阅读说明：本技术 一种基于人工智能的气藏单井控制面积劈分方法 (Gas reservoir single well control area splitting method based on artificial intelligence ) 是由 谭晓华 李劲涵 李晓平 王坤 毛正林 杨豪 于 2020-08-10 设计创作，主要内容包括：本发明涉及一种基于人工智能的气藏单井控制面积劈分方法,属于油气藏储量评价领域；为了解决现今气藏气井单井控制面积计算误差较大,流程冗杂等问题；其技术方案是：第一,准备气藏及气井静态及动态参数,利用三角剖分算法,绘制气藏区块边界曲线；建立气藏物性的渗透率、储层有效厚度、孔隙度二维矩阵；基于差异化竞争区域生长图像分割算法,计算单井竞争系数；结合单井竞争系数,进行气藏单井控制面积智能劈分；得到各单井控制面积比例,结合气藏实际含气面积,计算得到各单井控制面积；该方法贴合实际、计算过程省时省力；利用编程,绘制单井控制面积劈分图,形象直观；适用范围广,可推广性强。(The invention relates to a gas reservoir single-well control area splitting method based on artificial intelligence, belonging to the field of evaluation of reserves of a gas reservoir; the method aims to solve the problems that the single well control area of the existing gas reservoir gas well has large calculation error, complicated flow and the like; the technical scheme is as follows: firstly, preparing static and dynamic parameters of a gas reservoir and a gas well, and drawing a boundary curve of a gas reservoir block by utilizing a triangulation algorithm; establishing a two-dimensional matrix of permeability, effective reservoir thickness and porosity of physical properties of the gas reservoir; calculating a single-well competition coefficient based on a differential competition area growing image segmentation algorithm; combining the competition coefficients of the single wells, and intelligently splitting the control area of the single well of the gas reservoir; obtaining the control area proportion of each single well, and calculating to obtain the control area of each single well by combining the actual gas containing area of the gas reservoir; the method is fit to reality, and the calculation process is time-saving and labor-saving; by programming, drawing a single-well control area splitting diagram, and the image is visual; wide application range and strong popularization.)

1. A gas reservoir single well control area splitting method based on artificial intelligence is characterized by comprising the following steps:

firstly, preparing static and dynamic parameters of a gas reservoir and a gas well, wherein the static and dynamic parameters comprise actual gas containing area of the gas reservoir, logging data, reservoir temperature, natural gas viscosity, natural gas deviation factors, gas reservoir radius, shaft radius, well position coordinates, boundary coordinates and single well productivity;

secondly, extracting discrete point boundaries by using a triangulation algorithm according to single-well boundary coordinates, and drawing a gas reservoir block boundary curve;

thirdly, establishing a permeability two-dimensional matrix of the physical properties of the gas reservoir and a reservoir effective thickness two-dimensional matrix through programming according to single-well logging data, and further calculating to obtain a porosity two-dimensional matrix by utilizing a porosity calculation formula;

fourthly, calculating a single well competition coefficient by combining the single well productivity data and utilizing a single well competition coefficient equation according to the established permeability two-dimensional matrix, the reservoir effective thickness two-dimensional matrix and the porosity two-dimensional matrix;

fifthly, according to the well position coordinates and the boundary curve, combining the obtained single well competition coefficients, and utilizing a single well growth point discrimination formula to intelligently split the control area of the single well of the gas reservoir;

and sixthly, when no point in the gas reservoir meets the growth point discrimination formula, stopping the operation to obtain a gas reservoir single well area splitting diagram, obtaining the control area proportion of each single well according to the gas reservoir single well area splitting result, and calculating to obtain the control area of each single well by combining the actual gas containing area of the gas reservoir.

2. The artificial intelligence based gas reservoir single well control area splitting method as claimed in claim 1, wherein: the triangulation algorithm realizes the extraction of discrete point boundaries by using a Delaunay method through math software Matlab 2016 a.

