depth prediction is further improved, and the accuracy of the coring depth prediction is reduced.

Second, engineering aspects. The cost and difficulty of coring operations increases as the depth of the borehole increases. The deep coring operation has high cost and great engineering difficulty, and once a target lithologic section is drilled in the coring process due to misjudgment, the planned coring interval cannot be obtained, so the accuracy of the coring depth prediction is particularly important.

In order to ensure the accuracy of the coring depth prediction, a coring depth determination method for a geological complex zone is developed through comparative analysis.

Fig. 1 is a flowchart illustrating a coring depth determination method applied to a terminal according to an exemplary embodiment, and the fingerprint verification method includes the following steps, as shown in fig. 1.

In step 101, according to a first geological model, performing geosteering forward modeling on a well zone where a first production well is located to obtain a theoretical waveform response characteristic of a target lithology section, where the first production well is a drilling production well, the target lithology section is a lithology section corresponding to a coring objective, and the coring objective is the lithology of a core determined based on a purpose of the first production well.

In step 102, the first geological model is adjusted according to the actual waveform response characteristics and the theoretical waveform response characteristics of the target lithology section under different influence factors, and a second geological model is obtained.

At step 103, at least one sensitive attribute of the target lithology segment is determined based on the second geological model.

In step 104, the second geological model is labeled based on the attribute characterization of the at least one sensitive attribute to obtain a third geological model.

In step 105, depth calibration is performed on the well zone where the first mining well is located based on the third geological model, so as to obtain the coring depth of the target lithology section.

In some embodiments, the performing geosteering forward modeling on the well zone where the first production well is located according to the first geological model to obtain the theoretical waveform response characteristics of the target lithology section includes:

performing sedimentary microfacies analysis on target lithologic sections of a plurality of second production wells to obtain a sedimentary longitudinal superposition relation of the first geological model, wherein the second production wells are completed and adjacent wells of the first production wells;

comparing the target depositional facies of the target lithologic sections in the second plurality of production wells in the longitudinal stacking relationship;

performing single-factor analysis on the target sedimentary facies corresponding to the second mining wells to determine the waveform response characteristics of the target sedimentary facies under different influence factors;

In some embodiments, the adjusting the first geological model according to the actual waveform response characteristic and the theoretical waveform response characteristic of the target lithology section under different influence factors to obtain a second geological model includes:

and responding to the mismatching of the actual waveform response characteristic and the theoretical waveform response characteristic of the fourth geological model, and continuously adjusting the positions and the thicknesses of different lithologic sections in the fourth geological model until the theoretical waveform response characteristic of the fourth geological model is matched with the actual waveform response characteristic to obtain the second geological model.

In some embodiments, the determining at least one sensitive attribute of the target lithology section from the second geological model comprises:

determining a plurality of seismic attributes to be detected;

at least one susceptibility attribute is determined from the plurality of seismic attributes that the waveform response characteristic matches the actual waveform response characteristic.

In some embodiments, the determining a plurality of seismic attributes to be detected includes:

In some embodiments, the tagging the second geological model based on the attribute characterization of the at least one sensitive attribute to obtain a third geological model comprises:

determining attribute characterization of each sensitive attribute;

determining a weight for each sensitive attribute based on the coring objective;

and according to the weight of each sensitive attribute, fusing the attribute characterization of at least one sensitive attribute to obtain the third geological model.

Fig. 2 is a flowchart illustrating a coring depth determination method applied to a terminal according to an exemplary embodiment, and the coring depth determination method includes the following steps, as shown in fig. 2.

In step 201, the terminal performs geosteering forward modeling on the well zone where the first mining well is located according to the first geological model to obtain the theoretical waveform response characteristic of the target lithology section.

Wherein the first production well is a producing well that is being drilled, the target lithology section is a corresponding lithology section of a coring objective, the coring objective is a lithology of a cored core determined based on a purpose of the first production well.

The geosteering forward simulation refers to forward simulation of a first geological model, and waveform response characteristics displayed by a target lithology layer in a second mining well in the first geological model are determined through the forward simulation. The process is realized by the following steps (a1) - (a4), including:

(A1) and (4) carrying out sedimentary microfacies analysis on the target lithologic sections of the second mining wells by the terminal to obtain a sedimentary longitudinal superposition relation of the first geological model.

Wherein the second production well is completed and the adjacent well to the first production well. In the step, the terminal carries out product microphase analysis under a sequence stratigraphic framework on the target lithologic section according to the plurality of second mining wells to obtain the sedimentary longitudinal stacking relation of the first geological model, so that the stacking relation of each sedimentary facies in the stratum is determined.

(A2) The terminal compares the target depositional facies of the target lithology sections in the second plurality of production wells in the longitudinally stacked relationship.

The target dephasing is the dephasing that best characterizes the lithology of the target lithology segment. In this step, the sedimentary facies corresponding to the target lithology section in each second production well is determined, and the sedimentary facies of the target lithology sections of the plurality of second production wells are analyzed, so that the target sedimentary facies which can represent the lithology characteristics of the target lithology sections most can be obtained.

(A3) And the terminal performs single-factor analysis on the target sedimentary facies corresponding to the second mining wells to determine the waveform response characteristics of the target sedimentary facies under different influence factors.

