CN113392595A - Conglomerate oil reservoir horizontal well fracturing fracture net characterization method - Google Patents
Conglomerate oil reservoir horizontal well fracturing fracture net characterization method Download PDFInfo
- Publication number
- CN113392595A CN113392595A CN202010177193.3A CN202010177193A CN113392595A CN 113392595 A CN113392595 A CN 113392595A CN 202010177193 A CN202010177193 A CN 202010177193A CN 113392595 A CN113392595 A CN 113392595A
- Authority
- CN
- China
- Prior art keywords
- fracture
- fracturing
- horizontal well
- network
- reservoir
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000012512 characterization method Methods 0.000 title claims abstract description 21
- 238000000034 method Methods 0.000 claims abstract description 44
- 238000004088 simulation Methods 0.000 claims abstract description 36
- 239000011435 rock Substances 0.000 claims abstract description 30
- 230000000977 initiatory effect Effects 0.000 claims abstract description 19
- 238000012544 monitoring process Methods 0.000 claims abstract description 8
- 238000012314 multivariate regression analysis Methods 0.000 claims abstract description 6
- 238000009826 distribution Methods 0.000 claims description 17
- 239000012530 fluid Substances 0.000 claims description 17
- 238000004364 calculation method Methods 0.000 claims description 10
- 238000004458 analytical method Methods 0.000 claims description 6
- 238000006073 displacement reaction Methods 0.000 claims description 6
- 239000011159 matrix material Substances 0.000 claims description 6
- 230000007246 mechanism Effects 0.000 claims description 6
- 239000000203 mixture Substances 0.000 claims description 4
- 208000010392 Bone Fractures Diseases 0.000 description 104
- 238000010276 construction Methods 0.000 description 7
- 239000000463 material Substances 0.000 description 5
- 238000005336 cracking Methods 0.000 description 4
- 230000001419 dependent effect Effects 0.000 description 4
- 238000005516 engineering process Methods 0.000 description 4
- 229910052500 inorganic mineral Inorganic materials 0.000 description 4
- 239000011707 mineral Substances 0.000 description 4
- 230000007547 defect Effects 0.000 description 3
- 238000004519 manufacturing process Methods 0.000 description 3
- 230000035699 permeability Effects 0.000 description 3
- 230000015572 biosynthetic process Effects 0.000 description 2
- 238000002474 experimental method Methods 0.000 description 2
- 230000001788 irregular Effects 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000000704 physical effect Effects 0.000 description 2
- 230000008569 process Effects 0.000 description 2
- 238000000611 regression analysis Methods 0.000 description 2
- 239000004576 sand Substances 0.000 description 2
- 238000011161 development Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- -1 displacement volume Substances 0.000 description 1
- 238000005315 distribution function Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 238000002347 injection Methods 0.000 description 1
- 239000007924 injection Substances 0.000 description 1
- 238000000491 multivariate analysis Methods 0.000 description 1
- 239000002245 particle Substances 0.000 description 1
- 238000001228 spectrum Methods 0.000 description 1
- 238000007619 statistical method Methods 0.000 description 1
Images
Classifications
-
- E—FIXED CONSTRUCTIONS
- E21—EARTH OR ROCK DRILLING; MINING
- E21B—EARTH OR ROCK DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS
- E21B43/00—Methods or apparatus for obtaining oil, gas, water, soluble or meltable materials or a slurry of minerals from wells
- E21B43/25—Methods for stimulating production
- E21B43/26—Methods for stimulating production by forming crevices or fractures
Landscapes
- Life Sciences & Earth Sciences (AREA)
- Engineering & Computer Science (AREA)
- Geology (AREA)
- Mining & Mineral Resources (AREA)
- Physics & Mathematics (AREA)
- Environmental & Geological Engineering (AREA)
- Fluid Mechanics (AREA)
- General Life Sciences & Earth Sciences (AREA)
- Geochemistry & Mineralogy (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention provides a conglomerate oil reservoir horizontal well fracturing fracture net characterization method. The conglomerate oil reservoir horizontal well fracture net characterization method comprises the following steps: determining the fractal dimension of the fracturing network of each fracturing section of the horizontal well by using a fracturing network model formed by microseism monitoring data points; determining a fracture expansion fractal factor of a reservoir by using a multivariate regression analysis method according to the fractal dimension of the fracturing network and the physical parameters of the reservoir rock; and carrying out crack initiation and expansion simulation on the crack expansion fractal factor. The invention solves the problem that the shape of a seam network formed by fracturing of a horizontal well of a conglomerate oil reservoir cannot be accurately simulated in the prior art.
