CN113495304A - Three-dimensional modeling method for reservoir microfractures - Google Patents
Three-dimensional modeling method for reservoir microfractures Download PDFInfo
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Abstract
The invention provides a three-dimensional modeling method for reservoir microfractures. The three-dimensional modeling method comprises the following steps: step S10: establishing a three-dimensional construction model; step S15: carrying out gridding treatment on the three-dimensional structure model; step S20: establishing a single-well micro-crack development model; step S30: coarsening data in the single-well micro-crack development model into a meshed three-dimensional structural model to obtain micro-crack coarsening data in the three-dimensional structural model; step S35: judging, namely judging whether the error between the micro-fracture coarsening data in the three-dimensional structural model and the data in the single-well micro-fracture development model is less than or equal to 5%, if so, executing the step S40, and otherwise, repeatedly executing the steps S15 and S30; step S40: acquiring factors influencing the development of the microcracks and determining the spatial distribution trend of the microcracks; step S50: and establishing a three-dimensional model of the micro-crack development degree. The technical scheme of the invention can determine the development and distribution conditions of the microcracks.
Description
Technical Field
The invention relates to the technical field of oil and gas exploration and development, in particular to a three-dimensional modeling method for a reservoir microcrack.
Background
Shale gas is used as unconventional clean energy and becomes an exploration and development hotspot due to the abundant resource amount and the successful benefit large-scale development of the United states. Shale is able to become a reservoir, originating from a system of pore cracks that develop extensively within. Reservoir formation fractures can be roughly classified into the following three categories according to their scale rank: large scale fractures, small scale fractures and microfractures. The length scale of the large-scale crack is generally in the hundred meter level and above, the large-scale crack can be identified through seismic data, a deterministic modeling method is mainly adopted, the method is relatively mature, and the reliability of a large-scale crack model is good; the length scale of the small-scale cracks is in the order of centimeter-meter-tens of meters, the distribution of the small-scale cracks is generally controlled by a rock mechanical layer, the small-scale cracks can be identified through rock cores and logging information, a random modeling method is adopted, namely, the well point cracks are used as hard data, seismic attributes, fault distance, tectonic curvature, production dynamic information and the like are used as crack distribution trend constraints among wells, a small-scale crack density model is established, and a small-scale crack network model and an attribute model are established by combining geological knowledge on the basis. The length scale of the microcracks is in the centimeter level and below, the distribution of the microcracks is generally controlled by the microstructure in the rock mass, wherein the microcracks with larger scale can be identified by the rock core, and the microcracks with small scale need to be identified under the mirror. The shale reservoir microcracks not only provide a storage space for shale gas, but also are main channels for communicating micro pores with macro cracks, the quality of the reservoir is directly influenced, and the research on the shale microcracks has important significance on the exploration and development of the shale gas. At present, a method based on earthquake and logging data cannot effectively represent a core scale and a fine-micro natural fracture system below the core scale, and the development and distribution of the fine-micro natural fracture system can have extremely important influence on macroscopically improving the seepage characteristic of a shale reservoir, so that the development and distribution conditions of the microcracks of the whole reservoir need to be analyzed through three-dimensional modeling of the microcracks below the core scale.
Disclosure of Invention
The invention mainly aims to provide a three-dimensional modeling method for reservoir microfractures, so as to clarify the development and distribution conditions of the reservoir microfractures.
In order to achieve the above object, the present invention provides a three-dimensional modeling method for reservoir microfractures, the three-dimensional modeling method comprising: step S10: establishing a three-dimensional construction model of a target reservoir of a target well region; step S15: carrying out gridding treatment on the three-dimensional construction model to obtain a gridded three-dimensional construction model; step S20: establishing a single-well microcrack development model of a target well region; step S30: coarsening data in the single-well microcrack development model into a meshed three-dimensional structural model to obtain microcrack coarsening data in the three-dimensional structural model; step S35: a judging step, wherein the judging step comprises the steps of judging whether the error between the micro-crack coarsening data in the three-dimensional structural model and the data in the single-well micro-crack development model is less than or equal to 5%, if so, executing the step S40, and if not, repeatedly executing the steps S15 and S30; step S40: obtaining factors influencing the development of the microcracks, and determining the spatial distribution trend of the microcracks of the target well region according to data in a single-well microcrack development model; step S50: and (3) taking the micro-crack coarsening data in the three-dimensional structural model as hard data, calling the spatial distribution trend of the micro-cracks of the target well region, and establishing a three-dimensional model of the development degree of the micro-cracks.