The one-factor analysis refers to an analysis process in which only one variable is set for a target sedimentary facies. The single factor includes, among other things, the distance of the target dephase from the top boundary of the formation, the thickness of the target dephase, the physical properties of the target dephase, and the like. Wherein the physical properties of the target deposit phase include porosity parameters and the like. Correspondingly, in the step, the terminal respectively determines the waveform response characteristics of the target sedimentary facies under different factors corresponding to the same seismic wave.

(A4) And analyzing the waveform response characteristic of the target sedimentary facies by the terminal to obtain the theoretical waveform response characteristic of the target lithology section.

In the step, the terminal regularly summarizes the waveform response characteristics of each target sedimentary facies to obtain the theoretical waveform response characteristics of the target lithology section.

In the implementation mode, the target lithologic section is represented by the target sedimentary facies to perform the regular summary of the waveform response characteristics, so that the complicated and various reservoir longitudinal combination types are simplified, and the efficiency and the accuracy of determining the waveform response characteristics are improved.

In addition, the first geological model is a simulated data volume of a well zone where the simulated first production well is located. And the terminal acquires data of a second mining well in the scenic spot where the first mining well is located, and data volume import is carried out on the scenic spot where the first mining well is located according to the data of the first mining well and the data of the second mining well to obtain a first geological model. The process is realized by the following steps (B1) - (B3), including:

(B1) the terminal obtains first base data for a first production well.

The first basic data comprises seismic data, logging data, geological data of the area where the first mining well is located and the like of the first mining well.

The seismic data comprises a three-dimensional seismic data body of a well zone where the first mining well is located. The three-dimensional seismic data body comprises information such as stratum and lithology and can be formed by a prestack time migration data body and a high-fidelity prestack time migration pure wave data body.

The logging data includes GR (natural Gamma Ray log) data, AC (Acoustic time difference log) data, DEN (Density log) data, Rt (Resistivity log) data, and the like.

The geological data comprises well position coordinates, ground elevation, height of center filling, geological design, measured well deviation, azimuth angle data and the like.

In the step, the terminal acquires first basic data of a first production well which is stored; or receiving first basic data sent by other electronic equipment, wherein the other electronic equipment is used for detecting the first production well to obtain the first basic data of the first production well.

(B2) The terminal obtains second base data for a second plurality of production wells.

The plurality of second production wells are completed wells in the well zone where the first production well is located. The plurality of second production wells are adjacent to the first production well or within a preset distance of the first production well and the second production well. The second basic data comprises seismic data, logging data, geological data of the area where the second exploitation well is located and the like of the second exploitation well. The second basic data is similar to the first basic data, and is not described herein again. The process of acquiring the second basic data of the second production well by the terminal is similar to the process of acquiring the first basic data of the first production well, and is not repeated herein.

(B3) The terminal determines the first geological model according to the first basic data and the second basic data.

In the step, the terminal establishes a research work area through the logging data and the seismic data, adds other basic data of the first mining well and the second mining well into the research work area to obtain a seismic data body, and determines a first geological model based on the seismic data body.

It should be noted that the terminal is capable of directly determining the seismic data volume as the first geological model. The terminal can further carry out fineness portrayal on the seismic data body to obtain the first geological model. The method for the terminal to perform the fineness depiction on the seismic data volume is realized by at least one of the following methods.

In a first implementation, the terminal performs fidelity, amplitude and high resolution processing on the seismic data volume to obtain a first geological model. By the implementation mode, the longitudinal resolution of the seismic data volume can be improved. Wherein, the improvement degree is related to the degree of fidelity and amplitude-preserving high-resolution processing, and the longitudinal resolution can be improved by 10-20 meters after the fidelity and amplitude-preserving high-resolution processing is generally carried out.

In a second implementation mode, the terminal performs fine synthetic record calibration on the seismic data volume through second basic data of a second mining well, and performs fine calibration on each layer boundary to obtain a first geological model. Referring to FIG. 3, FIG. 3 illustrates a fine synthetic record calibration using the second baseline data from the second producing well and fidelity amplitude high resolution processed data volume A and second producing well sonic moveout and density profile data in accordance with an exemplary embodiment. The seismic response of the top boundary of the flying second section is a wave crest, and the bottom boundary is a wave trough. In the implementation mode, the seismic data volume is subjected to fine synthesis calibration through known basic data, so that the geological horizon boundary in the obtained first geological model is more obvious.

In a third implementation mode, the terminal describes a sedimentary facies plane development diagram of a layer where a target lithologic section is located according to the existing seismic data body and logging rock debris data and logging data of a second exploitation well, and marks the position of the first exploitation well in the sedimentary facies plane development diagram according to the position coordinate of the first exploitation well so as to determine the facies zone position of the compound exploitation well according to the sedimentary facies plane development diagram. Referring to fig. 4, fig. 4 is a deposition phase plan layout diagram according to an exemplary embodiment. A sedimentary facies plane development pattern of a layer where a planned coring section of a research area is located is recognized and depicted by utilizing a second exploitation well point-line-plane, well position coordinates of a first exploitation well are put into a plane diagram, referring to fig. 4, the first exploitation well LT2 is located in a plateau edge facies zone development area, the second exploitation well L4, the second exploitation well L6, the second exploitation well L104 and the second exploitation well L004-X1 are located in a plateau edge facies zone, and the second exploitation well L17 is in a slope facies zone.