Description
Technical Field
The invention relates to the field of oil exploitation, in particular to a gravel oil reservoir horizontal well fracture net characterization method.
Background
Natural fractures in conglomerate reservoir reservoirs do not develop generally, but physical properties and characteristics and the like have great heterogeneity, so that great challenges are brought to fracture engineering and production recognition. For a fracture network formed by fracturing, researchers at home and abroad often analyze the fracture propagation law by adopting indoor experiments and numerical simulation methods. Due to the limitation of experimental conditions and the difficulty of indoor physical simulation of complex cracks, the current numerical simulation method is a main means for researching the complex crack propagation rule. The numerical simulation of the horizontal well oil deposit is a reliable technology for quantitatively describing the production dynamics of a fractured oil and gas reservoir and is an important means for deeply knowing the oil reservoir, predicting the production and adjusting and optimizing the development scheme.
Analytical models are mostly adopted for early fracturing simulation, and the models can only roughly simulate the scale of a fracturing network and cannot finely represent the form of the fracturing network. With the progress of computer science and numerical calculation methods, more and more fracture simulation methods begin to adopt fracture initiation and propagation mechanism models such as propagation finite elements, discrete elements, discontinuous displacement and the like, and consider fine geological parameters and natural fracture models, so that the simulation precision and the fracture network characteristics are greatly improved.
Common numerical Fracture propagation models are classified into Planar Fracture Models (PFM) and Unconventional Fracture propagation models (UFM). The plane fracture model comprises a wire mesh model and an equivalent fracture model, only plane expansion fractures can be simulated, and the simple fracture expansion is mainly simulated so as to analyze and predict the scale of fractures formed by fracturing. The unconventional fracture propagation model can simulate a fracture network under real construction parameters according to a reservoir stress field, a rock mechanics model and natural fracture distribution.
The method and the simulation technology are applied to reservoirs such as shale, compact sandstone and the like successfully at the earliest time. According to these conventional fracture simulation methods, the formation of a complex fracture network requires certain reservoir geological conditions (petrophysical and stress field parameters, etc.), natural fracture distribution, and appropriate construction pressure (controlled by parameters such as displacement). In other words, the formation of the fractured complex fracture network in the reservoir is caused by the interlacing of artificial fractures and natural fractures, the complex fracture network is formed on the premise that natural fractures exist and meet certain geological parameter and ground stress parameter constraint conditions, otherwise, only simple double-wing fractures can be formed.
However, there is increasing evidence that in some conglomerate reservoirs that do not have natural fractures, the fracturing process does not result in a simple double-winged fracture. For example, the most direct evidence is that the range size of a single stage fracture microseismic monitoring point shows that the fracture network formed by the fracture has local complex branch fracture characteristics rather than simple double-winged fractures. The other strong evidence is that the half length of the fracture obtained by simulation is obviously longer than a monitoring value by performing fracture net pressure fitting based on the assumption of double wing seams according to construction discharge capacity and sand amount.
In view of the above, there is a need to develop a fracture network characterization method for a horizontal well of a conglomerate reservoir to more accurately simulate the fracture network morphology formed by fracturing the horizontal well of the conglomerate reservoir. By combining with technical analysis such as core experiment, core scanning and core mineral analysis, the local complex branch seam appearing in the fracturing of the conglomerate reservoir without natural fractures is caused by a weak face or a loose part cemented among gravels. The micro-scale simulation method has a relation with the particle size of the conglomerate gravel, the mineral components cemented among the gravels and the tightness, and macroscopically shows that the micro-scale simulation method is related to the properties of the conglomerate heterogeneity, the rock physical parameters, the brittleness index and the like, but the traditional simulation method cannot represent the micro-scale heterogeneity. In the invention, the conglomerate reservoir fracture complexity is quantitatively described based on a fractal dimension concept.