3. The artificial intelligence based gas reservoir single well control area splitting method as claimed in claim 1, wherein: the established permeability two-dimensional matrix, the reservoir effective thickness two-dimensional matrix and the porosity two-dimensional matrix are all two-dimensional matrices with the size of 10 multiplied by 10.

4. The artificial intelligence based gas reservoir single well control area splitting method as claimed in claim 1, wherein: the porosity calculation formula is

5. The artificial intelligence based gas reservoir single well control area splitting method as claimed in claim 1, wherein: the single well competition coefficient equation isWherein, in the step (A),q _sdfor single well productivity in m³/d；TIs the reservoir temperature in K;μnatural gas viscosity in cP;Zis a natural gas deviation factor without dimension;r _eis the radius of the gas reservoir in m;r _wis the wellbore radius in m;Kis the permeability of the reservoir, in mD,his the effective thickness of the reservoir in m, dpIs a single well competition coefficient and has no dimension.

6. The artificial intelligence based gas reservoir single well control area splitting method as claimed in claim 1, wherein: the growth point discrimination formula is

7. The artificial intelligence based gas reservoir single well control area splitting method as claimed in claim 1, wherein: the intelligent splitting of the gas reservoir single-well control area takes the coordinates of each well as an initial point, a boundary curve as a limiting condition, a single-well competition coefficient as a diffusion speed, a growth point discrimination formula as a diffusion condition, and differential area growth based on the single-well competition coefficient is carried out from the initial point to the periphery of the initial point.

8. The artificial intelligence based gas reservoir single well control area splitting method as claimed in claim 1, wherein: the single well control area ratio is stored in a one-dimensional matrix of the math software Matlab 2016a working area, the size of which is consistent with the number of the gas reservoir wells.

Technical Field

The invention relates to a gas reservoir single-well control area splitting method based on artificial intelligence, and belongs to the field of evaluation of reserves of oil and gas reservoirs.

Background

The single-well geological reserve calculation method is more and more widely applied compared with other general residual gas research methods due to the fact that the calculation process is high in operability and the result reliability is high. In the middle and later stages of development of the oil and gas field, the purpose of calculating the single-well geological reserves is to make clear the residual geological reserves and the distribution of residual oil and gas on a plane well point, and the calculation of the single-well control area is the most important factor for determining the single-well geological reserves, so that the related research on the calculation of the single-well control area of the gas reservoir is developed, and the method has great significance for reasonably developing the later stage of the gas reservoir, optimizing the single-well production system and improving the overall benefit of the gas reservoir.

Through extensive research, the research of single-well control area calculation is very little at present, and the patent number is CN201510197824.7, namely a method for determining the single-well control reserve of a fracture-cavity type oil reservoir, wherein the mentioned single-well control area determination needs to establish a corresponding physical model, the control shape of a well is clear, the required parameters are many, the calculation steps are complicated, and the reliability of the control shape obtained through a physical model experiment is low; the patent CN201811430509.4 "shale gas reservoir mining method based on optimal single well control area", wherein the mentioned single well control area is only regarded as the product of the control length and the control width, and the single well control area boundary is irregular shape in general, which is contrary to the practical situation.

Generally, the current method for calculating the single-well control area mainly comprises the following steps: the method comprises three types of empirical formulas, an area weighting method and a physical model, but all have larger limitations and errors. Therefore, a splitting method which is high in accuracy, strong in operability and consistent with the actual situation is urgently needed to calculate the single-well control area, and a foundation is laid for subsequent reserve evaluation and reasonable development of gas reservoirs.

Disclosure of Invention

The invention aims to: in order to solve the problems of large calculation error of the single well control area of the gas reservoir gas well, complex flow and the like, programming is carried out by utilizing math software Matlab 2016a, splitting of the control area of each single well of the gas reservoir is carried out based on artificial intelligence, and the splitting effect is good and the applicability is strong.