And in the fourth implementation mode, the field outcrop is determined through the gamma instrument, and the result is used for finely revising the second exploitation well to obtain the lithologic superposition rule and the corresponding gamma curve characteristic. For example, a gamma instrument is used for measuring field outcrop, and the result is used for finely repairing the well-drilled and logged data of the adjacent region, and the point to be described is determined by the lithology superposition rule and the gamma curve characteristic corresponding to the lithology superposition rule, because one rock fragment sample is taken when the interval of the logged rock fragment data is 1.0m, the outcrop measurement can be encrypted for sampling according to the requirement.

It should be noted that the terminal can perform a refinement revision on the seismic data volume through any one of the above implementation manners, and the terminal can also perform a refinement revision on the seismic data volume by combining at least two of the above four implementation manners, which is not specifically limited in the embodiment of the present disclosure.

In step 202, the terminal adjusts the first geological model according to the actual waveform response characteristics and the theoretical waveform response characteristics of the target lithology section under different influence factors, so as to obtain a second geological model.

Referring to fig. 5 and 6, the terminal designs two geological models by using forward modeling technology according to the actual geological conditions of the research area: and when the target lithology section is analyzed at different positions and different thicknesses, the corresponding waveform response characteristics of the target lithology section are analyzed, so that the waveform response characteristics of the target lithology section are analyzed. Wherein the top left diagram in FIG. 5 is a geological model of a 15 meter thick reservoir at 10 meters, 20 meters, 30 meters, 40 meters, and 50 meters; the upper right graph in fig. 5 is the corresponding waveform response characteristic. The lower left diagram in fig. 5 is a geological model of a reservoir 30 meters, 5 meters thick, 10 meters thick, 15 meters thick, 20 meters thick, 25 meters thick and 30 meters thick from the previous rock formation; the lower right graph in fig. 5 is the corresponding waveform response characteristic. And simulation proves that if the waveform response characteristic of the target lithologic segment is a wave trough, selecting a root mean square amplitude attribute which is sensitive to the response characteristic of the target lithologic segment, and depicting the plane spread characteristic of the target lithologic segment. And intersecting the stratum thickness map and the extracted root-mean-square amplitude attribute to further determine the distribution range B of the target lithology section. In this step, the terminal adjusts the first geologic model according to the difference between the theoretical waveform response characteristic and the actual waveform theoretical characteristic, so as to obtain a second geologic model. This step is realized by the following steps (1) to (3), including:

(1) and the terminal adjusts the positions and the thicknesses of different lithologic sections in the first geological model according to the actual waveform response characteristic and the theoretical waveform response characteristic to obtain a fourth geological model.

In this step, the terminal determines the difference between the actual waveform response characteristic and the theoretical waveform response characteristic, and determines the difference between the first geological model and the actual geological formation, thereby determining a lithology section in the first geological model that is inconsistent with the actual geological formation, and adjusting the position and thickness of the lithology section.

(2) The terminal determines theoretical waveform response characteristics of the fourth geological model.

In this step, similar to the step 201, the process of determining the theoretical waveform response characteristic of the first geological model by the terminal is similar, and details are not repeated here.

(3) And responding to the mismatching of the actual waveform response characteristic and the theoretical waveform response characteristic of the fourth geological model, and continuously adjusting the positions and the thicknesses of different lithologic sections in the fourth geological model by the terminal until the theoretical waveform response characteristic of the fourth geological model is matched with the actual waveform response characteristic to obtain the second geological model.

In this step, the terminal continues to match the theoretical waveform response characteristic of the fourth geological model with the actual waveform response characteristic of the current well, and if the theoretical waveform response characteristic of the fourth geological model is matched with the actual waveform response characteristic, the fourth geological model is determined as the second geological model. And responding to the mismatching of the theoretical waveform response characteristic and the actual waveform response characteristic of the fourth geological model, and continuously adjusting the position and the thickness of the lithologic section in the fourth geological model until the theoretical waveform response characteristic is matched with the actual waveform response characteristic to obtain a second geological model. See fig. 7. The theoretical waveform response characteristic and the actual waveform response characteristic are matched, namely the theoretical waveform response characteristic is the same as or similar to the actual waveform response characteristic.

In step 203, the terminal determines a plurality of seismic attributes to be detected.

In the step, the terminal determines a plurality of seismic attributes which are sensitive to the target lithology section according to the basic seismic attribute analysis. For example, by performing attribute analysis on attributes such as instantaneous amplitude, instantaneous phase and instantaneous frequency, and analyzing related data volume and waveform clustering attributes, various seismic attributes which are sensitive to the target lithology section are obtained, and insensitive seismic attributes are removed.

The steps are realized through the following steps (1) to (2), and the steps comprise:

(1) and the terminal determines the corresponding target lithology section of the coring target according to the coring target.

In this step, the terminal determines a coring objective of the first production well, and determines a target lithology section corresponding to the coring objective according to the coring objective.