Disclosure of Invention
The invention mainly aims to provide a conglomerate oil reservoir horizontal well fracture net characterization method to solve the problem that the fracture net shape formed by the conglomerate oil reservoir horizontal well fracturing cannot be accurately simulated in the prior art.
In order to achieve the above object, according to an aspect of the present invention, there is provided a conglomerate reservoir horizontal well fracture network characterization method, including: determining the fractal dimension of the fracturing network of each fracturing section of the horizontal well by using a fracturing network model formed by microseism monitoring data points; determining a fracture expansion fractal factor of a reservoir by using a multivariate regression analysis method according to the fractal dimension of the fracturing network and the physical parameters of the reservoir rock; and carrying out crack initiation and expansion simulation on the crack expansion fractal factor.
Further, the microseismic survey data points are modeled by microseismic inversion to form a fracture network.
Further, the reservoir petrophysical parameters include: young's modulus, poisson's ratio, and brittleness index.
Further, when fracture initiation and expansion simulation of the fracture expansion fractal factor is carried out, a stress field calculation model of the tight reservoir combination with multi-fracture stress interference is established by utilizing a displacement discontinuity method, mechanical mechanism analysis and initiation and expansion criteria.
Further, when solving the stress and geometric parameters of each newly added crack infinitesimal of the stress field calculation model, recalculating the additional stress field at each time step to determine the combined stress field distribution at the center of the global coordinate system.
Further, when the crack infinitesimal is expanded, crack steering is carried out according to the crack expansion fractal factor, and iteration is carried out in a circulating mode until the fractal dimension of the formed fracture network is consistent with the crack expansion fractal factor.
Further, the conglomerate oil reservoir horizontal well fracture net characterization method further comprises a step of simulating fracture cracking and expansion in the next time step by the current time step, and the step of simulating fracture cracking and expansion in the next time step by the current time step comprises the following steps:
step S1: judging whether a crack breaking point occurs in the next time step or not according to the rock breaking criterion, the stress intensity factor and the horizontal main stress direction, starting a crack length epsilon at a breaking angle if the crack breaking point occurs, and recalculating the stress field distribution; substituting the pressure at the node point into the seam width equation (1),
solving the seam widths x at different nodes, wherein a is the half length of the seam, P is the uniform pressure in the seam, E and v are respectively the Young modulus and Poisson ratio of the rock, and w is the opening degree of the seam at different positions;
step S2: substituting the obtained fracture width and initial flow distribution into a hydraulic fracture mass conservation formula (2),
and calculating to obtain a new pressure value at the hydraulic fracture node, wherein w is the fracture opening degree, vflAs to the flow rate of the fracturing fluid mixture,
is the mass flow rate of the wellbore into the fracture per unit time,
for the classical Carter one-dimensional leak rate, the calculation formula (3) is:
wherein, CleakIs the leakage coefficient related to the fluidity of the matrix, the viscosity of the matrix fluid and the fracturing fluid, and t is the current timeτ is the time at which the fluid first reaches the current location;
step S3: and calculating a stress concentration factor at the tip, judging whether the crack continues to extend according to an extension criterion, restarting a crack length epsilon under a new extension angle if the crack continues to extend, and recalculating stress field distribution until the tip does not break.
Further, the cracking length ε is more than 0 and 100mm or less.
And further, after the crack is judged to continue to extend, an extension angle is calculated according to the crack extension fractal factor.
Further, the extension angle is an extension angle or a deflection angle along the horizontal maximum stress direction.
By applying the technical scheme of the invention, the method for characterizing the horizontal well fracture network of the conglomerate oil reservoir comprises the following steps: determining the fractal dimension of the fracturing network of each fracturing section of the horizontal well by using a fracturing network model formed by microseism monitoring data points; determining a fracture expansion fractal factor of a reservoir by using a multivariate regression analysis method according to the fractal dimension of the fracturing network and the physical parameters of the reservoir rock; and carrying out crack initiation and expansion simulation on the crack expansion fractal factor.
In the scheme, the heterogeneity of a weak cementing surface of the micro gravels of the gravels is described by introducing crack propagation parting factors of the gravels, a complex micro propagation mechanism of fracturing cracks is researched, and auxiliary extension simulation of local branched double-wing cracks is carried out on a compact gravels stratum by using a crack piece simulation technology, so that the defect that only simple double-wing cracks are generated in a conventional simulation method is overcome, and the actual fracturing result is better met.
