CN117313472A - Repeated fracturing parameter optimization design method for fracture-cavity carbonate reservoir - Google Patents
Repeated fracturing parameter optimization design method for fracture-cavity carbonate reservoir Download PDFInfo
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Abstract
The invention discloses a repeated fracturing parameter optimization design method of a fracture-cavity carbonate reservoir, which comprises the following steps: the method comprises the following steps: establishing a carbonate reservoir three-dimensional geological model containing a fracture-cavity body; performing three-dimensional geomechanical modeling on the fracture-cavity carbonate reservoir; forming an initial three-dimensional ground stress field of a fracture-cavity carbonate reservoir; developing fracturing fracture flow integrated simulation, and inverting to obtain the initial fracturing fracture form and the pressure field distribution characteristics at different moments; establishing a fracture-cavity carbonate reservoir four-dimensional dynamic ground stress model; carrying out repeated fracturing numerical simulation and yield prediction of a fracture-cavity carbonate reservoir; optimizing fracture-cavity carbonate fracturing parameters; the beneficial effects are that: the method can accurately describe the four-dimensional stress field of the fracture-cavity carbonate reservoir, simultaneously simulate and realize yield calculation, obtain the optimal fracture parameters of repeated fracturing, improve the simulation efficiency, and effectively improve the oil gas extraction degree of the fracture-cavity carbonate reservoir.
Description
Technical Field
The invention relates to the technical field of oil and gas field development, in particular to a repeated fracturing parameter optimization design method of a fracture-cavity carbonate reservoir.
Background
In the oil and gas field development technology, a fracture-cavity type carbonate reservoir is a special carbonate reservoir, the reservoir is multiple in variety, pore media are complex, such as typical karst cave, dissolution holes, fine cracks and the like, so that the production difference of different layers of the fracture-cavity type carbonate is huge in the fracturing process, and great challenges are caused to the accuracy of fracturing design.
The repeated fracturing technology refers to the secondary or even tertiary reconstruction of the existing fracturing well, after repeated fracturing, the reservoir can not only promote the production for a certain period after initial fracturing, gradually generate closed cracks to open again, further enlarge the original reconstruction volume, but also form new cracks through a related process method, and the new cracks are turned to the non-mined stratum. However, because the stress field is induced to change under the conditions of reservoir failure and fracture stiffness deformation, the steering angle of a new fracture generated during repeated fracturing is not easy to control, and the steering fracture formed in many times is not ideal, so that the contact area between the repeated fracturing fracture and the oil and gas reservoir cannot be further enlarged, and the repeated fracturing effect is limited.
The hydraulic fracture parameter optimization mainly adopts numerical simulation as a main technical means, but the traditional hydraulic fracture parameter optimization method has the problems of low efficiency, poor calculation precision and the like. For this reason, it is necessary to introduce a proxy model to replace the numerical simulation calculation with a smaller calculation amount without reducing the accuracy of the calculation numerical simulation, thereby reducing the calculation cost. Common proxy model modeling methods include polynomial response surface method, kriging method, radial basis function method, etc. The quadratic polynomial response surface model is widely used due to good fitting accuracy and fitting efficiency. However, the repeated fracturing fracture parameter optimization design by using the proxy model and the polynomial response surface method is less studied at present.
The particle swarm optimization algorithm is a simple and efficient search algorithm, and is also a main method for optimizing the parameters of the fracturing fracture at present; however, as the optimization problem becomes more complex, the multi-objective optimization algorithm with excellent performance needs to be studied more deeply. However, the conventional particle swarm algorithm has some problems, such as that initial particles are randomly generated, and the diversity of the population is maintained, but the quality of partial particles is low, so that the quality and optimizing efficiency of the population are affected to a certain extent. Secondly, in the process of algorithm operation, particles are required to be continuously close to an individual extremum and a global extremum, so that all particles fly in the same direction, the particles tend to be identical, the diversity gradually disappears, and the later convergence speed and convergence precision of the algorithm are reduced. The competitive particle swarm algorithm is a modified algorithm of the basic particle swarm algorithm, and is different from the particle swarm algorithm in that particles are not only learned to individual optima and global optima, but failed particles are learned to winning particles through a competition mechanism. However, the optimization design of fracture parameters by using the competitive particle swarm algorithm is relatively rarely studied at present.
Disclosure of Invention
The invention aims at overcoming the defects in the prior art, and provides a repeated fracturing parameter optimization design method for a fracture-cavity carbonate reservoir, which effectively considers time scale effects of dynamic oil reservoir parameters, rock mechanical parameters and ground stress parameters, reduces the calculated amount of numerical simulation by a proxy model by setting a Net Present Value (NPV) value as a constraint condition, and finally optimizes the fracture-cavity carbonate fracturing parameters by a particle swarm intelligent learning method to obtain the optimal parameters of the fracture-cavity carbonate reservoir.