Prior to this step, a determination purpose needs to be determined. Wherein, the purpose of coring includes: horizon boundary coring, reservoir section coring, specific lithology section coring, and the like. Different coring purposes can be determined according to the work requirements. For example, if it is desired to take the interface between geological layers 1 and 2, then the purpose of coring the horizon interface is used. A lithologic section which is only a reservoir in a set of stratum is required to be selected, the lithologic section is characterized by a lithologic section top surface and a lithologic section bottom surface, and generally, the lithologic section top surface and the lithologic section bottom surface are lithologic mutational surfaces, and then the reservoir section is adopted for coring.

(2) And the terminal determines various seismic attributes of the target lithology section according to the properties of the target lithology section.

The seismic attributes include a three-transient attribute and other attributes derived from the three-transient attribute. Such as instantaneous amplitude properties, instantaneous phase properties, instantaneous frequency properties, etc. Different attribute types have different advantages for delineation of different geological features. For example, amplitude generic properties reflect changes in reflection coefficients and fluids in the reservoir pores, and can be used to directly describe one of the main attributes of reservoir changes. Frequency-generic properties reflect the thickness of the rock particles in the formation. When the thickness of the deposit particles is analyzed by frequency resonance, the lower the frequency, the thicker the deposit particles, and the higher the frequency, the higher the deposit particles. The phase class property is more sensitive to delineation of lithologic changes and can therefore be used to delineate boundaries of rock segments.

In step 204, the terminal determines the waveform response characteristics of the second geological model for each seismic attribute.

This step is similar to the process of determining the waveform response characteristic in step 201 (a3), and is not repeated here.

In step 205, the terminal determines at least one sensitivity attribute from the plurality of seismic attributes that the waveform response characteristic matches the actual waveform response characteristic.

In this step, the terminal compares the different waveform response characteristics with the waveform response characteristics of the actual geological significance corresponding to the waveform response characteristics, respectively. Responding to the matching of the waveform response characteristic of the actual geological meaning and the waveform response characteristic corresponding to the seismic attribute, and determining the seismic attribute as the sensitive attribute of the target lithology section by the terminal; and in response to the fact that the actual waveform response characteristic is not matched with the waveform response characteristic corresponding to the seismic attribute, the terminal rejects the seismic attribute.

In some embodiments, the terminal further determines the at least one sensitive attribute through an attribute determination model, and the responding terminal inputs the lithology section position and thickness corresponding to the second geological model into the attribute determination model; outputting, by the attribute determination model, at least one sensitive attribute of the target lithology segment. In the implementation mode, the at least one sensitive attribute is determined through the attribute determination model, so that the influence of subjective factors is avoided, and the accuracy of determining the at least one sensitive attribute is improved.

In step 206, the terminal labels the second geological model based on the attribute characterization of the at least one sensitive attribute to obtain a third geological model.

In this step, the terminal performs detail labeling on the second geological model based on the attribute characterization of the at least one sensitive attribute to obtain a third geological model for characterizing the target lithology layer. The process is realized by the following steps (1) to (3), and comprises the following steps:

(1) the terminal determines an attribute characterization for each of the sensitive attributes.

In this step, the terminal determines the attribute representation of different sensitive attributes on different lithological layers. For example, the most sensitive property to the instantaneous amplitude property is characterized by the characterization of reservoir and non-reservoir segments, and so on.

(2) The terminal determines the weight of each sensitive attribute according to the coring objective.

In this step, the terminal fuses different sensitive attributes. And the terminal determines the weights of different sensitive attributes according to different coring purposes, sets the weight of the sensitive attribute which can most represent the target lithology section to be the maximum, and properly reduces the probability of other sensitive attributes. For example, the at least one sensitive attribute is an instantaneous amplitude attribute X, an instantaneous phase attribute Y, and an instantaneous frequency attribute Z, and the fusion attribute H ═ aX + bY + cZ. Where a + b + c is 1, a is the weight of the instantaneous amplitude attribute X, b is the weight of the instantaneous phase attribute Y, and c is the weight of the instantaneous frequency attribute Z. If the lithology section corresponding to the coring purpose is a reservoir section, the largest difference between the reservoir section and the non-reservoir section is the physical properties of the rock stratum, such as different parameters of porosity, permeability and the like. The terminal sets the weight of the instantaneous amplitude attribute to maximum and the weights of the other sensitive attributes to smaller weights.

And for the fusion proportion of each sensitive attribute, the terminal can perform quantitative analysis and determine the fusion proportion of each sensitive attribute. The method comprises the steps that for coring of a reservoir interval, a terminal conducts proportional fusion on selected sensitive attributes according to reservoir lithology and physical property characteristics of a known well and geological knowledge-level geological rules of the area until an optimal solution is achieved; and for a certain lithology coring, the terminal performs proportional fusion according to lithology identification sensitive attributes and lithology boundary attribute detection until an optimal solution is reached. And after the sensitive attribute is determined, performing attribute optimization selection according to the characteristics of various attributes. In order to represent the amplitude strong and weak characteristics, the instantaneous amplitude attribute is modified into the root-mean-square attribute and substituted into the formula, and because the types of the attributes are more, the attribute subclass can be optimized according to the demand direction.