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 schematic flow diagram of a conglomerate reservoir horizontal fracture network characterization method according to one embodiment of the present invention.
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.
In order to solve the problem that the fracture network form formed by the fracturing of a conglomerate oil reservoir horizontal well cannot be accurately simulated in the prior art, the application provides a conglomerate oil reservoir horizontal well fracture network characterization method.
The conglomerate oil reservoir horizontal well fracture net characterization method comprises the following steps: determining the fractal dimension of the fracturing network of each fracturing section of the horizontal well by using a fracturing network model formed by microseism monitoring data points; determining a fracture expansion fractal factor of a reservoir by using a multivariate regression analysis method according to the fractal dimension of the fracturing network and the physical parameters of the reservoir rock; and carrying out crack initiation and expansion simulation on the crack expansion fractal factor.
In the scheme, the heterogeneity of a weak cementing surface of the micro gravels of the gravels is described by introducing crack propagation parting factors of the gravels, a complex micro propagation mechanism of fracturing cracks is researched, and auxiliary extension simulation of local branched double-wing cracks is carried out on a compact gravels stratum by using a crack piece simulation technology, so that the defect that only simple double-wing cracks are generated in a conventional simulation method is overcome, and the actual fracturing result is better met.
A number of field observations and laboratory studies have shown that: the rock has rough fracture structure and irregular fracture distribution and hasFractal characteristics are difficult to describe the rough structure and irregular distribution characteristics of the cracks by using a classical geometric language. Compared with the traditional geometric and statistical description method, the fractal description of the crack contains more crack information and can more closely reflect the roughness and distribution irregularity of the crack. At present, fractal description methods commonly used for rock fractures include an area perimeter method, a box-dimension method, an exponential spectrum method, a variation function method and the like, wherein the box-dimension method is widely adopted due to the convenience of operation, the box-dimension method is one of the most main methods for representing fracture irregularity by fracture fractal dimension, and the method is simple and convenient to calculate and easy to understand. The basic method for calculating the fractal dimension of the plane fracture by adopting the box dimension comprises the following steps: with NηRepresenting the number of square boxes with side length eta of the coverage curve, the available area value is Nη·η2The box dimensions of the curve thus obtained are: d ═ ln Nη/lnη。
Specifically, the microseismic survey data points are modeled by microseismic inversion to form a fracture network.
In particular, the reservoir petrophysical parameters include: young's modulus, poisson's ratio, and brittleness index.
Multivariate regression methods are statistical analysis methods that study the dependence of one dependent variable on another or on a set of independent variables. The multiple regression analysis method is a method used for dealing with a variable problem relating to a plurality of independent variables, and is more practical and effective than a method in which a dependent variable is predicted or estimated by an optimal combination of a plurality of independent variables.
In the application, the obtained fracture network fractal dimension on each fracture section is used as a dependent variable, and the relation between the fractal dimension and related rock parameters is searched and verified by utilizing multivariate regression analysis. The factors for determining the complexity of the conglomerate reservoir fracturing network are generally considered to be a comprehensive reflection of the geological environment of the rock and the reservoir characteristics, and are related to various factors such as rock brittleness index, rock mineral components, gravel content and cementing relation, cementing components and the like in expression.
In practical application, microscopic data such as rock mineral composition and the like are difficult to acquire in each fracture section, and the parameters are not considered in multiple regression analysis because the parameters are reflected on macroscopic Young modulus, Poisson's ratio and brittleness index. Therefore, the analysis is mainly performed by considering 3 parameter values of the Young modulus, the Poisson ratio and the brittleness index of the rock:
1) young's modulus E: when the deformation quantity does not exceed a certain elastic limit of the corresponding material, the ratio of the positive stress to the positive strain is defined as the Young modulus E of the material;
2) poisson ratio v: when a material is compressed in one direction, the material can be stretched in the other two directions which are perpendicular to the direction, namely the poisson phenomenon, and the ratio of the transverse deformation to the longitudinal deformation is the poisson ratio v which is a dimensionless physical quantity;
3) rock brittleness index BI: in geology and its related disciplines, the feature that a material exhibits little or no plastic deformation before breaking or breaking is called brittleness, which is an inherent property of rock that manifests itself as a small plastic strain that occurs macroscopically in the rock, all being released in the form of elastic energy upon fracture. The better the brittleness of the rock, indicating that the rock is more susceptible to fracture reformation, the parameter that measures this index is called the brittleness index.