Further, step S10 includes step S16 of building a three-dimensional structure model from the horizon model, the fault model, and the real well stratification data of the target reservoir of the target well zone.
Further, before step S16, step S10 further includes step S11 of selecting a target well and obtaining horizon data and fault data in a seismic interpretation result of the target well; and a step S12 of selecting the target reservoir and obtaining the drilling data, the logging data and the oil testing data of the target reservoir.
Further, after step S11 and step S12, step S10 further includes: step S13: establishing a fault model of the target reservoir of the target well area according to fault data in the seismic interpretation result and fault data encountered in the real drilling process, wherein the fault data encountered in the real drilling process is the fault data obtained in the step S12; step S14: and on the basis of the horizon data in the seismic interpretation result, correcting the horizon data in the seismic interpretation result through the real drilling well layered data, and establishing a horizon model of a target reservoir of a target well region.
Further, in step S12, the well data of the target reservoir includes well-head coordinates, well trajectory and real well stratification data.
Further, step S20 includes: step S21: performing borehole wall coring on a target reservoir of a target well zone to obtain a rock core sample; step S25: obtaining the face porosity of the microcracks of the core sample; step S26: and establishing a single-well microcrack development model according to the face porosity of the microcracks.
Further, after step S21, step S20 further includes step S22 of performing a scanning electron microscope experiment on the core sample using a scanning electron microscope to obtain a scanning electron microscope image of the core sample.
Further, step S20 includes step S23 of binarizing the scanning electron microscope image.
Further, after step S23 and before step S25, step S20 further includes step S24 of performing gridding processing on the binarized sem image.
Further, in step S30, data in the development model of the micro fractures of the single well is coarsened into a gridded three-dimensional structural model using any one of an arithmetic mean algorithm, a geometric mean algorithm, and a logarithmic distribution algorithm.
Further, when the data in the single well micro-fracture development model conforms to a normal distribution, an arithmetic mean algorithm is employed.
Further, in step S40, the three-dimensional modeling method includes determining factors that affect the development of the microfractures according to the seismic interpretation result data volume of the target well region and the well log data of the target reservoir.
Further, in step S40, the three-dimensional modeling method further includes performing geostatistical variogram analysis on the data in the single-well microcrack development model, determining a primary and secondary direction, a variation range and a lump value, and determining a spatial distribution trend of the target well region microcracks according to the primary and secondary directions, the variation range and the lump value.
Further, in step S50, a three-dimensional model of the development degree of the microcracks is established with the SEGY data volume in the seismic interpretation result of the selected target well region or the factors influencing the microcrack development determined in step S40 as constraint conditions.
Further, the SEGY data volume in the seismic interpretation result of the target well region comprises a depth domain data volume, a time domain data volume and a time-depth conversion model.
By applying the technical scheme of the invention, the spatial distribution trend of data in the development model of the microcracks of each single well in the target well area is called, the coarsened data of the microcracks in the three-dimensional structural model is taken as hard data, the SEGY data body in the earthquake explanation result of the selected target well area or the determined most main factor influencing the development of the microcracks is taken as a constraint condition, and the three-dimensional model of the development degree of the microcracks of the reservoir is established.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this application, illustrate embodiments of the invention and, together with the description, serve to explain the invention and not to limit the invention. In the drawings:
FIG. 1 shows a flow diagram of an embodiment of a method of three-dimensional modeling of reservoir microfractures according to the invention;
FIG. 2 illustrates a three-dimensional formation model of a target reservoir obtained according to the three-dimensional modeling method of FIG. 1;
FIG. 3a shows a scanning electron microscope image obtained according to the three-dimensional modeling method of FIG. 1;
FIG. 3b shows the SEM image of FIG. 3a after gray level thresholding to reflect microscopic pores;
FIG. 3c shows the image of FIG. 3b after color labeling of the microscopic pores; and
FIG. 4 shows a cloud of the development of a small layer of microfractures from a three-dimensional model of the development of reservoir microfractures created according to the three-dimensional modeling method of FIG. 1.