For example, the hilbert transform of the seismic traces yields a plurality of z (t), which is expressed as: z (t) ═ x (t) + iy (t). Where x (t) is the real part after Hilbert transform, and y (t) is the imaginary part after Hilbert transform.

The instantaneous amplitude attribute is then:

where A (t) is the instantaneous amplitude, x (t) is the real part after Hilbert transform, and y (t) is the imaginary part after Hilbert transform.

The instantaneous phase attribute is:

where θ (t) is the instantaneous phase, x (t) is the real part after Hilbert transform, and y (t) is the imaginary part after Hilbert transform.

The instantaneous frequency attribute is:

where f (t) is the instantaneous frequency and θ (t) is the instantaneous phase.

It should be noted that, because the value ranges of the instantaneous amplitude attribute, the instantaneous phase attribute and the instantaneous frequency attribute have large differences, normalization processing is required before fusion, and the value ranges are unified to the same order of magnitude, in order to avoid the influence of partial extrema, a smaller percentage can be specified when the upper and lower limits of the statistical value range are high and low to avoid the participation of the extrema, but the consideration is needed during fusion, so that the instantaneous amplitude attribute, the instantaneous phase attribute and the instantaneous frequency attribute after normalization processing are respectively obtained according to the percentage

And

the fused attribute is

Wherein H is the fused attribute, a is the instantaneous amplitude attribute

B is the instantaneous phase attribute

C is an instantaneous frequency attribute

The weight of (c). a. b and c are determined according to the coring purpose. For example, the coring requirement corresponding to the coring purpose is a top-bottom interface of the target lithology section, and since the instantaneous phase attribute can well measure the continuity of the same-phase axis on the seismic section, the value of b is μ, and μ belongs to (0.5, 1), the fusion attribute is:

wherein H (mu) is a fusion attribute,

in order to be an instantaneous amplitude attribute,

for the purpose of the instantaneous phase properties,

μ is a weight parameter for the instantaneous frequency attribute.

A similarity factor is determined for the instantaneous phase attribute and the fusion attribute. See the formula

Wherein, R is the similarity coefficient of the instantaneous phase attribute and the fusion attribute, i and j are the position points of the instantaneous phase attribute in the vertical and horizontal directions respectively, and theta_ijTo be instantaneousThe phase properties. Through the similarity coefficient formula, when the similarity coefficient is maximum, the corresponding weight parameter mu is determined, and then the final fusion result of H (mu) can be obtained.

It should be noted that, for any other type of determination method of the fusion attribute, the process is similar to the above process, and is not described herein again.

(3) And marking the second geological model by the terminal according to the weight of each sensitive attribute and the attribute representation of at least one sensitive attribute to obtain the third geological model.

And the terminal restrains the second geological model through attribute representation of different sensitive attributes to obtain a third geological model.

After the step, the terminal also carries out inversion constraint on the third geological model to obtain the third geological model with the top and bottom interfaces of the target lithologic section precisely depicted. For example, the data volume is processed with fidelity and amplitude-preserving high resolution to perform wave impedance inversion to obtain an inverted data volume, and the third geological model is constrained by the inverted data volume. And the terminal constrains the third geological model according to the coordinate corresponding relation between the inversion data volume and the third geological model. For example, the terminal converts both the inverted data volume and the third geological model into models in a geographic location coordinate system, and then constrains the third geological model with the inverted data volume for the corresponding location coordinates.

In step 207, the terminal performs depth calibration on the well zone where the first mining well is located based on the third geological model to obtain the coring depth of the target lithology section.

In the step, the terminal establishes an initial velocity model through data such as logging data, structural characteristics, stacking velocity and the like, adjusts the migration velocity layer by layer from shallow to deep in a data-driven mode, and enables the reflection homophase axes of the common reflection point gather to be leveled, and the process needs multiple iterations and gradually approaches to the real velocity. And performing prestack depth migration homing on the seismic data at the migration velocity finally finished by iteration, and obtaining a target layer coring depth range on the prestack depth migration data body through calibration of logging data.

And (4) obtaining a prestack depth migration data volume and obtaining a coring depth range by establishing a velocity volume. See fig. 8. Preparing a coring scheme according to the coring depth range: and (3) reducing the drilling speed after the second section of the target well section is drilled, strengthening the circulation of the drilling fluid when the predicted depth is approached, and beginning to core when the reverse rock debris is the debris limestone.

Fig. 9 is a block diagram illustrating a coring depth determining apparatus according to an exemplary embodiment, which is applied to a terminal, as shown in fig. 9, the apparatus including:

a forward modeling module 901, configured to perform geosteering forward modeling on a well zone where a first production well is located according to a first geological model to obtain a theoretical waveform response characteristic of a target lithology section, where the first production well is a drilling production well, the target lithology section is a lithology section corresponding to a coring objective, and the coring objective is a lithology of a core determined based on a use of the first production well;

an adjusting module 902, configured to adjust the first geological model according to the actual waveform response characteristics and the theoretical waveform response characteristics of the target lithology section under different influence factors, to obtain a second geological model;

a determining module 903, configured to determine at least one sensitive attribute of the target lithology section according to the second geological model;

a labeling module 904, configured to label the second geological model based on the attribute characterization of the at least one sensitive attribute, to obtain a third geological model;

and a depth calibration module 905, configured to perform depth calibration on the well region where the first mining well is located based on the third geological model, so as to obtain a coring depth of the target lithology section.