In order to achieve the aim, the invention provides a gas reservoir single well control area splitting method based on artificial intelligence, which comprises the following steps:

firstly, preparing static and dynamic parameters of a gas reservoir and a gas well, wherein the static and dynamic parameters comprise actual gas containing area of the gas reservoir, logging data, reservoir temperature, natural gas viscosity, natural gas deviation factors, gas reservoir radius, shaft radius, well position coordinates, boundary coordinates and single well productivity;

secondly, extracting discrete point boundaries by using a triangulation algorithm according to single-well boundary coordinates, and drawing a gas reservoir block boundary curve;

thirdly, establishing a permeability two-dimensional matrix of the physical properties of the gas reservoir and a reservoir effective thickness two-dimensional matrix through programming according to single-well logging data, and further calculating to obtain a porosity two-dimensional matrix by utilizing a porosity calculation formula;

fourthly, calculating a single well competition coefficient by combining the single well productivity data and utilizing a single well competition coefficient equation according to the established permeability two-dimensional matrix, the reservoir effective thickness two-dimensional matrix and the porosity two-dimensional matrix;

fifthly, according to the well position coordinates and the boundary curve, combining the obtained single well competition coefficients, and utilizing a single well growth point discrimination formula to intelligently split the control area of the single well of the gas reservoir;

and sixthly, when no point in the gas reservoir meets the growth point discrimination formula, stopping the operation to obtain a gas reservoir single well area splitting diagram, obtaining the control area proportion of each single well according to the result of the gas reservoir single well area splitting diagram, and calculating to obtain the control area of each single well by combining the actual gas containing area of the gas reservoir.

All the calculations of the artificial intelligence-based gas reservoir single well control area splitting method are realized by programming of mathematic software Matlab 2016 a.

In the method for splitting the control area of the single gas reservoir well based on artificial intelligence, the triangulation algorithm is programmed by a Delaunay method through mathematic software Matlab 2016a to extract discrete point boundaries.

In the method for splitting the control area of the single gas reservoir well based on the artificial intelligence, the established permeability two-dimensional matrix, the reservoir effective thickness two-dimensional matrix and the porosity two-dimensional matrix are two-dimensional matrices with the size of 10 multiplied by 10.

In the method for splitting the control area of the single gas reservoir well based on artificial intelligence, the porosity calculation formula isWherein, in the step (A),Kis the reservoir permeability in mD;φis porosity, dimensionless.

In the method for splitting the control area of the single well of the gas reservoir based on artificial intelligence, the single well competition coefficient equation isWherein, in the step (A),q _sdfor single well productivity in m³/d；TIs the reservoir temperature in K;μnatural gas viscosity in cP;Zis a natural gas deviation factor without dimension;r _eis the radius of the gas reservoir in m;r _wis the wellbore radius in m;Kis the permeability of the reservoir, in mD,his the effective thickness of the reservoir in m, dpIs a single well competition coefficient and has no dimension.

In the method for splitting the control area of the single gas reservoir well based on artificial intelligence, the judgment formula of the growth point is

Wherein, in the step (A),is a value of 0 or 1 at a point within the boundary of the entire gas reservoir, and is dimensionless.

The method for splitting the control area of the single gas reservoir well based on the artificial intelligence is characterized in that the intelligent splitting of the control area of the single gas reservoir well takes coordinates of each well as a boundary curve as a starting point, a single well competition coefficient as a limiting condition, a growth point discrimination formula as a diffusion condition, and differential area growth based on the single well competition coefficient is performed from the starting point to the periphery of the starting point.

In the method for splitting the single well control area of the gas reservoir based on artificial intelligence, the single well control area proportion is stored in a one-dimensional matrix of which the size is consistent with the number of the gas reservoir wells in a mathematic software Matlab 2016a working area.

Compared with the prior art, the invention has the following beneficial effects: (1) establishing a two-dimensional matrix of reservoir permeability, effective thickness and porosity, reflecting the heterogeneity of the gas reservoir by combining the single well productivity, and fitting the reality; (2) the area splitting and calculation are realized through programming, and the calculation process is time-saving and labor-saving; (3) by programming, drawing a single-well control area splitting diagram, and the image is visual; (4) wide application range and strong popularization.

Drawings

In the drawings:

FIG. 1 is a technical scheme of the method.

FIG. 2 is an interface diagram of a gas reservoir single well control area splitting software based on artificial intelligence.

Fig. 3 is a graph plotting a boundary of a gas reservoir.

FIG. 4 is a diagram of intelligent split of single well control area for a certain gas reservoir.

FIG. 5 is a plot of the results of the ratio of the individual well areas of a gas reservoir in the matlab workspace.

Detailed Description

The present invention will be further described with reference to the following embodiments and drawings.

The invention provides a gas reservoir single well control area splitting method based on artificial intelligence, and fig. 1 is a technical route diagram of the method, wherein the method comprises the following steps:

firstly, preparing static and dynamic parameters of a gas reservoir and a gas well, wherein the static and dynamic parameters comprise actual gas containing area of the gas reservoir, logging data, reservoir temperature, natural gas viscosity, natural gas deviation factors, gas reservoir radius, shaft radius, well position coordinates, boundary coordinates and single well productivity;

secondly, extracting discrete point boundaries by using a triangulation algorithm according to single-well boundary coordinates, and drawing a gas reservoir block boundary curve;

thirdly, establishing a permeability two-dimensional matrix of the physical properties of the gas reservoir and a reservoir effective thickness two-dimensional matrix through programming according to single-well logging data, and further calculating to obtain a porosity two-dimensional matrix by utilizing a porosity calculation formula;

fourthly, calculating a single well competition coefficient by combining the single well productivity data and utilizing a single well competition coefficient equation according to the established permeability two-dimensional matrix, the reservoir effective thickness two-dimensional matrix and the porosity two-dimensional matrix;

fifthly, according to the well position coordinates and the boundary curve, combining the obtained single well competition coefficients, and utilizing a single well growth point discrimination formula to intelligently split the control area of the single well of the gas reservoir;

and sixthly, when no point in the gas reservoir meets the growth point discrimination formula, stopping the operation to obtain a gas reservoir single well area splitting diagram, obtaining the control area proportion of each single well according to the gas reservoir single well area splitting result, and calculating to obtain the control area of each single well by combining the actual gas containing area of the gas reservoir.

Further, all the calculations are implemented by programming the math software Matlab 2016a, and the software interface is shown in fig. 2.

Further, the triangulation algorithm utilizes a Delaunay method to realize the extraction of discrete point boundaries through math software Matlab 2016 a.

Further, the established permeability two-dimensional matrix, the reservoir effective thickness two-dimensional matrix and the porosity two-dimensional matrix are all two-dimensional matrices with the size of 10 multiplied by 10.

Further, the porosity calculation formula is

Wherein, in the step (A),Kis the reservoir permeability in mD;φis degree of porosityAnd no dimensional quantity.

Further, the equation of the single well competition coefficient is

Wherein, in the step (A),q _sdfor single well productivity in m³/d；TIs the reservoir temperature in K;μnatural gas viscosity in cP;Zis a natural gas deviation factor without dimension;r _eis the radius of the gas reservoir in m;r _wis the wellbore radius in m;Kis the permeability of the reservoir, in mD,his the effective thickness of the reservoir in m, dpIs a single well competition coefficient and has no dimension.

Further, the growing point discrimination formula isWherein

Is a value of 0 or 1 at a point within the boundary of the entire gas reservoir, and is dimensionless.

Furthermore, the intelligent splitting of the gas reservoir single-well control area takes the coordinates of each well position as a starting point, a boundary curve as a limiting condition, a single-well competition coefficient as a diffusion speed, a growth point discrimination formula as a diffusion condition, and differential area growth based on the single-well competition coefficient is carried out from the starting point to the periphery of the starting point.

Further, the single well control area ratio is stored in a one-dimensional matrix of the math software Matlab 2016a working area with the same size as the number of the gas reservoir wells, as shown in fig. 5.

And intelligent splitting of the single-well control area is performed by using compiled single-well control area splitting software based on artificial intelligence and taking a certain gas reservoir as an example.

Preparing static and dynamic parameters of the gas reservoir and the gas well, including gas containing area of the whole gas reservoir area, logging data, reservoir temperature, natural gas viscosity, natural gas deviation factors, gas reservoir radius, shaft radius, well position coordinates, boundary coordinates and single well productivity;

the well location coordinates and the single well productivity are shown in table 1.

TABLE 1

Abscissa of the circle	Ordinate of the curve	Single well capacity
			165686.48	41391.96	6000
165683.84	41399.89	7000
			165690.34	41401.86	12000
165700.30	41394.04	9000
			165686.73	41405.68	11000

Extracting discrete point boundaries by using a triangulation algorithm according to the single-well boundary coordinates, and drawing a gas reservoir block boundary curve as shown in FIG. 3;

from single well log dataEstablishing a permeability two-dimensional matrix of gas reservoir physical properties, a reservoir effective thickness two-dimensional matrix by programming, and combining a porosity calculation formula

Further establishing a porosity two-dimensional matrix;

according to the established permeability two-dimensional matrix, the reservoir effective thickness two-dimensional matrix and the porosity two-dimensional matrix, the yield data of the single well is combined, the algorithm is divided based on the growth image of the differential competition area, and the equation of the competition coefficient of the single well is utilized

Calculating the competition coefficient of the single well, and showing in a table 2;

TABLE 2

Abscissa of the circle	Ordinate of the curve	Single well competition coefficient
			165686.48	41391.96	0.03074
165683.84	41399.89	0.03586
			165690.34	41401.86	0.06148
165700.30	41394.04	0.04611
			165686.73	41405.68	0.05636

According to the well position coordinates and the boundary curve, a single well growth point discrimination formula is utilizedCombining the single-well competition coefficient, taking the coordinates of each well as a starting point, taking the boundary curve as a limiting condition, taking the single-well competition coefficient as a diffusion speed, taking a growth point discrimination formula as a diffusion condition, and performing differential area growth from the starting point to the periphery of the starting point based on the single-well competition coefficient;

when no point in the gas reservoir meets the growth point discrimination formula, the operation is terminated to obtain a gas reservoir single well area splitting diagram, as shown in figure 4, the control area proportion of each single well is obtained according to the calculation result, as shown in figure 5, and the actual gas containing area of the gas reservoir is 24km²And calculating the control area of each single well, and showing in a table 3.

TABLE 3

Abscissa of the circle	Ordinate of the curve	Single well control of area ratio	Actual control area/km2
				165686.48	41391.96	15303	2.38
165683.84	41399.89	19374	3.02
				165690.34	41401.86	9341	1.46
165700.30	41394.04	66375	10.34
				165686.73	41405.68	43663	6.80

Compared with the prior art, the invention has the following beneficial effects: (1) establishing a two-dimensional matrix of reservoir permeability, effective thickness and porosity, reflecting the heterogeneity of the gas reservoir by combining the single well productivity, and fitting the reality; (2) the area splitting and calculation are realized through programming, and the calculation process is time-saving and labor-saving; (3) by programming, drawing a single-well control area splitting diagram, and the image is visual; (4) wide application range and strong popularization.

Finally, it should be noted that: although the present invention has been described in detail with reference to the above embodiments, it should be understood by those skilled in the art that: modifications and equivalents may be made thereto without departing from the spirit and scope of the invention and it is intended to cover in the claims the invention as defined in the appended claims.