The invention relates to a repeated fracturing parameter optimization design method of a fracture-cavity carbonate reservoir, which adopts the following technical scheme: the method comprises the following steps:
firstly, building a structural framework of a target stratum based on a structural framework modeling technology of the voxels, and performing thickness calibration of each small layer by core description, logging, well logging and seismic data and combining with well-guide layering data to realize block three-dimensional carbonate geological modeling containing small layers;
secondly, adding key oil reservoir attributes to a geological model through a numerical simulation method by seismic inversion and well logging interpretation results to obtain a three-dimensional oil reservoir physical model containing permeability and porosity;
Thirdly, simulating three-dimensional natural cracks of the fracture-cavity body and discontinuous geologic bodies of the fracture-cavity body based on a random modeling method to obtain a three-dimensional discontinuous geologic body model;
fourthly, considering the spatial distribution heterogeneity of lithofacies lithology, and establishing a fracture-cavity carbonate reservoir three-dimensional rock mechanical model through phase attribute constraint; further considering the development distribution characteristics of the fracture-cavity body, and constructing a three-dimensional carbonate reservoir rock mechanical model with weakened local strength;
fifthly, constructing a ground stress field of the fracture cavity body, and performing space inversion on the constructed ground stress field through collected ground breaking experimental data, single well ground stress longitudinal section data calculated by logging and relevant experimental data of paleogeomagnetism, wave velocity anisotropy, acoustic emission and differential strain to obtain three-dimensional stress field distribution characteristics;
performing fracturing numerical simulation through the constructed fracture cavity carbonate reservoir attribute model, the rock mechanical model and the ground stress model, setting the pumping degree of the on-site actual hydraulic fracturing construction to obtain a fracture expansion form, and performing inversion correction on the initial fracture form of the fracture cavity carbonate reservoir by using on-site monitoring data;
taking the initial fracture morphology and the oil reservoir attribute as input parameters, carrying out oil reservoir numerical simulation, and completing history fitting through on-site data collection to obtain fracture-cavity carbonate reservoir pressure field distribution under the conditions of different development moments;
Introducing a fracture-cavity reservoir pressure field into a geomechanical simulator to perform four-dimensional stress field seepage-stress fluid-solid coupling numerical simulation, and further obtaining fracture-cavity carbonate reservoir stress field distribution under the conditions of different development moments;
(nine) screening the horizons needing repeated fracturing;
(ten) setting NPV parameters to be economically optimal as a final optimization target; constructing a proxy model of related numerical simulation by a Kriging method, and then carrying out repeated fracturing crack expansion-flow integrated numerical simulation by setting different repeated fracturing construction pumping procedures;
and eleventh, carrying out numerical simulation on the output of the temporary plugging repeated fracturing well by taking the real-time residual oil distribution characteristic as an initial condition and combining the real-time oil reservoir parameters, and carrying out fracturing parameter optimization by taking the optimal output and no interference and interleaving among cracks as targets to obtain an optimal design scheme of repeated fracturing of the target block.
Preferably, in the first step, the construction of the fracture-cavity carbonate reservoir structure model is completed, and the related structure model mainly comprises the establishment of a fault model and a layer model, and the specific modeling method comprises the following steps: firstly, an initial construction grid is established by using a large set of positions on the top surface of a special position; secondly, establishing a layer thickness map of each small layer of the fracture-cavity carbonate reservoir through drilling layering disclosed by the pilot well; thirdly, adding more construction control points for the horizontal well section by establishing a virtual well, and further carrying out constraint and fine correction on the construction form revealed by the horizontal well; and finally, core description, logging, well logging and seismic data, and completing the establishment of a horizon construction model of each small layer according to the small layer thickness obtained by geostatistics, thereby providing a fine construction grid for the establishment of a seam hole type carbonate reservoir attribute model in the next step.
Preferably, in the second step, the key attributes of the oil reservoir are increased for the geological model through fracture-cavity carbonate reservoir seismic inversion and logging interpretation results and through a numerical simulation method, in the process of building the attributes, a lithology model is built firstly, the lithology model is built, the drilling result and lithology distribution trend on the area need to be combined, the lithology model is built according to the correlation analysis of the carbonate lithology and the impedance inversion body through a proper variation function and then a sequential indication simulation method is combined, the key attributes of the oil reservoir, such as the porosity, the permeability and the oil saturation model, are mainly completed through numerical simulation through a sequential Gaussian simulation random algorithm, and the permeability field model and the oil saturation model need to be subjected to numerical simulation by taking the intentional porosity model as second variables in a synergetic manner; the relevant specific steps can be completed through the following four steps: firstly, determining a grid design, determining the transverse size of a grid through a seismic surface element, and determining the vertical size of the grid through logging resolution; secondly, coarsening the logging curves, sampling the logging curves of all wells into grids through which well tracks pass, and using the data as hard point data of subsequent numerical simulation; thirdly, carrying out inversion attribute resampling, and resampling the inversion attribute to a three-dimensional grid; fourthly, performing attribute modeling by combining well and earthquake, inverting the transverse distribution of the attribute serving as the control attribute of the soft data, taking the well logging data as the hard data, and controlling the vertical distribution of the attribute.
Preferably, in the third step, a three-dimensional natural fracture of the fracture-cavity body and a discontinuous geologic body of the fracture-cavity body are simulated based on a random modeling method, so as to obtain a three-dimensional discontinuous geologic body model; when the fracture-cavity model is constructed, on one hand, the related response of fracture-cavity carbonate rock earthquake needs to be considered, and on the other hand, the accumulated fracture density analysis is carried out by effectively utilizing the interpretation result of imaging logging fractures; the production rule, development density and size characteristics of natural cracks are obtained through core observation and imaging logging data, the fracture cavity body depiction is described through seismic attributes, response characteristics and space distribution rules of the karst cavity and the cracks in a research area are obtained based on seismic attribute root mean square and coherent body analysis, and the fracture solution distribution form of the research area is extracted by combining early drilling data and broken body geophysical prospecting identification data; the related key seismic attributes mainly comprise root mean square and coherent volume data; for small-scale natural cracks, the analysis results of area fracture, ant body data and the measurement results of core crack sizes are synthesized, and a power function statistical method of a fractal theory is adopted to quantify the crack size distribution rule.
Preferably, the specific operation of the fourth step is as follows, the rock mechanical parameters are mainly calculated by logging data, and the calculated rock mechanical parameters mainly comprise Young modulus, poisson's ratio and compressive strength; wherein Young's modulus, shear modulus and Poisson's ratio are main parameters describing the elastic deformation of the rock, and are collectively referred to as the elastic parameters of the rock; calculating dynamic elastic parameters by using the acoustic time difference, including longitudinal waves and transverse waves, and the density logging value; the formula for calculating Young's modulus using log data is:
（1）
The poisson ratio is calculated as:
（2）
the Poisson's ratio and the rock modulus can be used for obtaining the parameters of a shear modulus and a volume model, wherein the shear modulus represents the ratio of stress to tangential strain, and the calculation formula is as follows:
（3）
bulk modulus refers to the ratio of fluid pressure to bulk strain, and the calculation formula is;
（4）
preferably, the specific operation of the fifth step is as follows, the existence of the fracture-cavity body is considered, so on the basis of a three-dimensional rock mechanical parameter field, the distribution characteristics of the three-dimensional ground stress field are simulated by adopting a finite element method in combination with ground stress analysis test data, meanwhile, the stress value of the area near the fault is locally corrected by adopting a fault local stress correction technology, deflection analysis is carried out on the direction of the maximum horizontal main stress, deflection of the maximum main stress perpendicular to the trend of the fault is followed, and the minimum main stress is parallel to the related standard of the trend deflection of the fault;
（5）
in the method, in the process of the invention,σ H ，σ h maximum and minimum horizontal principal stress, MPa, respectively; and [ mu ] is the Poisson's ratio of the rock, dimensionless, E is the Young's modulus of the rock, MPa,β 1 ，β 2 the constructional stress coefficients in the directions of the maximum and minimum horizontal principal stresses are dimensionless; alpha is a bit coefficient, dimensionless;P p is the formation pore pressure, MPa;
the range of horizontal ground stress is obtained by restraining pore pressure and overburden pressure simultaneously, namely, a stress polygon is formed; in general, the level stress at any position in the ground is smaller than the boundary value of the stress polygon, because the friction force generated by the underground fault and the natural crack plays a certain role in controlling the level stress;
According to the stress polygon theory, the maximum principal stress upper limit of the walk-slip fault is as follows:
（6）
the lower limit of the minimum horizontal principal stress is:
（7）
wherein:S v is vertical stress and MPa;P p pore pressure, MPa;S H is the maximum level of effective stress, MPa;S h is the minimum level effective stress, MPa;q f parameters calculated for the internal friction angle.
Preferably, in the eighth step, the fracture-cavity reservoir pressure field is led into a geomechanical simulator to perform four-dimensional stress field seepage-stress fluid-solid coupling numerical simulation, and the permeability and rock mechanical parameter equations under different effective stress conditions are used for updating the three-dimensional gas reservoir model and the three-dimensional rock mechanical model; the strain field and the stress field around the crack are updated mainly by using an Oda method; further obtaining stress field distribution of the fracture-cavity carbonate reservoir under the conditions of different development moments; in order to improve the seepage-stress double-field coupling numerical simulation calculation accuracy and consider the influence of calculation load, a cross iterative coupling algorithm is adopted to realize the modeling analysis of the dynamic stress field.
Preferably, in step nine, a horizon screen is selected for which repeated fracturing is required, and for fracture-cavity carbonate reservoirs, a well that is low-yielding or shut-in, but does not produce water is selected as the primary candidate well.
Preferably, in step ten, the scheme of constructing the proxy model specifically using the Kriging method is as follows: firstly, determining parameter X required to be optimized for integrated optimization design of a fracturing horizontal well, and establishing an objective function; selecting a test design method to generate initial sample points; in designing, monte carlo sampling or latin hypercube sampling may be employed; calling an original model to obtain the real response of an initial sample point, carrying a variable X to obtain an objective function, and taking the obtained initial sample point and the response thereof as an initial sample library to obtain a one-to-one correspondence between input and output; constructing a single well agent model A by using the sample library obtained by the method, and constructing a fracturing parameter agent model B by using a kriging model and the same method; by taking the outputs of the two proxy models as the input of the comprehensive model C, NPV is taken as the output; and establishing a comprehensive model C by taking the cooperative relationship of the single well agent model A and the fracturing parameter agent model B into consideration in a constraint adding and sensitivity analysis mode.
Preferably, the specific implementation method of the step eleven is as follows: calculating proxy model accuracy: by determining coefficientsR 2 To evaluate; the precision is met, and the construction of the two proxy models is completed; adding a sampling point update model: particle swarm global optimization process step package Including initializing a particle swarm: determining the range and the value space of the parameters; randomly generating an initial particle group, wherein each particle represents the value of a group of parameters, and assigning a random speed to each particle; and (4) carrying out fitness evaluation: predicting the parameter combination of each particle by using the agent model to obtain a predicted objective function value; the agent model is trained by using the previous sample data, and learns the relation between the input parameters and the objective function values, so that the objective function values of the new parameter combination can be predicted; recording individual historical and global optima: recording, for each particle, its own historical best fitness and corresponding parameter combinations; in the whole particle swarm, recording the global optimal fitness and the corresponding parameter combination; and (3) optimizing: updating the speed and the position of the particles according to the historical optimal and global optimal information of the particles; repeating the steps of evaluating fitness and updating the optimal position; repeating the above process to select an individual with optimal fitness from the final particle swarm as an optimization result.
Compared with the prior art, the invention has the following beneficial effects:
(1) Compared with the existing fracture-cavity carbonate modeling technology, the method is based on a geological engineering integrated thought, realizes attribute interaction of multiple parameters and a platform through a grid interaction technology, carries out geological modeling, attribute modeling, rock mechanics and ground stress modeling on fracture-cavity carbonate, and greatly facilitates extraction of fracture-cavity carbonate reservoir repeated fracturing basic parameters;
(2) Compared with the existing fracture-cavity type carbonate dynamic stress field modeling technology, the fracture-cavity type carbonate dynamic stress field modeling method is characterized in that the fracture-cavity type carbonate dynamic stress field modeling is realized through double-field coupling of seepage-stress fields, double-field coupling solving calculation is realized through a cross iterative coupling algorithm, meanwhile, the fracture-cavity type carbonate characteristics are considered, hard point data are adopted to correct local stress, and the requirements of repeated fracture crack expansion design and yield calculation can be met;
(3) Compared with the existing repeated fracturing design optimization evaluation technology, the efficient crack parameter optimization method based on the agent model and the competitive particle swarm algorithm is provided, the simulated calculation workload can be reduced through the agent model, the convergence of the algorithm can be calculated through the improved competitive particle swarm algorithm which adopts a three-competition mechanism and combines the strong convex sparse operator, and the three-competition mechanism competitive particle swarm updates all particles after the three-competition mechanism by combining the classical PSO and the updating rule in the competitive particle swarm, so that the balance of algorithm exploration and development capability is ensured, the population diversity is improved, the searching efficiency of the population is improved, the faster acquisition of the optimal crack parameter is realized, and important technical support can be provided for subsequent repeated fracturing design guidance.
Drawings
FIG. 1 is a schematic diagram of a geological modeling result of a carbonate rock of a fracture-cavity body of a research block constructed by the invention;
FIG. 2 is a schematic diagram of the change of the well perimeter stress field of the invention for obtaining the primary fracturing of fracture-cavity carbonate rock;
FIG. 3 is a graph showing the numerical simulation results of a fracture-cavity carbonate reservoir;
FIG. 4 is a schematic diagram of a fracture-cavity body carbonate history fit completed at various stages of production according to the present invention;
FIG. 5 is a simulated morphology of repeated fracture propagation at different construction displacements of the present invention;
FIG. 6 is a flow chart of the repeated fracturing parameters optimization design of the carbonate fracture cavity of the present invention;
in the above figure, the fracture-cavity model 100, the fracture-cavity body 200, the fault 300 and the hydraulic fracture 400 are shown.
Detailed Description
The preferred embodiments of the present invention will be described below with reference to the accompanying drawings, it being understood that the preferred embodiments described herein are for illustration and explanation of the present invention only, and are not intended to limit the present invention.
Embodiment 1, the repeated fracturing parameter optimization design method of the fracture-cavity carbonate reservoir provided by the invention comprises the following steps:
firstly, building a structural framework of a target stratum based on a structural framework modeling technology of the voxels, and performing thickness calibration of each small layer by core description, logging, well logging and seismic data and combining with well-guide layering data to realize block three-dimensional carbonate geological modeling containing small layers;
Secondly, adding key oil reservoir attributes to a geological model through a numerical simulation method by seismic inversion and well logging interpretation results to obtain a three-dimensional oil reservoir physical model containing permeability and porosity;
thirdly, simulating three-dimensional natural cracks of the fracture-cavity body and discontinuous geologic bodies of the fracture-cavity body based on a random modeling method to obtain a three-dimensional discontinuous geologic body model;
fourthly, considering the spatial distribution heterogeneity of lithofacies lithology, and establishing a fracture-cavity carbonate reservoir three-dimensional rock mechanical model through phase attribute constraint; further considering the development distribution characteristics of the fracture-cavity body, and constructing a three-dimensional carbonate reservoir rock mechanical model with weakened local strength;
fifthly, constructing a ground stress field of the fracture cavity body, and performing space inversion on the constructed ground stress field through collected ground breaking experimental data, single well ground stress longitudinal section data calculated by logging and relevant experimental data of paleogeomagnetism, wave velocity anisotropy, acoustic emission and differential strain to obtain three-dimensional stress field distribution characteristics;
performing fracturing numerical simulation through the constructed fracture cavity carbonate reservoir attribute model, the rock mechanical model and the ground stress model, setting the pumping degree of the on-site actual hydraulic fracturing construction to obtain a fracture expansion form, and performing inversion correction on the initial fracture form of the fracture cavity carbonate reservoir by using on-site monitoring data;
Taking the initial fracture morphology and the oil reservoir attribute as input parameters, carrying out oil reservoir numerical simulation, and completing history fitting through on-site data collection to obtain fracture-cavity carbonate reservoir pressure field distribution under the conditions of different development moments;
introducing a fracture-cavity reservoir pressure field into a geomechanical simulator to perform four-dimensional stress field seepage-stress fluid-solid coupling numerical simulation, and further obtaining fracture-cavity carbonate reservoir stress field distribution under the conditions of different development moments;
(nine) screening the horizons needing repeated fracturing;
(ten) setting NPV parameters to be economically optimal as a final optimization target; constructing a proxy model of related numerical simulation by a Kriging method, and then carrying out repeated fracturing crack expansion-flow integrated numerical simulation by setting different repeated fracturing construction pumping procedures;
and eleventh, carrying out numerical simulation on the output of the temporary plugging repeated fracturing well by taking the real-time residual oil distribution characteristic as an initial condition and combining the real-time oil reservoir parameters, and carrying out fracturing parameter optimization by taking the optimal output and no interference and interleaving among cracks as targets to obtain an optimal design scheme of repeated fracturing of the target block.
Embodiment 2, referring to fig. 1-6, the invention refers to a method for optimizing and designing repeated fracturing parameters of a fracture-cavity carbonate reservoir, which comprises the following detailed steps:
(1) The construction of a fracture-cavity carbonate reservoir structure model is completed, the related structure model mainly comprises the establishment of a fault model and a layer model, and the specific modeling method comprises the following steps of: firstly, an initial construction grid is established by using a large set of horizons such as a special horizon top surface and the like; secondly, establishing a layer thickness map of each small layer of the fracture-cavity carbonate reservoir through drilling layering disclosed by the pilot well; thirdly, adding more construction control points for the horizontal well section by establishing a virtual well, and further carrying out constraint and fine correction on the construction form revealed by the horizontal well; finally, core description, logging, well logging and seismic data, and according to the thickness of the small layers obtained by geostatistics, building a horizon construction model of each small layer, and providing a fine construction grid for building a seam hole type carbonate reservoir attribute model in the next step;
(2) Adding key oil reservoir attributes to a geological model through fracture-cavity type carbonate reservoir seismic inversion and logging interpretation results and a numerical simulation method, firstly establishing a lithology model in the process of constructing attributes, wherein the establishment of the lithology model needs to combine drilling results and lithology distribution trends on areas, and establishing the lithology model through a proper variation function and a sequential indication simulation method according to correlation analysis of carbonate lithology and an impedance inversion body; the key properties of the oil reservoir, such as porosity, permeability, oil saturation model and the like, are mainly achieved through numerical simulation through a sequential Gaussian simulation random algorithm, wherein the permeability field model and the oil saturation model need to be coordinated with each other by taking the porosity model as a second variable to conduct numerical simulation. The relevant specific steps can be completed through the following four steps: firstly, determining a grid design, determining the transverse size of a grid through a seismic surface element, and determining the vertical size of the grid through logging resolution; secondly, coarsening the logging curves, sampling the logging curves of all wells into grids through which well tracks pass, and using the data as hard point data of subsequent numerical simulation; thirdly, carrying out inversion attribute resampling, and resampling the inversion attribute to a three-dimensional grid; fourthly, performing attribute modeling by combining well and earthquake, inverting the transverse distribution of the attribute serving as a soft data control attribute, taking logging data serving as hard data, and controlling the vertical distribution of the attribute;
(3) Simulating three-dimensional natural cracks of the fracture-cavity body, discontinuous geologic bodies such as the fracture-cavity body and the like based on a random modeling method to obtain a three-dimensional discontinuous geologic body model; when the fracture-cavity model is constructed, on one hand, the related response of fracture-cavity type carbonate rock earthquake needs to be considered, and on the other hand, the accumulated fracture density analysis is carried out by effectively utilizing the interpretation result of imaging well logging fractures. The production law, development density and size characteristics of natural cracks are mainly obtained through rock core observation, imaging logging and other data, the fracture cavity body depiction is mainly described through seismic attributes, response characteristics and space distribution laws of karst cavities and cracks in a research area can be obtained based on seismic attribute root mean square and coherent body analysis, and the fracture solution distribution form of the research area is extracted by combining early drilling data and broken body geophysical prospecting identification data. The related key seismic attributes mainly comprise key data such as root mean square, coherence and the like; for small-scale natural cracks, mainly integrating an area fracture interpretation result, ant body data and a core crack size measurement result, and quantifying a crack size distribution rule by adopting a power function statistical method of a fractal theory.
(4) Taking the spatial distribution heterogeneity of lithofacies lithology into consideration, and establishing a three-dimensional rock mechanical model of the fracture-cavity carbonate reservoir through phase attribute constraint; further considering the development distribution characteristics of the fracture-cavity body, constructing a three-dimensional carbonate reservoir rock mechanical model with weakened local strength, wherein rock mechanical parameters explained by a single well are mainly calculated through logging data, and the calculated rock mechanical parameters mainly comprise Young modulus, poisson ratio, compressive strength and the like; wherein Young's modulus, shear modulus, poisson's ratio and the like are main parameters describing the elastic deformation of the rock, and are collectively called the elastic parameters of the rock. Dynamic elastic parameters can be calculated using sonic moveout (longitudinal and transverse) and densitometry values. The formula for calculating Young's modulus using log data is:
（1）
The poisson ratio is calculated as:
（2）
parameters such as shear modulus, volume model and the like can be obtained by using Poisson's ratio and rock modulus, and the shear modulus represents the ratio of stress to tangential strain, and the calculation formula is as follows:
（3）
bulk modulus refers to the ratio of fluid pressure to bulk strain, and the calculation formula is;
（4）
(5) Carrying out the construction of a ground stress field of a fracture cavity body, and carrying out space inversion on the constructed ground stress field through collected ground breaking experimental data, single well ground stress longitudinal section data calculated by logging, and relevant experimental data such as paleogeomagnetism, wave velocity anisotropy, acoustic emission, differential strain and the like to obtain a three-dimensional stress field distribution characteristic; considering the existence of a fracture-cavity body, simulating the distribution characteristics of a three-dimensional ground stress field by combining ground stress analysis test data on the basis of a three-dimensional rock mechanical parameter field, and simultaneously locally correcting the stress value of a region near a fault by using a fault local stress correction technology, and performing deflection analysis on the direction of the maximum horizontal main stress, wherein the maximum main stress is generally followed by a related standard that deflection is perpendicular to the trend of the fault, and the minimum main stress is parallel to the trend of the fault;
（5）
in the method, in the process of the invention,σ H ，σ h maximum and minimum horizontal principal stress, MPa, respectively; and [ mu ] is the Poisson's ratio of the rock, dimensionless, E is the Young's modulus of the rock, MPa, β 1 ，β 2 The constructional stress coefficients in the directions of the maximum and minimum horizontal principal stresses are dimensionless; alpha is a bit coefficient, dimensionless;P p is the formation pore pressure, MPa.
The range of horizontal ground stress may be constrained by both pore pressure and overburden pressure, i.e., forming a stress polygon. In general, the level of horizontal stress at any position in the ground is smaller than the boundary value of a stress polygon, because the friction force generated by the underground fault and the natural cracks plays a certain role in controlling the level of the horizontal stress.
According to the stress polygon theory, the maximum principal stress upper limit of the walk-slip fault is as follows:
（6）
the lower limit of the minimum horizontal principal stress is:
（7）
wherein:S v is vertical stress and MPa;P p pore pressure, MPa;S H is the maximum level of effective stress, MPa;S h is the minimum level effective stress, MPa;q f parameters calculated for internal friction angle;
(6) Carrying out fracturing numerical simulation through the constructed fracture cavity carbonate reservoir attribute model, the rock mechanical model and the ground stress model, setting the pumping degree of the on-site actual hydraulic fracturing construction, obtaining a crack expansion form, and carrying out inversion correction on the initial crack form of the fracture cavity carbonate reservoir by utilizing on-site monitoring data;
(7) Taking the initial fracture morphology and the oil reservoir attribute as input parameters, carrying out oil reservoir numerical simulation, and completing history fitting through on-site data collection to obtain fracture-cavity carbonate reservoir pressure field distribution under the conditions of different development moments;
(8) Introducing a fracture-cavity reservoir pressure field into a geomechanical simulator to perform four-dimensional stress field seepage-stress fluid-solid coupling numerical simulation, and updating a three-dimensional gas reservoir model and a three-dimensional rock mechanical model by using permeability and rock mechanical parameter equations under different effective stress conditions; the strain field and the stress field around the crack are updated mainly by using an Oda method; further obtaining stress field distribution of the fracture-cavity carbonate reservoir under the conditions of different development moments; in order to improve the seepage-stress double-field coupling numerical simulation calculation precision and consider the influence of calculation load, a cross iterative coupling algorithm is adopted to realize the modeling analysis of the dynamic stress field;
(9) Selecting a low-yield or shut-in well but no water outlet well as a main candidate well for a fracture-cavity type carbonate reservoir;
(10) Setting NPV parameters, and taking economic optimization as a final optimization target; constructing a proxy model of related numerical simulation, and then carrying out repeated fracturing crack expansion-flow integrated numerical simulation by setting different repeated fracturing construction pumping programs; the scheme for constructing the proxy model by the Kriging method is as follows: firstly, determining parameter X required to be optimized for integrated optimization design of a fracturing horizontal well, and establishing an objective function; selecting a test design method to generate initial sample points; in designing, monte carlo sampling or latin hypercube sampling may be employed; calling an original model to obtain the real response of an initial sample point, carrying a variable X to obtain an objective function, and taking the obtained initial sample point and the response thereof as an initial sample library to obtain a one-to-one correspondence between input and output; the single well agent model A is constructed by the sample library obtained by the method, and a kriging model can be selected. Then constructing a fracturing parameter agent model B by the same method; by taking the outputs of the two proxy models as inputs to the integrated model C, NPV is the output. Establishing a comprehensive model C by adding constraints (such as constraining the half length of a crack to prevent pressure channeling), sensitivity analysis and other modes and considering the cooperative relationship of the A, B model;
(11) And carrying out fracturing parameter optimization by adopting a three-competition mechanism and combining an improved competition particle swarm algorithm of a strong convex sparse operator and aiming at optimizing yield and avoiding interference and interleaving among cracks, so as to obtain an optimal design scheme of repeated fracturing of the target block fracture-cavity type carbonate reservoir. The specific implementation steps are as follows: calculating proxy model accuracy: by determining coefficientsR 2 To evaluate; and if the precision is satisfied, the construction of the two proxy models is completed. Adding a sampling point update model: the particle swarm global optimization process step includes initializing a particle swarm: the range and the value space of the parameters are determined. Randomly generating an initial particle group, wherein each particle represents the value of a group of parameters, and assigning a random speed to each particle; and (4) carrying out fitness evaluation: and predicting the parameter combination of each particle by using the proxy model to obtain a predicted objective function value. The agent model is trained by using the previous sample data, and learns the relation between the input parameters and the objective function values, so that the objective function values of the new parameter combination can be automatically predicted; recording individual historical and global optima: for each particle, its own historical best fitness and corresponding parameter combinations are recorded. In the whole particle swarm, recording the global optimal fitness and the corresponding parameter combination; and (3) optimizing: the speed and position of the particles are updated according to the historical best and global best information of the particles themselves. The steps of evaluating fitness and updating the best position are repeated. Repeating the above process to select an individual with optimal fitness from the final particle swarm as an optimization result. The main repeated fracturing optimization parameters comprise horizontal section length, fracturing fluid volume, sand ratio, displacement, pad fluid proportion and the like).
Compared with the particle swarm algorithm, the competition particle swarm algorithm can effectively avoid trapping in local optimum, and the diversity of particles is increased. The three-competition mechanism competition particle swarm is a competition particle swarm algorithm improved on the basis of the competition particle swarm. The three-competition mechanism the competition particle swarm adopts a three-competition mechanism with higher convergence speed than the two-to-two competition in the competition particle swarm. The three-competition mechanism is to divide the particles of the population into three sub-populations equally, and randomly select one particle from each sub-population to perform two-to-two competition among the three particles.
In view of the updating rule of PSO, the winning particles are learned to global optimum, the speed is finely adjusted, and the convergence of the algorithm is accelerated. The speed update procedure for the winning particles is as follows:
, (8)
wherein,is the speed of the winning particle, and +.>、/>、/>As above, the description is omitted.
、/>And the position of the winning particles are updated by the following rules:
， (9)
wherein the method comprises the steps of。
The above description is only a few preferred embodiments of the present invention, and any person skilled in the art may make modifications to the above described embodiments or make modifications to the same. Accordingly, the corresponding simple modifications or equivalent changes according to the technical scheme of the present invention fall within the scope of the claimed invention.
Claims (10)
1. A repeated fracturing parameter optimization design method of a fracture-cavity carbonate reservoir is characterized by comprising the following steps: the method comprises the following steps:
firstly, building a structural framework of a target stratum based on a structural framework modeling technology of the voxels, and performing thickness calibration of each small layer by core description, logging, well logging and seismic data and combining with well-guide layering data to realize block three-dimensional carbonate geological modeling containing small layers;
secondly, adding key oil reservoir attributes to a geological model through a numerical simulation method by seismic inversion and well logging interpretation results to obtain a three-dimensional oil reservoir physical model containing permeability and porosity;
thirdly, simulating three-dimensional natural cracks of the fracture-cavity body and discontinuous geologic bodies of the fracture-cavity body based on a random modeling method to obtain a three-dimensional discontinuous geologic body model;
fourthly, considering the spatial distribution heterogeneity of lithofacies lithology, and establishing a fracture-cavity carbonate reservoir three-dimensional rock mechanical model through phase attribute constraint; further considering the development distribution characteristics of the fracture-cavity body, and constructing a three-dimensional carbonate reservoir rock mechanical model with weakened local strength;
fifthly, constructing a ground stress field of the fracture cavity body, and performing space inversion on the constructed ground stress field through collected ground breaking experimental data, single well ground stress longitudinal section data calculated by logging and relevant experimental data of paleogeomagnetism, wave velocity anisotropy, acoustic emission and differential strain to obtain three-dimensional stress field distribution characteristics;
Performing fracturing numerical simulation through the constructed fracture cavity carbonate reservoir attribute model, the rock mechanical model and the ground stress model, setting the pumping degree of the on-site actual hydraulic fracturing construction to obtain a fracture expansion form, and performing inversion correction on the initial fracture form of the fracture cavity carbonate reservoir by using on-site monitoring data;
taking the initial fracture morphology and the oil reservoir attribute as input parameters, carrying out oil reservoir numerical simulation, and completing history fitting through on-site data collection to obtain fracture-cavity carbonate reservoir pressure field distribution under the conditions of different development moments;
introducing a fracture-cavity reservoir pressure field into a geomechanical simulator to perform four-dimensional stress field seepage-stress fluid-solid coupling numerical simulation, and further obtaining fracture-cavity carbonate reservoir stress field distribution under the conditions of different development moments;
(nine) screening the horizons needing repeated fracturing;
(ten) setting NPV parameters to be economically optimal as a final optimization target; constructing a proxy model of related numerical simulation by a Kriging method, and then carrying out repeated fracturing crack expansion-flow integrated numerical simulation by setting different repeated fracturing construction pumping procedures;
And eleventh, carrying out numerical simulation on the output of the temporary plugging repeated fracturing well by taking the real-time residual oil distribution characteristic as an initial condition and combining the real-time oil reservoir parameters, and carrying out fracturing parameter optimization by taking the optimal output and no interference and interleaving among cracks as targets to obtain an optimal design scheme of repeated fracturing of the target block.
2. The fracture-cavity carbonate reservoir repeated fracturing parameter optimization design method of claim 1, wherein the method is characterized by comprising the following steps of: in the first step, the construction of a fracture-cavity carbonate reservoir structure model is completed, the related structure model mainly comprises the establishment of a fault model and a layer model, and the specific modeling method comprises the following steps: firstly, an initial construction grid is established by using a large set of positions on the top surface of a special position; secondly, establishing a layer thickness map of each small layer of the fracture-cavity carbonate reservoir through drilling layering disclosed by the pilot well; thirdly, adding more construction control points for the horizontal well section by establishing a virtual well, and further carrying out constraint and fine correction on the construction form revealed by the horizontal well; and finally, core description, logging, well logging and seismic data, and completing the establishment of a horizon construction model of each small layer according to the small layer thickness obtained by geostatistics, thereby providing a fine construction grid for the establishment of a seam hole type carbonate reservoir attribute model in the next step.
3. The fracture-cavity carbonate reservoir repeated fracturing parameter optimization design method according to claim 2, wherein the method is characterized in that: in the second step, through fracture-cavity carbonate reservoir seismic inversion and logging interpretation results, adding oil reservoir key attributes to a geological model through a numerical simulation method, in the process of building attributes, firstly building a lithology model, wherein the building of the lithology model needs to be combined with drilling results and lithology distribution trends on areas, and according to correlation analysis of carbonate lithology and an impedance inversion body, building the lithology model through a proper variation function and a sequential indication simulation method, and the oil reservoir key attributes, such as porosity, permeability and oil saturation model, are mainly subjected to numerical simulation through a sequential Gaussian simulation random algorithm, wherein the permeability field model and the oil saturation model need to be subjected to numerical simulation in cooperation with the porosity model as a second variable; the relevant specific steps can be completed through the following four steps: firstly, determining a grid design, determining the transverse size of a grid through a seismic surface element, and determining the vertical size of the grid through logging resolution; secondly, coarsening the logging curves, sampling the logging curves of all wells into grids through which well tracks pass, and using the data as hard point data of subsequent numerical simulation; thirdly, carrying out inversion attribute resampling, and resampling the inversion attribute to a three-dimensional grid; fourthly, performing attribute modeling by combining well and earthquake, inverting the transverse distribution of the attribute serving as the control attribute of the soft data, taking the well logging data as the hard data, and controlling the vertical distribution of the attribute.
4. The fracture-cavity carbonate reservoir repeated fracturing parameter optimization design method according to claim 3, wherein the method is characterized in that: in the third step, simulating a three-dimensional natural fracture of the fracture-cavity body and a discontinuous geologic body of the fracture-cavity body based on a random modeling method to obtain a three-dimensional discontinuous geologic body model; when the fracture-cavity model is constructed, on one hand, the related response of fracture-cavity carbonate rock earthquake needs to be considered, and on the other hand, the accumulated fracture density analysis is carried out by effectively utilizing the interpretation result of imaging logging fractures; the production rule, development density and size characteristics of natural cracks are obtained through core observation and imaging logging data, the fracture cavity body depiction is described through seismic attributes, response characteristics and space distribution rules of the karst cavity and the cracks in a research area are obtained based on seismic attribute root mean square and coherent body analysis, and the fracture solution distribution form of the research area is extracted by combining early drilling data and broken body geophysical prospecting identification data; the related key seismic attributes mainly comprise root mean square and coherent volume data; for small-scale natural cracks, the analysis results of area fracture, ant body data and the measurement results of core crack sizes are synthesized, and a power function statistical method of a fractal theory is adopted to quantify the crack size distribution rule.