In some embodiments, the forward modeling module 901 includes:

a comparison unit for comparing the target depositional facies of the target lithology sections in the second plurality of production wells in the longitudinally stacked relationship;

the first determining unit is used for performing single-factor analysis on the target sedimentary facies corresponding to the plurality of second mining wells and determining the waveform response characteristics of the target sedimentary facies under different influence factors;

In some embodiments, the adjustment module 902 includes:

the adjusting unit is used for adjusting the positions and the thicknesses of different lithologic sections in the first geological model according to the actual waveform response characteristic and the theoretical waveform response characteristic to obtain a fourth geological model;

the adjusting unit is configured to, in response to a mismatch between the actual waveform response characteristic and the theoretical waveform response characteristic of the fourth geological model, continue to adjust the position and the thickness of different lithologic segments in the fourth geological model until the theoretical waveform response characteristic of the fourth geological model matches the actual waveform response characteristic, and obtain the second geological model.

In some embodiments, the determining module 903 comprises:

a fourth determining unit, configured to determine a waveform response characteristic of the second geological model under each seismic attribute, respectively;

and a fifth determining unit for determining at least one sensitivity attribute from the plurality of seismic attributes that the waveform response characteristic matches the actual waveform response characteristic.

In some embodiments, the third determining unit is configured to determine, according to the coring objective, a corresponding target lithology section of the coring objective; and determining a plurality of seismic attributes of the target lithology section according to the properties of the target lithology section.

In some embodiments, the determining module 903 comprises:

and a sixth determining unit, configured to output at least one sensitive attribute of the target lithology segment through the attribute determination model.

In some embodiments, the annotation module 904 comprises:

a seventh determining module 903 unit, configured to determine an attribute characterization of each sensitive attribute;

an eighth determining unit, configured to determine a weight of each of the sensitive attributes according to the coring purpose;

It should be noted that: in the above-described embodiments, when determining the coring depth, the coring depth determination apparatus is exemplified by only the division of the functional modules, and in practical applications, the function distribution may be completed by different functional modules according to needs, that is, the internal structure of the apparatus is divided into different functional modules, so as to complete all or part of the functions described above. In addition, the coring depth determination device and the coring depth determination method provided by the above embodiments belong to the same concept, and specific implementation processes thereof are described in the method embodiments and are not described herein again.

Fig. 10 shows a block diagram of a terminal 1000 according to an exemplary embodiment of the disclosure. The terminal 1000 can be: a smart phone, a tablet computer, an MP3 player (Moving Picture Experts Group Audio Layer III, motion video Experts compression standard Audio Layer 3), an MP4 player (Moving Picture Experts Group Audio Layer IV, motion video Experts compression standard Audio Layer 4), a notebook computer or a desktop computer. Terminal 1000 can also be referred to as user equipment, portable terminal, laptop terminal, desktop terminal, or the like by other names.

In general, terminal 1000 can include: a processor 1001 and a memory 1002.

Processor 1001 may include one or more processing cores, such as a 4-core processor, an 8-core processor, and so forth. The processor 1001 may be implemented in at least one hardware form of a DSP (Digital Signal Processing), an FPGA (Field-Programmable Gate Array), and a PLA (Programmable Logic Array). The processor 1001 may also include a main processor and a coprocessor, where the main processor is a processor for Processing data in an awake state, and is also referred to as a Central Processing Unit (CPU); a coprocessor is a low power processor for processing data in a standby state. In some embodiments, the processor 1001 may be integrated with a GPU (Graphics Processing Unit), which is responsible for rendering and drawing the content required to be displayed on the display screen. In some embodiments, the processor 1001 may further include an AI (Artificial Intelligence) processor for processing a computing operation related to machine learning.

Memory 1002 may include one or more computer-readable storage media, which may be non-transitory. The memory 1002 may also include high-speed random access memory, as well as non-volatile memory, such as one or more magnetic disk storage devices, flash memory storage devices. In some embodiments, a non-transitory computer readable storage medium in memory 1002 is used to store at least one instruction for execution by processor 1001 to implement the coring depth determination methods provided by method embodiments in the present disclosure.

In some embodiments, terminal 1000 can also optionally include: a peripheral interface 1003 and at least one peripheral. The processor 1001, memory 1002 and peripheral interface 1003 may be connected by a bus or signal line. Various peripheral devices may be connected to peripheral interface 1003 via a bus, signal line, or circuit board. Specifically, the peripheral device includes: at least one of radio frequency circuitry 1004, touch screen display 1005, camera 1006, audio circuitry 1007, positioning components 1008, and power supply 81009.

The peripheral interface 1003 may be used to connect at least one peripheral related to I/O (Input/Output) to the processor 1001 and the memory 1002. In some embodiments, processor 1001, memory 1002, and peripheral interface 1003 are integrated on the same chip or circuit board; in some other embodiments, any one or two of the processor 1001, the memory 1002, and the peripheral interface 1003 may be implemented on separate chips or circuit boards, which are not limited by this embodiment.