Inputting values of multiple groups of independent variables and dependent variables into a multiple regression tool, such as SPSS, Excel, Matlab tool boxes and the like, so as to obtain a relational expression between the fractal dimension of the rock and the independent variables: d ═ f (E, ν, BI).
In order to distinguish from actual or simulated resulting fractal dimensions of the fracture network, the parameterized fractal dimension is referred to as a fractal factor, which quantitatively describes the most likely complexity of the fracture network formed by conglomerate.
Specifically, when fracture initiation and propagation simulation of a fracture propagation fractal factor is carried out, a stress field calculation model of a multi-fracture stress interference compact reservoir combination is established by utilizing a displacement discontinuity method, mechanical mechanism analysis and initiation and propagation criteria.
Specifically, when solving the stress and geometric parameters of each newly added fracture infinitesimal of the stress field calculation model, the additional stress field is recalculated at each time step to determine the combined stress field distribution at the center of the global coordinate system.
Specifically, when the crack infinitesimal is expanded, crack steering is carried out according to the size of a crack expansion fractal factor and a certain proportion, and iteration is carried out in a circulating mode until the fractal dimension of the formed fracture network conforms to the crack expansion fractal factor.
Specifically, the conglomerate reservoir horizontal well fracture net characterization method further comprises a step of simulating fracture initiation and expansion in the next time step by the current time step, and the step of simulating fracture initiation and expansion in the next time step by the current time step comprises the following steps:
step S1: judging whether a crack breaking point occurs in the next time step or not according to the rock breaking criterion, the stress intensity factor and the horizontal main stress direction, starting a crack length epsilon at a breaking angle if the crack breaking point occurs, and recalculating the stress field distribution; substituting the pressure at the node point into the seam width equation (1),
solving the seam widths x at different nodes, wherein a is the half length of the seam, P is the uniform pressure in the seam, E and v are respectively the Young modulus and Poisson ratio of the rock, and w is the opening degree of the seam at different positions;
step S2: substituting the obtained fracture width and initial flow distribution into a hydraulic fracture mass conservation formula (2),
and calculating to obtain a new pressure value at the hydraulic fracture node, wherein w is the fracture opening degree, vflAs to the flow rate of the fracturing fluid mixture,
is the direction of flow of the wellbore in unit timeThe mass flow rate of the fracture(s),
for the classical Carter one-dimensional leak rate, the calculation formula (3) is:
wherein, CleakThe leakage coefficient related to the matrix fluidity, the matrix fluid and the viscosity of the fracturing fluid is shown, t is the current time, and tau is the time when the fluid reaches the current position for the first time;
step S3: and calculating a stress concentration factor at the tip, judging whether the crack continues to extend according to an extension criterion, restarting a crack length epsilon under a new extension angle if the crack continues to extend, and recalculating stress field distribution until the tip does not break.
In the present application, the formula (4) for the deflection and bifurcation of the crack is:
where P is the probability of deflection, DnFor the current simulation of the fractal dimension of the formed fracture network, D is the fractal factor of the fracture section, N is a normal distribution function, L is the half-length of the current fracture, and L is the half-length of the current fracture0For fracture characteristic length, L in one embodiment of the present application0Is 200 m. The formula shows that the smaller the fractal dimension of the seam network formed by simulation, the more likely the deflection bifurcation will be formed, and in addition, the longer the crack extension, the more likely the deflection will be formed.
Specifically, the cracking length ε is greater than 0 and 100mm or less.
Specifically, after the fracture is judged to continue to extend, an extension angle is calculated according to the fracture extension fractal factor.
In particular, the extension angle is an extension angle or a deflection angle along the horizontal maximum stress direction.