Detailed Description
It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict. The present invention will be described in detail below with reference to the embodiments with reference to the attached drawings.
It is noted that, unless otherwise indicated, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.
In the present invention, unless specified to the contrary, use of the terms of orientation such as "upper, lower, top, bottom" or the like, generally refer to the orientation as shown in the drawings, or to the component itself in a vertical, perpendicular, or gravitational orientation; likewise, for ease of understanding and description, "inner and outer" refer to the inner and outer relative to the profile of the components themselves, but the above directional words are not intended to limit the invention.
As shown in fig. 1, in an embodiment of the present invention, the method for three-dimensional modeling of reservoir microfractures includes:
step S10: establishing a three-dimensional construction model of a target reservoir of a target well region;
step S15: carrying out gridding treatment on the three-dimensional construction model to obtain a gridded three-dimensional construction model;
step S20: establishing a single-well microcrack development model of a target well region;
step S30: coarsening data in the single-well microcrack development model into a meshed three-dimensional structural model to obtain microcrack coarsening data in the three-dimensional structural model;
step S35: a judging step, wherein the judging step comprises the steps of judging whether the error between the micro-crack coarsening data in the three-dimensional structural model and the data in the single-well micro-crack development model is less than or equal to 5%, if so, executing the step S40, and if not, repeatedly executing the steps S15 and S30;
step S40: acquiring the most main factors influencing the development of the microcracks, and determining the spatial distribution trend of the microcracks of the target well region according to data in a single-well microcrack development model;
step S50: and (3) taking the micro-crack coarsening data in the three-dimensional structural model as hard data, calling the spatial distribution trend of the micro-cracks of the target well region, and establishing a three-dimensional model of the development degree of the micro-cracks.
According to the method, a three-dimensional structure model of a target reservoir is established, the geological structure of the target reservoir of a target well region can be simulated through the three-dimensional structure model, the three-dimensional structure model is gridded, and a foundation is laid for subsequent data coarsening; the method comprises the following steps of (1) simulating the microcrack development condition of a target reservoir of a single well by establishing a microcrack development model of the single well of a target well region; the single-well microcrack development model is coarsened into the gridded three-dimensional structural model, coarsened data of the single-well microcrack development model in the three-dimensional structural model are obtained, the geological structure of the target well region and the microcrack development condition of the target reservoir region can be combined, and the development condition of the microcrack in the geological structure of the target reservoir region of the target well region can be reflected through the simulation process; the error between the coarsened data and the data in the single-well microcrack development model is controlled within 5 percent, so that the accuracy of the coarsened data can be ensured, and the reliability of the three-dimensional model can be improved; by analyzing factors influencing the development of the microcracks, the main factors with strongest correlation with the development of the microcracks can be obtained; the method comprises the steps of analyzing the spatial distribution trend of data in a single-well microcrack development model in a target well region, and obtaining the spatial distribution trend and rule of microcracks in the target well region; the development degree three-dimensional model of the microcracks is established by combining the coarsened three-dimensional structural model data, the most main factors influencing the microcrack development and the spatial distribution trend and rule of the microcracks in the target well region.
The invention and the embodiment of the invention provide a three-dimensional modeling method for the microcracks below the core scale of the shale reservoir, and the method can analyze the development and distribution conditions of the microcracks of the whole reservoir, is beneficial to realizing the purposes of evaluating the reservoir properties in the early development stage and scientifically developing oil and gas, and has important significance for the exploration and development of shale gas.
Preferably, the gridding process performed on the three-dimensional structure model in step S15 is performed according to the scope of the research region, and the grid is divided into more and more fine grids as the scope of the research region is reduced (e.g., the scope is reduced from the well region to the platform and then to the single well).