The Radio Frequency circuit 1004 is used for receiving and transmitting RF (Radio Frequency) signals, also called electromagnetic signals. The radio frequency circuitry 1004 communicates with communication networks and other communication devices via electromagnetic signals. The radio frequency circuit 1004 converts an electrical signal into an electromagnetic signal to transmit, or converts a received electromagnetic signal into an electrical signal. Optionally, the radio frequency circuit 1004 includes: an antenna system, an RF transceiver, one or more amplifiers, a tuner, an oscillator, a digital signal processor, a codec chipset, a subscriber identity module card, and so forth. The radio frequency circuitry 1004 may communicate with other control devices via at least one wireless communication protocol. The wireless communication protocols include, but are not limited to: metropolitan area networks, various generation mobile communication networks (2G, 3G, 4G, and 5G), Wireless local area networks, and/or WiFi (Wireless Fidelity) networks. In some embodiments, the radio frequency circuit 1104 may also include NFC (Near Field Communication) related circuits, which are not limited by this disclosure.

The display screen 1005 is used to display a UI (User Interface). The UI may include graphics, text, icons, video, and any combination thereof. When the display screen 1005 is a touch display screen, the display screen 1005 also has the ability to capture touch signals on or over the surface of the display screen 1005. The touch signal may be input to the processor 1001 as a control signal for processing. At this point, the display screen 1005 may also be used to provide virtual buttons and/or a virtual keyboard, also referred to as soft buttons and/or a soft keyboard. In some embodiments, display screen 1005 can be one, providing a front panel of terminal 1000; in other embodiments, display 1005 can be at least two, respectively disposed on different surfaces of terminal 1000 or in a folded design; in still other embodiments, display 1005 can be a flexible display disposed on a curved surface or on a folded surface of terminal 1000. Even more, the display screen 1005 may be arranged in a non-rectangular irregular figure, i.e., a shaped screen. The Display screen 1005 may be made of LCD (Liquid Crystal Display), OLED (Organic Light-Emitting Diode), and the like.

The camera assembly 1006 is used to capture images or video. Optionally, the camera assembly 1006 includes a front camera and a rear camera. Generally, a front camera is provided on a front panel of the control apparatus, and a rear camera is provided on a rear surface of the control apparatus. In some embodiments, the number of the rear cameras is at least two, and each rear camera is any one of a main camera, a depth-of-field camera, a wide-angle camera and a telephoto camera, so that the main camera and the depth-of-field camera are fused to realize a background blurring function, and the main camera and the wide-angle camera are fused to realize panoramic shooting and VR (Virtual Reality) shooting functions or other fusion shooting functions. In some embodiments, the camera assembly 1006 may also include a flash. The flash lamp can be a monochrome temperature flash lamp or a bicolor temperature flash lamp. The double-color-temperature flash lamp is a combination of a warm-light flash lamp and a cold-light flash lamp, and can be used for light compensation at different color temperatures.

The audio circuit 1007 may include a microphone and a speaker. The microphone is used for collecting sound waves of a user and the environment, converting the sound waves into electric signals, and inputting the electric signals into the processor 1001 for processing or inputting the electric signals into the radio frequency circuit 1004 for realizing voice communication. For stereo sound collection or noise reduction purposes, multiple microphones can be provided, each at a different location of terminal 1000. The microphone may also be an array microphone or an omni-directional acquisition microphone. The speaker is used to convert electrical signals from the processor 1001 or the radio frequency circuit 1004 into sound waves. The loudspeaker can be a traditional film loudspeaker or a piezoelectric ceramic loudspeaker. When the speaker is a piezoelectric ceramic speaker, the speaker can be used for purposes such as converting an electric signal into a sound wave audible to a human being, or converting an electric signal into a sound wave inaudible to a human being to measure a distance. In some embodiments, the audio circuit 1007 may also include a headphone jack.

A Location component 1008 is employed to locate a current geographic Location of terminal 1000 for purposes of navigation or LBS (Location Based Service). The Positioning component 1008 may be a Positioning component based on the Global Positioning System (GPS) in the united states, the beidou System in china, the graves System in russia, or the galileo System in the european union.

Power supply 1009 is used to supply power to various components in terminal 1000. The power source 1009 may be alternating current, direct current, disposable batteries, or rechargeable batteries. When the power source 1009 includes a rechargeable battery, the rechargeable battery may support wired charging or wireless charging. The rechargeable battery may also be used to support fast charge technology.

In some embodiments, terminal 1000 can also include one or more sensors 1010. The one or more sensors 1010 include, but are not limited to: acceleration sensor 1011, gyro sensor 1012, pressure sensor 1013, fingerprint sensor 1014, optical sensor 1015, and proximity sensor 1016.

Acceleration sensor 1011 can detect acceleration magnitudes on three coordinate axes of a coordinate system established with terminal 1000. For example, the acceleration sensor 1011 can be used to detect the components of the gravitational acceleration on three coordinate axes. The processor 1001 may control the touch display screen 1005 to display a user interface in a landscape view or a portrait view according to the gravitational acceleration signal collected by the acceleration sensor 1011. The acceleration sensor 1011 may also be used for acquisition of motion data of a game or a user.

The gyro sensor 1012 may detect a body direction and a rotation angle of the terminal 1000, and the gyro sensor 1012 and the acceleration sensor 1011 may cooperate to acquire a 3D motion of the user on the terminal 1000. From the data collected by the gyro sensor 1012, the processor 1001 may implement the following functions: motion sensing (such as changing the UI according to a user's tilting operation), image stabilization at the time of photographing, game control, and inertial navigation.

Pressure sensor 1013 may be disposed on a side frame of terminal 1000 and/or on a lower layer of touch display 1005. When pressure sensor 1013 is disposed on a side frame of terminal 1000, a user's grip signal on terminal 1000 can be detected, and processor 1001 performs left-right hand recognition or shortcut operation according to the grip signal collected by pressure sensor 1013. When the pressure sensor 1013 is disposed at a lower layer of the touch display screen 1005, the processor 1001 controls the operability control on the UI interface according to the pressure operation of the user on the touch display screen 1005. The operability control comprises at least one of a button control, a scroll bar control, an icon control, and a menu control.

The fingerprint sensor 1014 is used to collect a fingerprint of the user, and the processor 1001 identifies the user according to the fingerprint collected by the fingerprint sensor 1014, or the fingerprint sensor 1014 identifies the user according to the collected fingerprint. Upon identifying that the user's identity is a trusted identity, the processor 1001 authorizes the user to perform relevant sensitive operations including unlocking a screen, viewing encrypted information, downloading software, paying, and changing settings, etc. Fingerprint sensor 1014 can be disposed on the front, back, or side of terminal 1000. When a physical key or vendor Logo is provided on terminal 1000, fingerprint sensor 1014 can be integrated with the physical key or vendor Logo.

The optical sensor 1015 is used to collect the ambient light intensity. In one embodiment, the processor 1001 may control the display brightness of the touch display screen 1005 according to the intensity of the ambient light collected by the optical sensor 1015. Specifically, when the ambient light intensity is high, the display brightness of the touch display screen 1005 is increased; when the ambient light intensity is low, the display brightness of the touch display screen 1005 is turned down. In another embodiment, the processor 1001 may also dynamically adjust the shooting parameters of the camera assembly 1006 according to the intensity of the ambient light collected by the optical sensor 1015.

Proximity sensor 1016, also known as a distance sensor, is typically disposed on a front panel of terminal 1000. Proximity sensor 1016 is used to gather the distance between the user and the front face of terminal 1000. In one embodiment, when proximity sensor 1016 detects that the distance between the user and the front surface of terminal 1000 gradually decreases, processor 1001 controls touch display 1005 to switch from a bright screen state to a dark screen state; when proximity sensor 1016 detects that the distance between the user and the front of terminal 1000 is gradually increased, touch display screen 1005 is controlled by processor 1001 to switch from a breath-screen state to a bright-screen state.

Those skilled in the art will appreciate that the configuration shown in FIG. 10 is not intended to be limiting and that terminal 1000 can include more or fewer components than shown, or some components can be combined, or a different arrangement of components can be employed.

The embodiment of the present disclosure also provides a computer-readable storage medium, which is applied to a terminal, and in which at least one program code is stored, and the at least one program code is loaded and executed by a processor to implement the operations performed by the coring depth determination apparatus in the method of the foregoing embodiment.

The embodiments disclosed in the present application also provide an application program, wherein when the program code of the application program is executed by a processor of a server, the instructions executed in the coring depth determination in the method embodiments are realized.

It will be understood by those skilled in the art that all or part of the steps for implementing the above embodiments may be implemented by hardware, or may be implemented by a program instructing relevant hardware, and the program may be stored in a computer-readable storage medium, and the above-mentioned storage medium may be a read-only memory, a magnetic disk or an optical disk, etc.

Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure herein. This disclosure is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.

It will be understood that the present disclosure is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims

1. A coring depth determination method, the method comprising:

2. The method of claim 1, wherein performing geosteering forward modeling on the well zone in which the first production well is located according to the first geological model to obtain theoretical waveform response characteristics of the target lithology section comprises:

3. The method of claim 1, wherein the adjusting the first geological model according to the actual waveform response characteristics and the theoretical waveform response characteristics of the target lithology section under different influence factors to obtain a second geological model comprises:

4. The method of claim 1, wherein determining at least one sensitive attribute of the target lithology section from the second geological model comprises:

determining various seismic attributes to be detected;

5. The method of claim 4, wherein determining the plurality of seismic attributes to be detected comprises:

6. The method of claim 1, wherein determining at least one sensitive attribute of the target lithology section from the second geological model comprises:

7. The method of claim 1, wherein the tagging the second geological model based on the attribute characterization of the at least one sensitive attribute results in a third geological model comprising:

determining attribute characterization of each sensitive attribute;

and marking the second geological model according to the weight of each sensitive attribute and the attribute representation of at least one sensitive attribute to obtain the third geological model.

8. A coring depth determining apparatus, the apparatus comprising:

9. A terminal, characterized in that the terminal comprises a processor and a memory; the memory stores at least one program code for execution by the processor to implement the coring depth determination method of any one of claims 1 through 7.

10. A computer-readable storage medium, characterized in that the storage medium stores at least one program code for execution by a processor to implement the coring depth determination method of any one of claims 1 through 7.