In this applicationIn one embodiment, the software is simulated by a numerical value based on a conductivity linked list
For example, the fine numerical simulation grid data to be loaded includes:
the method comprises the following steps: loading original numerical simulation model
The method comprises the data of conventional physical properties such as angular point grid geometric information, porosity, permeability, saturation and the like, and rock mechanical parameters such as rock Young modulus, Poisson ratio, initial maximum and minimum horizontal principal stress, maximum principal stress direction, brittleness index and the like.
1) The grid geometric information data comprises the main parts of SPECGRID, COORD, ZCRN, ACTNUM and the like:
first, assume that the oil is hidden in the X, Y, Z direction and the grid numbers are N1, N2 and N3, respectively. To construct the grid of corner points, it is first necessary to generate the pillars in the depth direction. Two points define a straight line, and each point corresponds to three coordinate values, so that 6 data are needed for defining a support.
When the pillars of the grid of corner points are fixed, the specific positions of the grid cannot be determined, and at this time, another parameter is needed, and the coordinates of eight corner points of the grid in the Z direction are needed. Since the corner points of the grid can only move on the defined support posts, once the coordinates of a point in any direction are known, the position of the point on the support posts, i.e. the three-dimensional coordinates of the corner points, can be determined. Since the contact surfaces of adjacent meshes of a grid of corner points do not necessarily coincide completely, each corner point of each mesh needs to be defined separately. For a hexahedral mesh, each mesh has 8 corner points, each corner point needs to be located by a coordinate value, and we need the total number of Z-direction coordinates to be 8 × N1 × N2 × N3.
2) Porosity data, in the format:
wherein n is the total grid number and v is the grid porosity value.
3) Grid permeability data in the format:
wherein n is the total grid number and v is the grid permeability value.
4) Grid conductivity data in the format:
where N is the conductivity logarithm, g1 represents the number of the first mesh for each set of conductivity, g2 represents the number of the second mesh for each set of conductivity, and t represents the value of each set of conductivity.
Step two: loading hydraulic fracturing construction parameters
Including fracture construction data.
1) Fracturing construction data
In the data section, FRACFLD designates the type of the fracturing fluid, including the name of the fracturing fluid, the density of the fracturing fluid and the viscosity of the fracturing fluid; DATES specifies the fracture (interval) start time; frac injh specifies fracture construction information including well name, fracturing fluid, displacement volume, injection pressure and sand ratio. TSTEP specifies the fracture time step.
2) Perforation section of fracturing section
The columns are well names, fracturing stages, fracturing clusters and the positions of the shooting holes of the clusters respectively.
Step three: simulating fracture initiation and propagation
In this step, the entire process of fracture network from initiation to propagation to final form is simulated according to the fracture simulation method described previously.
Step four: outputting a fracture network file
In this step, a fracture network obtained by fracture simulation is output, and the fracture network file mainly includes information such as geometric information (vertex coordinates) of the fracture and the width of the fracture. The format is as follows:
it should be noted that, as shown in fig. 1, the main simulation flow in this application is: firstly, determining a fracturing network model, determining the fractal dimension of a fracturing network, then determining the fractal factor of the fracturing network by using a multivariate analysis method based on the known fractal dimension of the fracturing network and the physical parameters of reservoir rocks, and finally simulating the fracture initiation and the expansion of the fractal factor of the fracturing network.
From the above description, it can be seen that the above-described embodiments of the present invention achieve the following technical effects:
1. compared with a natural fracture fractal theory, the conglomerate fractal factor is introduced, so that the simulation result is more accurate;
2. the defect that only simple double-wing gaps are generated by a conventional simulation method is overcome.
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 (10)
1. A conglomerate oil reservoir horizontal well fracture net characterization method is characterized by comprising the following steps:
determining the fractal dimension of the fracturing network of each fracturing section of the horizontal well by using a fracturing network model formed by microseismic monitoring data points;
determining a fracture expansion fractal factor of the reservoir by using a multivariate regression analysis method according to the fractal dimension of the fracturing network and the physical parameters of the reservoir rock;
and carrying out crack initiation and expansion simulation on the crack expansion fractal factor.
2. The method for characterizing the conglomerate reservoir horizontal well fracture network according to claim 1, wherein the micro-seismic monitoring data points are modeled by micro-seismic inversion to form the fracture network.