5. The fracture-cavity carbonate reservoir repeated fracturing parameter optimization design method of claim 4, wherein the method is characterized by comprising the following steps of: the rock mechanical parameters are calculated by logging data, and the calculated rock mechanical parameters mainly comprise Young modulus, poisson's ratio and compressive strength; wherein Young's modulus, shear modulus and Poisson's ratio are main parameters describing the elastic deformation of the rock, and are collectively referred to as the elastic parameters of the rock; calculating dynamic elastic parameters by using the acoustic time difference, including longitudinal waves and transverse waves, and the density logging value; the formula for calculating Young's modulus using log data is:
（1）
the poisson ratio is calculated as:
（2）
the Poisson's ratio and the rock modulus can be used for obtaining the parameters of a shear modulus and a volume model, wherein the shear modulus represents the ratio of stress to tangential strain, and the calculation formula is as follows:
（3）
bulk modulus refers to the ratio of fluid pressure to bulk strain, and the calculation formula is;
（4）。
6. the fracture-cavity carbonate reservoir repeated fracturing parameter optimization design method of claim 5, wherein the method is characterized by comprising the following steps of: the specific operation of the fifth step is as follows, the existence of a fracture-cavity body is considered, so on the basis of a three-dimensional rock mechanical parameter field, the distribution characteristics of the three-dimensional ground stress field are simulated by adopting a finite element method in combination with ground stress analysis test data, meanwhile, the stress value of a region near a fault is locally corrected by adopting a fault local stress correction technology, deflection analysis is carried out on the direction of the maximum horizontal main stress, deflection of the maximum main stress perpendicular to the fault trend is followed, and the minimum main stress is parallel to the relevant standard of the fault trend deflection;
（5）
In the method, in the process of the invention,σ H ，σ h maximum and minimum horizontal principal stress, MPa, respectively; and [ mu ] is the Poisson's ratio of the rock, dimensionless, E is the Young's modulus of the rock, MPa,β 1 ，β 2 the constructional stress coefficients in the directions of the maximum and minimum horizontal principal stresses are dimensionless; alpha is a bit coefficient, dimensionless;P p is the formation pore pressure, MPa;
the range of horizontal ground stress is obtained by restraining pore pressure and overburden pressure simultaneously, namely, a stress polygon is formed; in general, the level stress at any position in the ground is smaller than the boundary value of the stress polygon, because the friction force generated by the underground fault and the natural crack plays a certain role in controlling the level stress;
according to the stress polygon theory, the maximum principal stress upper limit of the walk-slip fault is as follows:
（6）
the lower limit of the minimum horizontal principal stress is:
（7）
wherein:S v is vertical stress and MPa;P p pore pressure, MPa;S H is the maximum level of effective stress, MPa;S h is the minimum level effective stress, MPa;q f parameters calculated for the internal friction angle.
7. The fracture-cavity carbonate reservoir repeated fracturing parameter optimization design method of claim 6, wherein the method is characterized by comprising the following steps of: in the eighth step, the fracture-cavity reservoir pressure field is led into a geomechanical simulator to perform four-dimensional stress field seepage-stress fluid-solid coupling numerical simulation, and a three-dimensional gas reservoir model and a three-dimensional rock mechanical model are updated by applying permeability and rock mechanical parameter equations under different effective stress conditions; the strain field and the stress field around the crack are updated mainly by using an Oda method; further obtaining stress field distribution of the fracture-cavity carbonate reservoir under the conditions of different development moments; in order to improve the seepage-stress double-field coupling numerical simulation calculation accuracy and consider the influence of calculation load, a cross iterative coupling algorithm is adopted to realize the modeling analysis of the dynamic stress field.
8. The fracture-cavity carbonate reservoir repeated fracturing parameter optimization design method of claim 7, wherein the method is characterized by comprising the following steps of: in step nine, selecting a low-yield or shut-in well but no-water well as a main candidate well for a fracture-cavity type carbonate reservoir.
9. The fracture-cavity carbonate reservoir repeated fracturing parameter optimization design method of claim 8, wherein the method is characterized by comprising the following steps of: in step ten, the scheme of constructing the proxy model by specifically adopting the Kriging method is as follows: firstly, determining parameter X required to be optimized for integrated optimization design of a fracturing horizontal well, and establishing an objective function; selecting a test design method to generate initial sample points; in designing, monte carlo sampling or latin hypercube sampling may be employed; calling an original model to obtain the real response of an initial sample point, carrying a variable X to obtain an objective function, and taking the obtained initial sample point and the response thereof as an initial sample library to obtain a one-to-one correspondence between input and output; constructing a single well agent model A by using the sample library obtained by the method, and constructing a fracturing parameter agent model B by using a kriging model and the same method; by taking the outputs of the two proxy models as the input of the comprehensive model C, NPV is taken as the output; and establishing a comprehensive model C by taking the cooperative relationship of the single well agent model A and the fracturing parameter agent model B into consideration in a constraint adding and sensitivity analysis mode.
10. The fracture-cavity carbonate reservoir repeated fracturing parameter optimization design method of claim 9, wherein the method is characterized by comprising the following steps of: the specific implementation method of the step eleven is as follows: calculating proxy model accuracy: by determining coefficientsR 2 To evaluate; the precision is met, and the construction of the two proxy models is completed; adding a sampling point update model: the particle swarm global optimization process step includes initializing a particle swarm: determining the range and the value space of the parameters; randomly generating an initial particle group, wherein each particle represents the value of a group of parameters, and assigning a random speed to each particle; and (4) carrying out fitness evaluation: predicting the parameter combination of each particle by using the agent model to obtain a predicted objective function value; the proxy model uses previous sample data for performingTraining, the relation between the input parameters and the objective function values is learned, so that the objective function values of new parameter combinations can be predicted; recording individual historical and global optima: recording, for each particle, its own historical best fitness and corresponding parameter combinations; in the whole particle swarm, recording the global optimal fitness and the corresponding parameter combination; and (3) optimizing: updating the speed and the position of the particles according to the historical optimal and global optimal information of the particles; repeating the steps of evaluating fitness and updating the optimal position; repeating the above process to select an individual with optimal fitness from the final particle swarm as an optimization result.
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