Specifically, step S10 includes the steps of:
step S11: selecting a target area, and acquiring an SEGY (seismic of Exploration seismic data) data body, horizon data and fault data in the seismic interpretation result of the target well area;
step S12: selecting a target reservoir in the target well region, and acquiring drilling data, logging data and oil testing data of the target reservoir;
preferably, the well data of the target reservoir include well head coordinates, well track and the real well stratification data.
Step S13: establishing a fault model according to fault data in the seismic interpretation result obtained in the step S11 and fault data encountered in the actual drilling process, wherein the fault data encountered in the actual drilling process are fault data obtained from the drilling data, the logging data and the oil testing data of the target reservoir obtained in the step S12; in the step S13, the fault data encountered in the actual drilling process has a certain correction effect on the fault data in the seismic interpretation result, and the fault data in the seismic interpretation result can be corrected, so that the established fault model can more accurately reflect the fault distribution condition of the target well region.
Step S14: on the basis of the horizon data in the seismic interpretation result obtained in the step S11, correcting the horizon data in the seismic interpretation result through the real drilling well hierarchical data to establish a horizon model; in the step S14, the actual drilling layered data has a certain correction effect on the horizon data in the seismic interpretation result, so that the established horizon model can more accurately reflect the horizon condition of the target well region.
The method comprises the steps of establishing a horizon model and a fault model of a target reservoir of a target well area, correcting the horizon model and the fault model by using real well stratification data, and combining the horizon model and the fault model to form a three-dimensional structure model of the target reservoir.
Step S16: and establishing a three-dimensional construction model according to the horizon model, the fault model and the real drilling well hierarchical data of the target reservoir of the target well area. That is, a three-dimensional structural model (as shown in fig. 2) combined with the well seismic data of the target reservoir of the target well zone is established by using the real drilling well hierarchical data through the fault model and the horizon model. The three-dimensional structure model created in step S16 described above can simulate the geological structure of the target reservoir of the target well.
In the above steps, the horizon model, the fault model and the three-dimensional structure model are established based on the SEGY data volume, the horizon data and the fault data in the seismic interpretation result of the target well region, and the drilling data, the logging data and the oil testing data of the target reservoir layer of the target well region.
In step S20, a single-well micro-fracture development model needs to be established according to the sem image of the core sample.
As shown in fig. 3a to 3c, in the embodiment of the present invention, the step S20 includes the following steps:
step S21: performing borehole wall coring on the target reservoir of the target well zone to obtain a rock core sample;
preferably, according to the size, shape and structural development condition of the target well zone, at least the exploratory well distribution at the important boundary and structural development position of the target well zone is ensured, sidewall coring is performed at the well section where the target reservoir of the exploratory well is located, and a core sample is ensured to be in each small layer.
Step S22: performing a scanning electron microscope experiment on the core sample by using a scanning electron microscope to obtain a scanning electron microscope image of the core sample;
preferably, a common scanning electron microscope and an argon ion polishing emission scanning electron microscope experiment are performed on all core samples obtained from the target well zone, so as to obtain a high-resolution scanning electron microscope image (as shown in fig. 3 a) of the core sample, and lay the foundation for obtaining the face porosity of the microcracks of the core sample.
Step S23: carrying out binarization processing on the scanning electron microscope image;
preferably, the scanning electron microscope image of the core sample is subjected to binarization processing, and the specific processing steps are as follows: firstly, setting the gray value of a pixel point on the scanning electron microscope image to be 0 or 255, so that the scanning electron microscope image presents a black-and-white effect and becomes a gray image; and then, selecting a gray threshold value to enable the gray image to still reflect the microscopic pore characteristics of the core sample.
Preferably, the gray threshold can be adjusted according to actual needs.
Preferably, the selecting step of the threshold value is: firstly, determining a reasonable threshold, wherein in the gray level image, the part larger than the threshold is a rock skeleton, the part smaller than the threshold is a micro pore, and finally determining the pore gray level threshold of each core sample by adopting a mode of selecting for many times and comparing the processed scanning electron microscope image with the original scanning electron microscope image. By selecting the gray threshold, the gray image can still reflect the overall and local characteristics of the scanning electron microscope image. In an embodiment of the invention, as shown in fig. 3b, the selected gray level threshold is 5.
Preferably, the microcracks are determined mainly by microscopic recognition, and mainly by pore morphology, fillers, and the like.
Step S24: carrying out gridding processing on the scanning electron microscope image after the binarization processing;
in the above steps, the gridding processing is performed on the scanning electron microscope image, which is beneficial to the subsequent analysis of the scanning electron microscope image.
Step S25: obtaining the face porosity of the microcracks of the core sample;
preferably, the microscopic porosity of the surface of the micro-pores of the different sections of each core sample is obtained by a "gridding method", and the average value is the surface porosity of the core sample. Specifically, according to the morphological characteristics of the microcracks, marking the microcracks on a scanning electron microscope image subjected to binarization processing by using orange color (as shown in fig. 3c, an orange part is represented by an area with the same color indicated by a reference mark "a" in fig. 3 c), and calculating the proportion of the orange area to the total area of the core sample represented by the scanning electron microscope image by using a grid method, namely the face porosity of the microcracks of the core sample. Through the steps, the total surface porosity of the microcracks can be obtained, and the proportion of the surface porosity of the microcracks to the total surface porosity of the micro pores can also be obtained.
Preferably, the micro pores include inorganic pores, organic pores, micro cracks, and the like.
Step S26: and establishing a single-well microcrack development model according to the face porosity of the microcracks.
Preferably, the development degree of the small-layer microcracks is represented by the face porosity of the microcracks, and a single-well microcrack development model is established according to the development degree of the microcracks.
In step S20, the development model of the microcracks of the single well of the target well zone may be established only according to the sem image of the single well in the target well zone that has undergone the sidewall coring and obtained the core sample and the sem image of the core sample, or may be established after the sem image of the core sample is obtained by performing the sidewall coring on the single well in the target well zone.
Specifically, step S30 is: coarsening data (namely the face porosity of the single-well microcracks of the target well region) in the single-well microcrack development model of the target well region into the gridded three-dimensional structural model of the target well region to obtain coarsened data of the microcracks; step S35 is: checking the fitting degree of the coarsening data of the microcracks in the three-dimensional structural model and the data in the single-well microcrack development model, judging whether the error between the coarsening data of the microcracks in the three-dimensional structural model and the data in the single-well microcrack development model is less than or equal to 5%, if so, executing the step S40, and if not, repeatedly executing the step S15 and the step S30 until the error between the coarsening data of the microcracks in the three-dimensional structural model and the data in the single-well microcrack development model is less than or equal to 5%, so as to ensure that the coarsening data of the microcracks in the three-dimensional structural model and the data in the single-well microcrack development model have higher fitting degree.
In step S30, the developing models of microcracks in all the individual wells of the target well are coarsened into the gridded three-dimensional structural model of the target well; in step S35, it is determined whether or not the error between the coarsening data of the micro fractures in the three-dimensional structural model and the data of the micro fracture development models of all the single wells is 5% or less.
Preferably, the error is calculated by: and the coarsening data of the microcracks in the three-dimensional structural model and the data in the single-well microcrack development model account for the difference value in a certain distribution interval.
Preferably, data in the micro-crack development model of each single well of the target well region is coarsened into the three-dimensional structure model of the target well region subjected to the gridding treatment by adopting any one algorithm of an arithmetic mean algorithm, a geometric mean algorithm, a logarithmic distribution algorithm and the like.
Preferably, an algorithm is employed that minimizes the error between the micro-fracture coarsening data in the three-dimensional formation model and the data in the single-well micro-fracture development model to ensure that the above-mentioned error is within 5%; specifically, if the lateral continuity of the data in the development model of the microcracks of each single well of the target well region is strong and deviates to normal distribution without conforming to normal distribution, a geometric mean algorithm is adopted; if the data has strong transverse continuity and conforms to normal distribution, adopting an arithmetic mean algorithm; if the data do not conform to normal distribution and the heterogeneity is strong, a logarithmic distribution algorithm is adopted.
Specifically, in step S40, the three-dimensional modeling method includes a step of determining the most significant factors affecting the development of the microcracks according to the seismic interpretation result data volume of the target well, such as a TOC (Total Organic Carbon) data volume, and the log data of the target reservoir of the target well, such as porosity.
Preferably, a linear regression analysis is carried out by combining the seismic interpretation result data body of the target well region and the logging data of the target reservoir of the target region, and the most main factors influencing the development of the microcracks are determined; through the steps, the main factor with the strongest correlation with the development of the microcracks can be obtained.
Specifically, in step S40, the three-dimensional modeling method further includes performing geostatistical variogram analysis on data in the single-well microcrack development model of the target well, determining a primary and secondary direction, a variable range, and a block value, and determining a spatial distribution trend and a law of the microcracks of the target well according to the primary and secondary direction, the variable range, and the block value.
Preferably, in the case that the data in the development model of the microcracks of the single well of the target well region and the microcrack coarsening data in the three-dimensional structural model are both relatively small, the primary and secondary directions, the variation and the block gold value of the data of the development degree of the microcracks can be indirectly determined through the data of the most important factors influencing the development of the microcracks, which are relatively rich in data, so as to determine the spatial distribution trend and the rule of the microcracks of the target well region.
In the embodiment of the present invention, step S50 is: and calling the spatial distribution trend and rule of the microcracks of the target well region, taking the microcrack coarsening data in the three-dimensional structural model as hard data, and taking an SEGY data body in an earthquake explanation result or the most main factor which is determined in the step S40 and influences the microcrack development as a constraint condition to establish a three-dimensional model of the microcrack development degree of the target region. The cloud picture of the development degree of the microcracks of any small layer can be obtained through the three-dimensional model of the development degree of the microcracks (as shown in fig. 4, fig. 4 shows the cloud picture of the development degree of the microcracks of a certain small layer obtained through the three-dimensional model of the development degree of the microcracks), the development and distribution conditions of the microcracks of a target reservoir zone of the target well zone can be determined through the cloud picture of the development degree of the microcracks, the purposes of evaluating the reservoir properties in the early development stage and scientifically developing oil and gas are facilitated, and the cloud picture of the development degree of the microcracks has important significance for the exploration and development of oil and gas.
Preferably, the SEGY data volume in the seismic interpretation result comprises a depth domain data volume, a time domain data volume and a time-depth conversion model.
Preferably, the most major factors (such as TOC, porosity and the like) influencing the microcrack development can be acquired through seismic interpretation results of the target well region and well logging data of a single well, and the most major factors influencing the microcrack development are taken as constraint conditions, so that the three-dimensional development degree of the microcracks in the range of the target well region can be better represented.
From the above description, it can be seen that the above-described embodiments of the present invention achieve the following technical effects: according to the technical scheme, a horizon model, a fault model and a three-dimensional structure model are established through an SEGY data body, horizon data and fault data in an earthquake interpretation result of a target well area and drilling data, logging data and oil testing data of a target reservoir layer of the target well area; obtaining the face porosity of the microcracks of the core sample through the obtained core sample of the target reservoir of the target well zone and the scanning electron microscope image of each core sample, adopting the face porosity of the microcracks of the core sample to represent the development degree of the microcracks, and establishing a development model of the microcracks of each single well according to the development degree of the microcracks; then, coarsening data in the development model of the microcracks of the single well into the three-dimensional structural model subjected to gridding treatment, and ensuring that the error between the coarsening data of the microcracks in the three-dimensional structural model and the data in the development model of the microcracks of each single well is less than or equal to 5%; secondly, determining the most main factors of the target well region influencing the development of the microcracks and the spatial distribution trend and the rule of the microcracks of the target well region; finally, calling the spatial distribution trend of the microcracks of the target well region, taking the coarsening data of the microcracks in the three-dimensional structural model as hard data, and taking an SEGY data body in the selected seismic interpretation result of the target well region or the determined most main factor influencing the microcrack development as a constraint condition to establish a three-dimensional model of the development degree of the reservoir microcracks; the three-dimensional modeling method of the reservoir microcracks can be used for determining the development and distribution conditions of the microcracks of the target reservoir of the target well region, is beneficial to achieving the purposes of evaluating the reservoir properties in the early development stage and scientifically developing oil and gas, and has important significance for the exploration and development of the oil and gas.
It is to be understood that the above-described embodiments are only a few, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention. It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments according to the present application. As used herein, the singular is intended to include the plural unless the context clearly dictates otherwise, and it should be further understood that the terms "comprises" and/or "comprising," when used in this specification, specify the presence of features, steps, operations, devices, components, and/or combinations thereof.
It should be noted that the terms "first," "second," and the like in the description and claims of this application and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the application described herein are capable of operation in sequences other than those illustrated or described herein.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (15)
1. A three-dimensional modeling method of reservoir microfractures, the three-dimensional modeling method comprising:
step S10: establishing a three-dimensional construction model of a target reservoir of a target well region;
step S15: carrying out gridding treatment on the three-dimensional construction model to obtain a gridded three-dimensional construction model;
step S20: establishing a single-well microcrack development model of the target well region;
step S30: coarsening data in the single-well microcrack development model into the gridded three-dimensional structural model to obtain microcrack coarsening data in the three-dimensional structural model;
step S35: a judging step, wherein the judging step comprises the steps of judging whether the error between the micro-crack coarsening data in the three-dimensional structural model and the data in the single-well micro-crack development model is less than or equal to 5%, if so, executing the step S40, and if not, repeatedly executing the step S15 and the step S30;
step S40: obtaining factors influencing the development of the microcracks, and determining the spatial distribution trend of the microcracks of the target well region according to data in the development model of the microcracks of the single well;
step S50: and taking the micro-crack coarsening data in the three-dimensional structural model as hard data, calling the spatial distribution trend of the micro-cracks of the target well region, and establishing a three-dimensional model of the development degree of the micro-cracks.
2. The three-dimensional modeling method according to claim 1, wherein the step S10 includes a step S16 of building the three-dimensional construction model from a horizon model, a fault model and real well stratification data of a target reservoir of a target well zone.
3. The three-dimensional modeling method according to claim 2, wherein before the step S16, the step S10 further includes a step S11 of selecting a target well region and obtaining horizon data and fault data in a seismic interpretation result of the target well region; and S12, selecting a target reservoir and obtaining the drilling data, the logging data and the oil testing data of the target reservoir.
4. The three-dimensional modeling method according to claim 3, wherein after said step S11 and said step S12, said step S10 further includes:
step S13: establishing a fault model of a target reservoir of a target well region according to fault data in the seismic interpretation result and fault data encountered in the real drilling process, wherein the fault data encountered in the real drilling process are the fault data obtained in the step S12;
step S14: and on the basis of the horizon data in the seismic interpretation result, modifying the horizon data in the seismic interpretation result through real well layered data to establish a horizon model of a target reservoir of a target well region.
5. The three-dimensional modeling method according to claim 3, wherein in said step S12, the well data of said target reservoir includes well-head coordinates, well trajectory and said real well stratification data.
6. The three-dimensional modeling method according to any one of claims 1 to 5, wherein said step S20 includes:
step S21: performing borehole wall coring on a target reservoir of the target well zone to obtain a core sample;
step S25: obtaining the face porosity of the microcracks of the core sample;
step S26: and establishing a single-well microcrack development model according to the face porosity of the microcracks.
7. The three-dimensional modeling method according to claim 6, characterized in that after step S21, step S20 further comprises a step S22 of performing a scanning electron microscope experiment on the core sample using a scanning electron microscope to obtain a scanning electron microscope image of the core sample.
8. The three-dimensional modeling method according to claim 7, characterized in that said step S20 further includes a step S23 of binarizing said scanning electron microscope image.
9. The three-dimensional modeling method according to claim 8, wherein after said step S23 and before said step S25, said step S20 further includes a step S24 of gridding the binarized sem image.
10. The three-dimensional modeling method according to any one of claims 1 to 5, wherein in step S30, data in the single-well microcrack development model is coarsened into the gridded three-dimensional formation model using any one of arithmetic mean algorithm, geometric mean algorithm, and logarithmic distribution algorithm.
11. The three-dimensional modeling method of claim 10, wherein the arithmetic mean algorithm is employed when data in the developmental model of microfractures for a single well conforms to a normal distribution.
12. The three-dimensional modeling method according to any one of claims 1 to 5, wherein in said step S40, said three-dimensional modeling method includes determining factors affecting microcrack development from seismic interpretation result data volume of said target well region and well log data of target reservoir.
13. The three-dimensional modeling method according to any one of claims 1-5, further comprising performing geostatistical variogram analysis on data in the development model of the single-well microcracks, determining a primary and secondary direction, a variation and a block value, and determining a spatial distribution trend of the target well region microcracks according to the primary and secondary direction, the variation and the block value in step S40.
14. The three-dimensional modeling method according to any one of claims 1 to 5, wherein in step S50, a three-dimensional model of the development degree of microcracks is established with the selected SEGY data volume in seismic interpretation of the target well region or the factors influencing microcrack development determined in step S40 as constraints.
15. The three-dimensional modeling method of claim 14, wherein the SEGY data volume in the seismic interpretation of the target well zone comprises a depth domain data volume, a time domain data volume and a time-depth conversion model.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20120221306A1 (en) * | 2009-04-08 | 2012-08-30 | Schlumberger Technology Corporation | Multiscale digital rock modeling for reservoir simulation |
| WO2016041189A1 (en) * | 2014-09-19 | 2016-03-24 | 杨顺伟 | Method for evaluating shale gas reservoir and seeking desert area |
| CN105842751A (en) * | 2016-03-17 | 2016-08-10 | 成都创源油气技术开发有限公司 | Shale reservoir crack evaluation method |
| CN107462937A (en) * | 2017-10-09 | 2017-12-12 | 中国石油集团川庆钻探工程有限公司地球物理勘探公司 | Fracture spacing new 3 D geological model construction method after shale gas reservoir pressure |
| US20180232950A1 (en) * | 2015-09-24 | 2018-08-16 | Halliburton Energy Services, Inc. | Simulating fractured reservoirs using multiple meshes |
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20120221306A1 (en) * | 2009-04-08 | 2012-08-30 | Schlumberger Technology Corporation | Multiscale digital rock modeling for reservoir simulation |
| WO2016041189A1 (en) * | 2014-09-19 | 2016-03-24 | 杨顺伟 | Method for evaluating shale gas reservoir and seeking desert area |
| US20180232950A1 (en) * | 2015-09-24 | 2018-08-16 | Halliburton Energy Services, Inc. | Simulating fractured reservoirs using multiple meshes |
| CN105842751A (en) * | 2016-03-17 | 2016-08-10 | 成都创源油气技术开发有限公司 | Shale reservoir crack evaluation method |
| CN107462937A (en) * | 2017-10-09 | 2017-12-12 | 中国石油集团川庆钻探工程有限公司地球物理勘探公司 | Fracture spacing new 3 D geological model construction method after shale gas reservoir pressure |
Non-Patent Citations (5)
| Title |
|---|
| 吕雪祥;: "非常规油气藏地质建模与数值模拟一体化技术研究", 中国煤炭地质, no. 08 * |
| 张亚春;尹太举;周文;: "在蚂蚁属性体约束下的裂缝建模方法研究", 长江大学学报(自科版), no. 14 * |
| 张小平等: "新场气田裂缝孔隙性储层地质建模研究", 石油天然气学报（江汉石油学院学报）, pages 41 - 44 * |
| 杨恒林等: "页岩气储层工程地质力学一体化技术进展与探讨", 石油钻探技术 * |
| 赵力彬等: "库车坳陷克深2气藏裂缝—孔隙型砂岩储层地质建模方法", 天然气工业 * |
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