3. The conglomerate reservoir horizontal well fracturing fracture network characterization method according to claim 1, wherein the reservoir petrophysical parameters include: young's modulus, poisson's ratio, and brittleness index.
4. The method for characterizing the horizontal well fracture network of the conglomerate reservoir according to claim 1, wherein a stress field calculation model of a compact reservoir combination with multi-fracture stress interference is established by utilizing a displacement discontinuity method, mechanical mechanism analysis and a fracture initiation and propagation criterion during fracture initiation and propagation simulation of the fracture propagation fractal factor.
5. The conglomerate reservoir horizontal well pressure fracture net characterization method according to claim 4, characterized in that when solving stress and geometric parameters of each newly added fracture infinitesimal of the stress field calculation model, an additional stress field is recalculated at each time step to determine the combined stress field distribution at the center of a global coordinate system.
6. The conglomerate oil reservoir horizontal well fracture network characterization method according to claim 5, characterized in that during fracture infinitesimal expansion, fracture steering is performed according to the fracture expansion fractal factor, and iteration is performed in a circulating manner until the fractal dimension of the formed fracture network conforms to the fracture expansion fractal factor.
7. The conglomerate reservoir horizontal well fracture net characterization method according to claim 6, further comprising a step of simulating fracture initiation and propagation in a next time step from a current time step, wherein the step of simulating fracture initiation and propagation in the next time step from the current time step comprises:
step S1: judging whether a crack breaking point occurs in the next time step or not according to the rock breaking criterion, the stress intensity factor and the horizontal main stress direction, starting a crack length epsilon at a breaking angle if the crack breaking point occurs, and recalculating the stress field distribution;
substituting the pressure at the node point into the seam width equation (1),
solving the seam widths x at different nodes, wherein a is the half length of the seam, P is the uniform pressure in the seam, E and v are respectively the Young modulus and Poisson ratio of the rock, and w is the opening degree of the seam at different positions;
step S2: substituting the obtained fracture width and initial flow distribution into a hydraulic fracture mass conservation formula (2),
and calculating to obtain a new pressure value at the hydraulic fracture node, wherein w is the fracture opening degree, vflAs to the flow rate of the fracturing fluid mixture,
is the mass flow rate of the wellbore into the fracture per unit time,
for the classical Carter one-dimensional leak rate, the calculation formula (3) is:
wherein, CleakThe leakage coefficient related to the matrix fluidity, the matrix fluid and the viscosity of the fracturing fluid is shown, t is the current time, and tau is the time when the fluid reaches the current position for the first time;
step S3: and calculating a stress concentration factor at the tip, judging whether the crack continues to extend according to an extension criterion, restarting one crack length epsilon under a new extension angle if the crack continues to extend, and recalculating stress field distribution until the tip does not break.
8. The conglomerate reservoir horizontal well fracturing fracture net characterization method according to claim 7, wherein the fracture length epsilon is greater than 0 and less than or equal to 100 mm.
9. The conglomerate reservoir horizontal well fracture net characterization method according to claim 7, characterized in that after the fractures are judged to continue to extend, an extension angle is calculated according to the fracture extension fractal factor.
10. The conglomerate reservoir horizontal fracture network characterization method according to claim 7, wherein the extension angle is an extension angle or a deflection angle along a horizontal maximum stress direction.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010177193.3A CN113392595A (en) | 2020-03-13 | 2020-03-13 | Conglomerate oil reservoir horizontal well fracturing fracture net characterization method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010177193.3A CN113392595A (en) | 2020-03-13 | 2020-03-13 | Conglomerate oil reservoir horizontal well fracturing fracture net characterization method |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN113392595A true CN113392595A (en) | 2021-09-14 |
Family
ID=77616292
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010177193.3A Pending CN113392595A (en) | 2020-03-13 | 2020-03-13 | Conglomerate oil reservoir horizontal well fracturing fracture net characterization method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113392595A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114548593A (en) * | 2022-03-02 | 2022-05-27 | 西南石油大学 | Conglomerate reservoir hydraulic fracturing complex fracture extension track prediction method |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108319756A (en) * | 2017-12-29 | 2018-07-24 | 西安石油大学 | A kind of compact reservoir volume fracturing seam net extended simulation and characterizing method |
-
2020
- 2020-03-13 CN CN202010177193.3A patent/CN113392595A/en active Pending
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108319756A (en) * | 2017-12-29 | 2018-07-24 | 西安石油大学 | A kind of compact reservoir volume fracturing seam net extended simulation and characterizing method |
Non-Patent Citations (3)
| Title |
|---|
| 原创力文档: "第6章 水力压裂力学", pages 1 - 4, Retrieved from the Internet <URL:https://max.book118.com/html/2019/0504/8066100001002022.shtm> * |
| 夏富国等: ""天然裂缝压裂液滤失模型"", 《油气地质与采收率》, vol. 20, no. 4, 31 July 2013 (2013-07-31) * |
| 邬元月等: ""一种砾岩油藏水平井压裂缝网的评价与预测方法"", 《IFEDC- 20194549》, 16 October 2019 (2019-10-16), pages 4 - 7 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114548593A (en) * | 2022-03-02 | 2022-05-27 | 西南石油大学 | Conglomerate reservoir hydraulic fracturing complex fracture extension track prediction method |
| CN114548593B (en) * | 2022-03-02 | 2024-04-16 | 西南石油大学 | Method for predicting extension track of hydraulic fracturing complex cracks of conglomerate reservoir |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Sobhaniaragh et al. | Three-dimensional investigation of multiple stage hydraulic fracturing in unconventional reservoirs | |
| CN113901681B (en) | Three-dimensional compressibility evaluation method for dual desserts of shale gas reservoir in whole life cycle | |
| Nandlal et al. | Drained rock volume around hydraulic fractures in porous media: planar fractures versus fractal networks | |
| CN109241588B (en) | Simulation method for single crack propagation based on quasi-continuous geomechanical model | |
| Zhao et al. | Numerical study of fracture dynamics in different shale fabric facies by integrating machine learning and 3-D lattice method: a case from Cangdong Sag, Bohai Bay basin, China | |
| Hattori et al. | Numerical simulation of fracking in shale rocks: current state and future approaches | |
| CN104750896B (en) | A kind of fractured-cavernous carbonate reservoir method for numerical simulation | |
| Yin et al. | Strain energy density distribution of a tight gas sandstone reservoir in a low-amplitude tectonic zone and its effect on gas well productivity: A 3D FEM study | |
| CN110469303B (en) | Volume fracturing parameter optimization design method based on four types of transformation volumes | |
| CN106874544A (en) | A kind of geology characterizing method of shale reservoir reconstruction volume | |
| CN105701319A (en) | Sedimentary microfacies modeling method under horizontal well rule development well net | |
| Jiang et al. | Effects of fractures on the well production in a coalbed methane reservoir | |
| CN114547953B (en) | Fracturing construction parameter optimization method and system based on optimization design chart | |
| Yang et al. | Influence of reservoirs/interlayers thickness on hydraulic fracture propagation laws in low-permeability layered rocks | |
| Zhang et al. | Simulation of a multistage fractured horizontal well in a water-bearing tight fractured gas reservoir under non-Darcy flow | |
| Liu et al. | A simplified and efficient method for water flooding production index calculations in low permeable fractured reservoir | |
| CN110705168A (en) | Simulation method of structural stress field | |
| CN115510778A (en) | Continental facies shale reservoir infinite stage fracturing process optimization method and system | |
| Zhang et al. | Production performance simulation of a horizontal well in a shale gas reservoir considering the propagation of hydraulic fractures | |
| Ren et al. | Propagation simulation and structural characterization of multiple hydraulic fractures in naturally fractured unconventional hydrocarbon reservoirs | |
| CN113392595A (en) | Conglomerate oil reservoir horizontal well fracturing fracture net characterization method | |
| Ma et al. | DEM simulation of injection-induced micro-cracks behaviors in the heterogeneous glutenite by fluid–solid coupling | |
| Ren et al. | Experimental and numerical simulation study of hydraulic fracture propagation during coalbed methane development | |
| Kalantari-Dahaghi | Systematic approach to numerical simulation and modelling of shale gas reservoirs | |
| CN114183113B (en) | Method for simplifying characterization of shale gas well fracturing crack morphology |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |