CN113779764A - Quantitative evaluation method and device for shale gas reservoir fracturing fracture network parameters - Google Patents

Abstract

The specification provides a quantitative evaluation method and device for shale gas reservoir fracturing fracture network parameters. Based on the method, the preset normalization processing can be firstly carried out on the acquired production data of the flow-back stage and the production data of the production stage of the target area, so that the normalized production data of the flow-back stage and the normalized production data of the production stage are obtained; determining a first fracture network parameter based on the flow characteristics according to the production data normalized in the flow-back stage; according to the production data after the production stage normalization, a linear analysis function of a matrix linear flow stage under a target area discrete fracture network is constructed; determining a second fracture network parameter according to the function; and then comprehensively utilizing the two fracture network parameters of the first fracture network parameter and the second fracture network parameter, and combining the production data after the normalization of the flowback stage and the production data after the normalization of the production stage to accurately determine the target fracture parameters of the discrete fracture network in the target area.

Description

Quantitative evaluation method and device for shale gas reservoir fracturing fracture network parameters

Technical Field

The specification belongs to the technical field of oil and gas development, and particularly relates to a quantitative evaluation method and device for shale gas reservoir fracturing fracture network parameters.

Background

Generally, when oil and gas development is carried out, a horizontal well volume fracturing needs to be carried out on a reservoir area firstly, so that an artificial fracture filled with proppant is formed in a near well area. After the volume fracturing of the horizontal well is finished, for a reservoir region with strong natural fracture development, induced fractures formed by shearing and sliding of the natural fractures can also develop in a near-well region in a large scale. Therefore, after fracturing, the fracturing fluid is likely to remain in the matrix of the artificial fractures, induced fractures, and in the vicinity of the fractures, and needs to be flowback first and then produced.

Aiming at the complex production scene, the fracture parameters of the discrete fracture network of the fractured reservoir region are often difficult to accurately determine based on the existing method.

In view of the above problems, no effective solution has been proposed.

Disclosure of Invention

The specification provides a quantitative evaluation method and device for shale gas reservoir fracturing fracture network parameters, which can accurately determine target fracture parameters of a discrete fracture network in a target area after the volume fracturing of a horizontal well is finished.

The embodiment of the specification provides a quantitative evaluation method for shale gas reservoir fracturing fracture network parameters, which comprises the following steps:

acquiring production data of a flowback stage and production data of a production stage of a target area;

respectively performing preset normalization processing on the production data of the flowback stage and the production data of the production stage to obtain normalized production data of the flowback stage and normalized production data of the production stage;

determining a first fracture network parameter according to the normalized production data of the flowback stage;

according to the production data normalized in the production stage, a linear analysis function of a matrix linear flow stage in a discrete fracture network in a target area is constructed; determining a second fracture network parameter according to the straight line analysis function;

and determining a target crack parameter of the discrete crack network in the target area according to the production data after the normalization of the flowback stage, the production data after the normalization of the production stage, the first crack network parameter and the second crack network parameter.

In some embodiments, the target region comprises a shale gas reservoir region.

In some embodiments, obtaining production data for the flowback stage and production data for the production stage of the target area comprises:

acquiring production data of a flowback stage by acquiring a daily measured value, a daily gas production rate and a daily water production rate of the bottom hole pressure of a target area in the flowback stage;

and acquiring the daily measured value, the daily gas production rate and the daily water production rate of the bottom hole pressure of the target area in the production stage to obtain the production data of the production stage.

In some embodiments, the preset normalization process is performed by using the production data of the flow-back stage, and includes:

and respectively carrying out preset normalization processing on the time parameter and the pressure parameter of the flow-back stage by using the production data of the flow-back stage according to the following formula:

wherein X is a normalized time parameter (mu)_gc^* _mt)_iIs the product of the gas viscosity at the initial pressure and the integrated compression factor, mu_gIs the viscosity of the gas at the initial pressure, c^* _mtIs a comprehensive compression factor, q, considering the adsorption and desorption of the shale gas under the initial pressure_gThe amount of the generated gas is the daily gas amount,

is the product of the gas viscosity at the average bottom hole pressure and the integrated compressibility factor, t is time; y is the normalized pressure parameter, p_iAs initial pressure, p_wM () represents the corresponding pseudo pressure of the gas as a daily measurement of the bottom hole pressure.

In some embodiments, determining a first fracture network parameter from the normalized production data of the flowback stage includes:

determining the water-gas two-phase dynamic flow characteristics of each flow stage in a plurality of flow stages contained in the flow-back stage according to the normalized production data of the flow-back stage;

and determining a first fracture network parameter according to the water-gas two-phase dynamic flow characteristics of each of the plurality of flow stages.

In some embodiments, constructing a linear analysis function of a linear flow phase of the matrix under the target area discrete fracture network according to the normalized production data of the production phase comprises:

calculating a dimensionless bottom hole pressure local solution of the discrete fracture network of the target area in the matrix linear flow stage according to the normalized production data of the production stage;

and constructing a linear analysis function of the matrix linear flow stage under the target area discrete fracture network according to the dimensionless bottom hole pressure local solution of the target area discrete fracture network in the matrix linear flow stage.

In some embodiments, constructing a straight line analysis function of the linear flow phase of the matrix under the target area discrete fracture network comprises:

constructing a linear analysis function of a matrix linear flow stage under a target area discrete fracture network according to the following formula:

Y＝mX+b

wherein the content of the first and second substances,

wherein X is a normalized time parameter, Y is a normalized pressure parameter, m is a preset slope term, and b is a preset intercept termH is the reservoir thickness of the target zone, T is the temperature, phi_mIs the formation porosity, L, of the target zone_hfLength of horizontal well volume fracture for target zone, w_hfWidth, k, of horizontal well volume fracture for target zone_mIs the permeability, k, of the formation in the target zone_hfPermeability of horizontal well volume fracturing fracture for target zone (mu)_gc^* _mt)_iIs the product of the gas viscosity at the initial pressure and the integrated compression factor.

In some embodiments, determining a target fracture parameter of a target area discrete fracture network according to the production data normalized at the flowback stage, the production data normalized at the production stage, the first fracture network parameter, and the second fracture network parameter includes:

and fitting the daily gas production rate by using the first crack network parameter, the second crack network parameter, the normalized production data in the flowback stage and the normalized production data in the production stage and adjusting the half length and the permeability of the crack so as to obtain the target crack parameter of the target area discrete crack network which meets the precision requirement.

The embodiment of the present specification further provides a quantitative evaluation device for shale gas reservoir fracturing fracture network parameters, including:

the acquisition module is used for acquiring the production data of the flowback stage and the production data of the production stage of the target area;

the normalization module is used for respectively carrying out preset normalization processing on the production data of the flowback stage and the production data of the production stage to obtain the normalized production data of the flowback stage and the normalized production data of the production stage;

the first determining module is used for determining a first fracture network parameter according to the production data normalized in the flowback stage;

the second determining module is used for constructing a linear analysis function of the matrix linear flow stage under the discrete fracture network of the target area according to the production data normalized by the production stage; determining a second fracture network parameter according to the straight line analysis function;

and the third determining module is used for determining the target crack parameters of the target area discrete crack network according to the normalized production data of the flowback stage, the normalized production data of the production stage, the first crack network parameters and the second crack network parameters.

Embodiments of the present specification also provide a computer readable storage medium having stored thereon computer instructions that, when executed, perform the steps of: acquiring production data of a flowback stage and production data of a production stage of a target area; respectively performing preset normalization processing on the production data of the flowback stage and the production data of the production stage to obtain normalized production data of the flowback stage and normalized production data of the production stage; determining a first fracture network parameter according to the normalized production data of the flowback stage; according to the production data normalized in the production stage, a linear analysis function of a matrix linear flow stage in a discrete fracture network in a target area is constructed; determining a second fracture network parameter according to the straight line analysis function; and determining a target crack parameter of the discrete crack network in the target area according to the production data after the normalization of the flowback stage, the production data after the normalization of the production stage, the first crack network parameter and the second crack network parameter.

The quantitative evaluation method and device for shale gas reservoir fracturing fracture network parameters provided by the embodiment of the specification can firstly perform preset normalization processing on the acquired production data of the flowback stage and the production data of the production stage of the target area after the volume fracturing of the horizontal well is finished, so as to obtain the normalized production data of the flowback stage and the normalized production data of the production stage; determining a first crack network parameter based on water-gas two-phase flow characteristics according to the production data after normalization of the flowback stage; according to the production data after the production stage normalization, a linear analysis function of a matrix linear flow stage under a target area discrete fracture network is constructed; determining a second fracture network parameter according to the function; and then the two fracture network parameters of the first fracture network parameter and the second fracture network parameter can be comprehensively utilized at the same time, and the target fracture parameters of the discrete fracture network in the target area after the volume fracturing of the horizontal well is finished are accurately determined by combining the normalized production data in the flowback stage and the normalized production data in the production stage, so that the determination errors can be effectively reduced, and the fracture network parameters with higher precision in a complex production scene can be obtained.

Drawings

In order to more clearly illustrate the embodiments of the present specification, the drawings needed to be used in the embodiments will be briefly described below, and the drawings in the following description are only some of the embodiments described in the specification, and it is obvious to those skilled in the art that other drawings can be obtained based on the drawings without any inventive work.

Fig. 1 is a schematic flow chart of a quantitative evaluation method for shale gas reservoir fracture network parameters, provided in an embodiment of the present description;

FIG. 2 is a schematic diagram illustrating an embodiment of a quantitative evaluation method for fracture network parameters of a shale gas reservoir provided by an embodiment of the present disclosure;

FIG. 3 is a schematic diagram illustrating an embodiment of a quantitative evaluation method for fracture network parameters of a shale gas reservoir provided by an embodiment of the present disclosure;

FIG. 4 is a schematic diagram illustrating an embodiment of a quantitative evaluation method for fracture network parameters of a shale gas reservoir provided by an embodiment of the present disclosure;

fig. 5 is a schematic structural component diagram of a server provided in an embodiment of the present specification.

Detailed Description

In order to make those skilled in the art better understand the technical solutions in the present specification, the technical solutions in the embodiments of the present specification will be clearly and completely described below with reference to the drawings in the embodiments of the present specification, and it is obvious that the described embodiments are only a part of the embodiments of the present specification, and not all of the embodiments. All other embodiments obtained by a person skilled in the art based on the embodiments in the present specification without any inventive step should fall within the scope of protection of the present specification.

Referring to fig. 1, an embodiment of the present specification provides a quantitative evaluation method for a fracture network parameter of a shale gas reservoir. When the method is implemented, the following contents can be included:

s101: acquiring production data of a flowback stage and production data of a production stage of a target area;

s102: respectively performing preset normalization processing on the production data of the flowback stage and the production data of the production stage to obtain normalized production data of the flowback stage and normalized production data of the production stage;

s103: determining a first fracture network parameter according to the normalized production data of the flowback stage;

s104: according to the production data normalized in the production stage, a linear analysis function of a matrix linear flow stage in a discrete fracture network in a target area is constructed; determining a second fracture network parameter according to the straight line analysis function;

s105: and determining a target crack parameter of the discrete crack network in the target area according to the production data after the normalization of the flowback stage, the production data after the normalization of the production stage, the first crack network parameter and the second crack network parameter.

In some embodiments, the target area may specifically include a shale gas reservoir area. Such as a reservoir zone containing a shale gas reservoir to be mined.

For the target area, when oil and gas development is specifically carried out, horizontal well volume fracturing needs to be carried out firstly; after fracturing is finished, performing fracturing fluid flowback on the area (corresponding to a flowback stage); and after the flowback is finished, carrying out production mining on the area (corresponding to a production stage).

In some embodiments, the applicant considers that in the above real and complex production scenario, first, in the flowback phase, the seepage environment of the fracturing fluid flowback is mainly the fracture, which is different from the seepage environment in the production phase (mainly the fracture and the matrix). Among these, in the production phase, the use of fracturing is often of interest to maximize the mobility of the matrix.

Further, during the flowback phase, formation fluids are also produced during flowback of the fracturing fluid, resulting in a two-phase (gas and water) flow process involved during flowback of the fracturing fluid during the flowback phase of the shale gas reservoir area.

The existing method for determining the crack network parameters usually only considers the seepage environment characteristics of the flow-back stage; when the seepage environment characteristics of the flowback stage are considered, only a single-phase flow process is usually noticed, so that the determined fracture network parameter error is large, the accuracy is low, and the subsequent production and exploitation of oil gas are influenced.

In view of the above circumstances, the applicant has proposed a quantitative evaluation method for network parameters of shale gas reservoir fracturing fractures, which is provided in the embodiments of the present specification: firstly, analyzing seepage environments of two different stages, namely a flow-back stage and a production stage, and determining to obtain two different fracture network parameters, namely a first fracture network parameter and a second fracture network parameter, based on the seepage environments of the two different stages; in addition, when the seepage environment characteristics of the flowback stage are specifically considered and analyzed, different flowing stages in the flowback stage can be distinguished, and the water-gas two-phase dynamic flowing characteristics of the different flowing stages are analyzed to obtain a first fracture network parameter with high accuracy; when the seepage environment characteristics in the production stage are specifically considered to be analyzed, a dimensionless bottom hole pressure local solution of the discrete fracture network in the target area in the matrix linear flow stage can be calculated, then a linear analysis function of the matrix linear flow stage in the discrete fracture network with a simple structure and a good effect can be constructed and obtained by using the local solution, and then a second fracture network parameter with high accuracy can be efficiently determined and obtained according to the linear analysis function; and finally, comprehensively utilizing the first crack network parameter and the second crack network parameter to obtain a target crack parameter of the discrete crack network with higher precision and meeting the precision requirement. Therefore, the technical problems of large error and low precision of the determined fracture network parameters in the existing method can be effectively solved.

In some embodiments, the obtaining of the production data of the flowback stage and the production data of the production stage of the target area may include the following steps: acquiring production data of a flowback stage by acquiring a daily measured value, a daily gas production rate and a daily water production rate of the bottom hole pressure of a target area in the flowback stage; and acquiring the daily measured value, the daily gas production rate and the daily water production rate of the bottom hole pressure of the target area in the production stage to obtain the production data of the production stage.

In this embodiment, in a specific implementation, the time parameter may be a daily measurement value of the acquired bottom hole pressure, a daily gas production rate, and an acquisition date corresponding to the daily water production rate.

In some embodiments, the performing of the preset normalization process by using the production data in the flow-back stage may include:

and respectively carrying out preset normalization processing on the time parameter and the pressure parameter of the flow-back stage by using the production data of the flow-back stage according to the following formula:

wherein X is a normalized time parameter (mu)_gc^* _mt)_iIs the product of the gas viscosity at the initial pressure and the integrated compression factor, mu_gIs the viscosity of the gas at the initial pressure, c^* _mtIs a comprehensive compression factor, q, considering the adsorption and desorption of the shale gas under the initial pressure_gThe amount of the generated gas is the daily gas amount,

is flatThe product of the gas viscosity at the bottom hole pressure and the integrated compressibility factor,

to be the gas viscosity at the average bottom hole pressure,

is the integrated compressibility factor at average bottom hole pressure, t is time; y is the normalized pressure parameter, p_iAs initial pressure, p_wFor daily measurements of the bottom hole pressure, m () represents the corresponding pseudo pressure of the gas, in particular, m (p)_i) Denotes the pseudo-pressure of the gas, m (p), corresponding to the initial pressure_w) Representing the pseudo pressure of the gas corresponding to the daily measurement of the bottom hole pressure.

In this embodiment, the normalization processing for presetting the time parameter by the above equation is to consider that there is a time difference between production rates for a plurality of wells, and if only the date recorded directly is used as the time parameter for analysis, the accuracy is easily lost. Therefore, the preset normalization processing can be used for introducing the material balance time and carrying out the preset normalization processing on the time parameter, so that the normalized time parameter with better effect and higher accuracy is obtained.

The daily value of the bottom hole pressure is normalized by the formula, so that the pressure parameters can be unified to a standard, and the normalized pressure parameters more suitable for subsequent processing can be obtained.

In some embodiments, in practice, the same formula and manner as described above may also be used for the production phase to perform the preset normalization process on the time parameter and the pressure parameter of the production phase by using the production data of the production phase. Therefore, the description is not repeated.

In some embodiments, the determining a first fracture network parameter according to the production data normalized at the flowback stage may include the following steps:

s1: determining the water-gas two-phase dynamic flow characteristics of each flow stage in a plurality of flow stages contained in the flow-back stage according to the normalized production data of the flow-back stage;

s2: and determining a first fracture network parameter according to the water-gas two-phase dynamic flow characteristics of each of the plurality of flow stages.

Through the embodiment, the flow-back stage can be divided into a plurality of different flow stages according to the production data after the normalization of the flow-back stage; respectively determining water-gas two-phase dynamic flow characteristics aiming at each flow stage in the plurality of flow stages; and then, based on the water-gas two-phase dynamic flow characteristics of each flow stage, explaining to determine a first fracture network parameter with relatively high accuracy determined based on the seepage environment characteristics of the flowback stage.

In some embodiments, the gas phase pressure and the water phase pressure may be distinguished based on normalized pressure parameters in the flowback stage normalized production data; then, combining the normalized time parameters based on the material balance, constructing a log-log graph about the pressure and the time; according to the log-log plot, the flow-back phase is divided into the following four flow phases: an aqueous phase first linear flow stage, an aqueous phase second linear flow stage, an aqueous phase boundary control flow stage, and a gas phase linear flow stage. In particular, as shown in fig. 2.

The first linear flow stage of the aqueous phase may specifically refer to that, at the beginning of flowback, the high permeability of the fracture causes the fracturing fluid in the fracture to flow into the wellbore along the fracture first, and a linear flow is represented in the fracture. In this case, the flow occurs only in the fracture, the fluid in the matrix is hardly used and only the fracturing fluid is supplied to the production well. Referring to fig. 2, the flow phase is represented on a typical curve in the figure as a straight line segment of slope 1/2.

The second linear flow phase of the aqueous phase may specifically mean that the fluid in the matrix continuously flows into the fracture along with the flow-back, the gas saturation in the fracture is continuously increased, the aqueous phase and the gas phase are main mobile phases in the fracture, and the first linear flow of the aqueous phase is interrupted. After a short transition flow, a second linear flow occurs. Referring to fig. 2, the flow phase is represented on a typical curve in the figure as a straight line segment of another slope 1/2.

The water phase boundary control flow stage specifically means that most of fracturing fluid in the fracture is discharged after the water phase second linear flow is finished, the yield of the fracturing fluid is low, and the gas phase is a main mobile phase in the fracture. The flowing stage is the final flowing stage of the flow-back process and indicates that the flow-back process of the fracturing fluid is about to finish. Referring to fig. 2, the flow phase is represented on a typical curve in the figure as a straight line segment with a slope of 1.

The gas phase linear flow phase may specifically mean that the flow phase is almost the same as the water phase boundary control flow in time, and is the first flow phase of the shale gas reservoir production phase. At this time, the gas in the matrix flows toward the fracture in a direction perpendicular to the fracture surface. Referring to fig. 2, the flow phase is represented on a typical curve in the figure as a straight line segment of slope 1/2.

Further, the analysis and determination of the water-gas two-phase dynamic flow characteristics may be performed for each of the above-described flow phases. As can be seen in particular in fig. 3.

And then according to the water-gas two-phase dynamic flow characteristics of each flow stage in the multiple flow stages, interpreting the discrete fracture seepage parameters of the target area so as to more accurately determine the first fracture network parameters based on the seepage environmental characteristics of the flowback stage.

In some embodiments, the above-mentioned constructing a linear analysis function of the matrix linear flow stage in the target region discrete fracture network according to the production data normalized by the production stage may include the following steps:

s1: calculating a dimensionless bottom hole pressure local solution of the discrete fracture network of the target area in the matrix linear flow stage according to the normalized production data of the production stage;

s2: and constructing a linear analysis function of the matrix linear flow stage under the target area discrete fracture network according to the dimensionless bottom hole pressure local solution of the target area discrete fracture network in the matrix linear flow stage.

In some embodiments, constructing a straight line analysis function of the linear flow phase of the matrix under the target area discrete fracture network comprises:

constructing a linear analysis function of a matrix linear flow stage under a target area discrete fracture network according to the following formula:

Y＝mX+b

wherein the content of the first and second substances,

wherein X is a normalized time parameter, Y is a normalized pressure parameter, m is a preset slope term, b is a preset intercept term, h is the reservoir thickness of the target area, T is the temperature, phi_mIs the formation porosity, L, of the target zone_hfLength of horizontal well volume fracture for target zone, w_hfWidth, k, of horizontal well volume fracture for target zone_mIs the permeability, k, of the formation in the target zone_hfPermeability of horizontal well volume fracturing fracture for target zone (mu)_gc^* _mt)_iIs the product of the gas viscosity at the initial pressure and the integrated compression factor.

In some embodiments, in specific implementation, the discrete fracture seepage parameters of the target area may be interpreted according to the production data normalized in the production stage and by combining the above-mentioned linear analysis function, so as to more accurately and efficiently determine the second fracture network parameters based on the seepage environment characteristics in the production stage.

In some embodiments, the determining a target fracture parameter of a discrete fracture network in a target area according to the production data normalized at the flowback stage, the production data normalized at the production stage, the first fracture network parameter, and the second fracture network parameter may include the following steps: and fitting the daily gas production rate by using the first crack network parameter, the second crack network parameter, the normalized production data in the flowback stage and the normalized production data in the production stage and adjusting the half length and the permeability of the crack so as to obtain the target crack parameter of the target area discrete crack network which meets the precision requirement.

Wherein the target fracture parameters may include at least: the total length and permeability of the target area discrete fracture network, etc.

In this embodiment, in specific implementation, the bottom-hole flow pressure determined based on the normalized pressure parameter may be used as a constraint, the first fracture network parameter and the second fracture network parameter are used as initial values of target fracture parameters to be determined, the production data after normalization in the flowback stage and the production data after normalization in the production stage are used, and the daily gas production rate and the accumulated gas production rate are dynamically fitted by adjusting the half length of the fracture and the permeability of the fracture for multiple times until a difference value between the fitted daily gas production rate and the accumulated gas production rate and the acquired actual daily gas production rate and the accumulated gas production rate is less than or equal to a preset difference threshold value. And determining the total length and the permeability of the corresponding discrete fracture network based on the half-length and the permeability of the fracture at the moment, and taking the total length and the permeability of the discrete fracture network as target fracture network parameters meeting the precision requirement. The preset difference threshold may be a minimum value.

Through the embodiment, the first network fracture parameter based on the seepage environment characteristic of the flowback stage and the second network fracture parameter based on the seepage environment characteristic of the production stage can be comprehensively utilized at the same time, and the target fracture network parameter with smaller error and higher precision is determined.

In some embodiments, after the target fracture parameters of the target area discrete fracture network are determined, oil and gas development of the target area can be guided according to the target fracture parameters of the target area discrete fracture network; and quantitatively evaluating the shale gas reservoir pressure fracture network in the target area according to the target fracture parameters of the discrete fracture network in the target area.

As can be seen from the above, based on the quantitative evaluation method for the shale gas reservoir fracturing fracture network parameters provided in the embodiments of the present specification, the preset normalization processing may be performed on the acquired production data of the flowback stage and the production data of the production stage of the target region to obtain the normalized production data of the flowback stage and the normalized production data of the production stage; determining a first fracture network parameter based on the flow characteristics according to the production data normalized in the flow-back stage; according to the production data after the production stage normalization, a linear analysis function of a matrix linear flow stage under a target area discrete fracture network is constructed; determining a second fracture network parameter according to the function; and then the first fracture network parameter and the second fracture network parameter can be comprehensively utilized, and the target fracture parameter of the discrete fracture network in the target area can be accurately determined by combining the normalized production data in the flowback stage and the normalized production data in the production stage, so that the determination error is effectively reduced, and the fracture network parameter with higher precision in a complex production scene is obtained.

In a specific scenario example, the quantitative evaluation method for the fracture network parameters of the shale gas reservoir provided by the embodiments of the present disclosure may be applied to implement quantitative evaluation of the fracture network based on flowback and production oil-water two-phase yield dynamic analysis (i.e., determining the target fracture parameters of the discrete fracture network in the target region). The following can be referred to as a specific implementation process.

In the scenario example, a characteristic segment of a log-log curve analysis curve of normalized pressure and time is drawn through normalization processing of time, a parameter expression of a characteristic straight-line segment is further obtained through establishment of an inner region-based steady-state local solution, actual production data is used for modifying the half length of a crack and the permeability of the crack to perform parameter fitting, and finally an interpretation value of the parameter is obtained. The specific implementation may include the following steps.

S1: acquiring and normalizing gas-water two-phase yield data of the flow-back stage and the production stage (for example, respectively performing preset normalization processing on the production data of the flow-back stage and the production data of the production stage).

In this step, the flow characteristics are usually studied by using a log-log curve, on which the conventional production time is obviously not used for the variable of shale gas reservoir time X, and the substance balance time is required to be introduced as the variable X when normalization is performed.

S2: and (3) oil-water flow characteristics and analysis in the flow-back stage (for example, determining a first fracture network parameter according to the production data normalized in the flow-back stage).

In this step, based on the fact that the S1 has the time variable X and the pressure variable Y, a processing manner of a log-log curve is adopted, and different characteristic segments on the curve can be interpreted as 4 flow stages of the shale gas reservoir flowback process, and then are processed respectively.

S3: and (3) a production stage gas-water flow linear analysis method (for example, a linear analysis function of a matrix linear flow stage under a target area discrete fracture network is constructed according to the production data normalized by the production stage, and a second fracture network parameter is determined according to the linear analysis function).

In this step, the straight line segment in the log-log curve obtained in step S2 may be subjected to a local solution to interpret the characteristic parameters, so as to construct a straight line formula and determine the fracture parameters. The key here is how to build the local solution.

S4: and (3) a seam network parameter interpretation technology for dynamically combining the flowback and production full-yield data (for example, determining a target crack parameter of a target area discrete crack network according to the production data after the flowback stage normalization, the production data after the production stage normalization, the first crack network parameter and the second crack network parameter).

In this step, historical fitting daily output and accumulated output can be performed by adjusting the half-length of the fracture and the permeability of the fracture based on the local solution and the related parameters obtained in step S3, and characteristic parameters, namely, the half-length of the fracture and the permeability of the fracture (i.e., target fracture parameters of the discrete fracture network in the target region) can be obtained after the historical fitting.

In specific implementation, for step S1, the purpose of normalizing the gas-water two-phase production data in the flowback and production phases is to simulate the production well in actual conditions.

Specifically, when performing yield dynamic analysis, a log-log curve of time and pressure needs to be drawn, and in the log-log curve of time and pressure, the pressure and time may be normalized first. The straight line segment expression in the curve can be expressed in the form:

Y＝mX+b

in the above equation, Y is a normalization process of the pressure (e.g., a normalized time parameter), X is a normalization process of the time (e.g., a normalized pressure parameter), m is a slope (e.g., a pending preset slope term), and b is an intercept (e.g., a pending preset intercept term).

In practice, production wells are usually produced with variable production or variable bottom hole flow pressure, no transformation is used for the Y variable, and the introduction of material balance time is usually required for the X variable with respect to time. Because there is a time difference between the production rates for multiple wells, the accuracy is lost by evaluating only the production time.

Specifically, for example, for a shale gas reservoir, the material equilibrium time t may be considered in consideration of compressibility and adsorption/desorption of shale gas_cCan be defined as:

wherein q is_gIs the daily gas production, m³/d；

For considering the comprehensive compression factor of shale gas adsorption and desorption, MPa^-1；

Is the product of gas viscosity and overall compressibility at average pressure within the range, mPas.MPa^-1。

Specifically, the variable parameters in the above straight line segment can be referred to table 1.

TABLE 1 shale gas reservoir Linear analysis method variable table

For step S2, a simulation calculation may be performed using the flowback mathematical model, and the flow characteristics may be further analyzed. In particular, as shown in fig. 2.

In fig. 2, a log-log plot of gas phase normalized pseudo-pressure and water phase normalized pressure versus time to mass equilibrium is shown. Referring to fig. 2, it can be seen that the shale gas reservoir flowback process mainly has four flow stages: (1) an aqueous phase first linear flow stage, (2) an aqueous phase second linear flow stage, (3) an aqueous phase boundary control flow stage, and (4) a gas phase linear flow stage. The flow characteristics of each stage are described below.

(1) Aqueous phase first linear flow stage: at the very beginning of flowback, the high permeability of the fracture causes the fracturing fluid within the fracture to flow into the wellbore first along the fracture, exhibiting a linear flow within the fracture. In this case, the flow occurs only in the fracture, the fluid in the matrix is hardly used and only the fracturing fluid is supplied to the production well. This flow phase is represented on the typical curve shown in fig. 2 as a straight line segment of slope 1/2.

(2) Aqueous phase second linear flow stage: along with the flowing back, the fluid in the matrix continuously flows into the crack, the gas saturation in the crack is continuously increased, the water phase and the gas phase are main mobile phases in the crack, and the first linear flow of the water phase is interrupted. After a short transition flow, a second linear flow occurs, which flow phase appears as a straight line segment of another slope 1/2 on the typical curve shown in fig. 2.

(3) Water phase boundary control flow phase: after the second linear flow of the water phase is finished, most of fracturing fluid in the fracture is discharged, the yield of the fracturing fluid is low, and the gas phase is a main mobile phase in the fracture. This flow phase is the last flow phase of the flowback process, which is indicative of the near-end of the flowback process of the fracturing fluid, and is represented by the straight line segment with slope 1 on the typical curve shown in fig. 2.

(4) Gas phase linear flow stage: the flow phase takes place at approximately the same time as the water phase boundary control flow, and is the first flow phase of the shale gas reservoir production phase. At this point, the gas within the matrix flows toward the fracture in a direction perpendicular to the fracture plane, and appears as a straight line segment of slope 1/2 on the typical curve shown in FIG. 2.

Further, a description of the various flow stages and a summary and explanation of the schematic may be found in reference to fig. 3. Because the shale gas reservoir flowback shows gas-water two-phase flow just before, the local solution derivation of the gas-water two-phase flow is difficult at present, and the shale gas reservoir flowback dynamic characteristics can be analyzed by using a history fitting method, so that discrete fracture seepage parameters can be explained.

Specifically, for example, shale gas reservoir, for actual variable production or variable bottom hole flow pressure production, the material balance time t is usually adopted_cInstead of the actual time, one can get:

where Δ p represents the pressure difference between the formation initial pressure and the bottom hole flow pressure, C_ItRepresenting the comprehensive compressibility of the crack development zone, N_wIndicating the initial water content in the fracture system, B_oDenotes the volume factor, q_oDenotes the daily yield, K_IDenotes the equivalent permeability, r, of the fracture development zone_eDenotes the equivalent radius of the crack development zone, r_wRepresenting the horizontal wellbore radius, S_hfNegative skin indicating crack initiation, S_AIndicating non-circular generation of the epidermis in the fissure development zone.

Further, it is possible to provide:

the material equilibrium time can be defined by the formula (t)_c＝Q_o/q_o) And substituting the equation into the formula, and finishing to obtain:

the equation is a linear analysis formula for interpreting fracture key parameters based on an inner region quasi-steady state flow, which can be further simplified to be written as follows:

Y＝mX+b。

the relevant variable parameters related to the linear analysis formula can be specifically referred to table 2.

TABLE 2 variables for pseudo-steady state linear analysis in tight and shale gas reservoirs

Wherein the content of the first and second substances,

and Z^*The specific method can be the method which takes the substance balance time, the comprehensive compression coefficient and the compression factor after the shale gas adsorption and desorption into consideration.

For step 3, an inner-region-based quasi-steady-state local solution may be established, and the specific steps may include:

based on the relevant theory, the method has the following advantages: the flow in the fracture is stabilized in the stratum linear flow stage of the double-wing symmetrical fracture, and the fracture is equivalent to the action of a negative epidermis.

Further, a dimensionless bottom hole pressure expression of the double-wing symmetric fracture in a linear flow stage of the stratum is given based on the characteristics:

in the formula, S_hfNegative skin for crack generation, t_DDimensionless time. Wherein S is_hfThe expression of (c) can be expressed as:

in the formula, c_hfDThe crack has no dimensional flow conductivity.

Substituting the above formula into a discrete fracture network, taking a shale gas reservoir as an example, can obtain:

further, a reference length L is introduced_RThe above formula can be rewritten as:

based on the dimensionless pressure, dimensionless time, and dimensionless fracture conductivity definitions, the above equation can be written as:

where the equation is a dimensionless local solution of the bottom hole pressure of a discrete fracture network at the linear flow phase of the matrix, the local solution is very similar to that of a symmetric biplane fracture, except that the dimensionless time term and the fracture skin term are more than constant terms, which is due to the difference in reference lengths in the dimensionless definition.

Transforming the above formula into a causal form, and further sorting to obtain:

it can be seen that the bottom hole pressure is linear with the square root of time, and if the basic physical parameters of the reservoir are defined, the total length and permeability of the discrete fracture network can be obtained by explaining the inversion of the production data of the matrix linear flow stage. The above equation can be further simplified to be written as the following equation:

Y＝mX+b。

the equation is a straight line analysis equation for explaining the key seepage parameters of the fracture by using the matrix linear flow.

For step S4, the fracture parameters may be interpreted using a history fitting method after the flow phase is specified.

Specifically, because the production well is not provided with a crack monitoring measure, the daily gas production rate can be fitted by adjusting the half length of the crack and the permeability of the crack by assuming that the discrete crack is a double-wing symmetric crack and taking the bottom hole flowing pressure as constraint. The basic parameters involved can be seen in table 3.

TABLE 3 shale gas reservoir flowback example analysis basic parameter Table

The involved coupling solution method is as follows:

H·q_scfo+p_hfo＝p_i-h

wherein H represents a coupling solving matrix, H represents a solving variable composed of the flow of the fracture unit and the bottom hole flowing pressure, and q represents_scfoRepresenting the flow of the formation to each fracture unit, p_hfoThe pressure of each fracture cell is shown.

In the formula, the matrix H can be specifically represented as:

the vector h may specifically be represented as:

wherein the values of n and m are 1 and 1.5.

Referring to fig. 4, fitting results of two flowback processes are respectively given. After the history fitting is finished, the flow-back process is predicted for 120 days at the bottom hole pressure of 4 MPa. As can be seen from the graph, the goodness of fit of the measured data and the simulated data is high, and meanwhile, the daily yield and the cumulative yield trend are accurately captured by the prediction result. The half length of the crack obtained by history fitting is 66m, the total length of the crack is 1584m, and the permeability of the crack is 589 multiplied by 10^-3μm²The parameter values are basically reasonable. And then the half-length of the fracture and the permeability of the fracture determined after fitting can be used as final fracture network parameters.

Through the scene example, it is verified that the quantitative evaluation method for the shale gas reservoir fracturing fracture network parameters provided by the embodiment of the specification can simulate matrix flow by using linear flow, and a seepage mathematical model and a semi-analytic solution of a discrete fracture network fracturing fluid flowback stage are established through coupling fracture multiphase flow; and the multiphase flow characteristics of the whole flowback process of the compact oil reservoir and the shale gas reservoir are respectively determined, and a linear analysis method for explaining the total length and the permeability of a discrete fracture network by using flowback dynamic data is provided to determine fracture network parameters. The seepage mathematical model and the fracture parameter interpretation method have important theoretical significance on production prediction, flowback prediction, volume fracturing effect evaluation and volume fracturing network parameter interpretation of the tight oil reservoir and the shale gas reservoir.

Embodiments of the present specification further provide a server, including a processor and a memory for storing processor-executable instructions, where the processor, when implemented, may perform the following steps according to the instructions: acquiring production data of a flowback stage and production data of a production stage of a target area; respectively performing preset normalization processing on the production data of the flowback stage and the production data of the production stage to obtain normalized production data of the flowback stage and normalized production data of the production stage; determining a first fracture network parameter according to the normalized production data of the flowback stage; according to the production data normalized in the production stage, a linear analysis function of a matrix linear flow stage in a discrete fracture network in a target area is constructed; determining a second fracture network parameter according to the straight line analysis function; and determining a target crack parameter of the discrete crack network in the target area according to the production data after the normalization of the flowback stage, the production data after the normalization of the production stage, the first crack network parameter and the second crack network parameter.

In order to more accurately complete the above instructions, referring to fig. 5, another specific server is provided in the embodiments of the present specification, wherein the server includes a network communication port 501, a processor 502 and a memory 503, and the above structures are connected by an internal cable, so that the structures can perform specific data interaction.

The network communication port 501 may be specifically configured to acquire production data of a flowback stage and production data of a production stage of a target area.

The processor 502 may be specifically configured to perform preset normalization processing on the production data of the flowback stage and the production data of the production stage respectively to obtain normalized production data of the flowback stage and normalized production data of the production stage; determining a first fracture network parameter according to the normalized production data of the flowback stage; according to the production data normalized in the production stage, a linear analysis function of a matrix linear flow stage in a discrete fracture network in a target area is constructed; determining a second fracture network parameter according to the straight line analysis function; and determining a target crack parameter of the discrete crack network in the target area according to the production data after the normalization of the flowback stage, the production data after the normalization of the production stage, the first crack network parameter and the second crack network parameter.

The memory 503 may be specifically configured to store a corresponding instruction program.

In this embodiment, the network communication port 501 may be a virtual port that is bound to different communication protocols, so that different data can be sent or received. For example, the network communication port may be a port responsible for web data communication, a port responsible for FTP data communication, or a port responsible for mail data communication. In addition, the network communication port can also be a communication interface or a communication chip of an entity. For example, it may be a wireless mobile network communication chip, such as GSM, CDMA, etc.; it can also be a Wifi chip; it may also be a bluetooth chip.

In this embodiment, the processor 502 may be implemented in any suitable manner. For example, the processor may take the form of, for example, a microprocessor or processor and a computer-readable medium that stores computer-readable program code (e.g., software or firmware) executable by the (micro) processor, logic gates, switches, an Application Specific Integrated Circuit (ASIC), a programmable logic controller, an embedded microcontroller, and so forth. The description is not intended to be limiting.

In this embodiment, the memory 503 may include multiple layers, and in a digital system, the memory may be any memory as long as binary data can be stored; in an integrated circuit, a circuit without a physical form and with a storage function is also called a memory, such as a RAM, a FIFO and the like; in the system, the storage device in physical form is also called a memory, such as a memory bank.

The present specification further provides a computer-readable storage medium based on the quantitative evaluation method for the fracture network parameters of the shale gas reservoir, where the computer-readable storage medium stores computer program instructions, and when the computer program instructions are executed, the computer program instructions implement: acquiring production data of a flowback stage and production data of a production stage of a target area; respectively performing preset normalization processing on the production data of the flowback stage and the production data of the production stage to obtain normalized production data of the flowback stage and normalized production data of the production stage; determining a first fracture network parameter according to the normalized production data of the flowback stage; according to the production data normalized in the production stage, a linear analysis function of a matrix linear flow stage in a discrete fracture network in a target area is constructed; determining a second fracture network parameter according to the straight line analysis function; and determining a target crack parameter of the discrete crack network in the target area according to the production data after the normalization of the flowback stage, the production data after the normalization of the production stage, the first crack network parameter and the second crack network parameter.

In this embodiment, the storage medium includes, but is not limited to, a Random Access Memory (RAM), a Read-Only Memory (ROM), a Cache (Cache), a Hard Disk Drive (HDD), or a Memory Card (Memory Card). The memory may be used to store computer program instructions. The network communication unit may be an interface for performing network connection communication, which is set in accordance with a standard prescribed by a communication protocol.

In this embodiment, the functions and effects specifically realized by the program instructions stored in the computer-readable storage medium can be explained in comparison with other embodiments, and are not described herein again.

On the aspect of software, the embodiment of the present specification further provides a quantitative evaluation device for shale gas reservoir fracturing fracture network parameters, and the device may specifically include the following structural modules:

the acquisition module is specifically used for acquiring production data of a flowback stage and production data of a production stage of the target area;

the normalization module is specifically configured to perform preset normalization processing on the production data of the flowback stage and the production data of the production stage respectively to obtain normalized production data of the flowback stage and normalized production data of the production stage;

the first determining module is specifically configured to determine a first fracture network parameter according to the production data normalized at the flowback stage;

the second determining module is specifically used for constructing a linear analysis function of the matrix linear flow stage in the discrete fracture network of the target area according to the production data normalized by the production stage; determining a second fracture network parameter according to the straight line analysis function;

the third determining module may be specifically configured to determine a target fracture parameter of the target area discrete fracture network according to the production data after the flowback stage normalization, the production data after the production stage normalization, the first fracture network parameter, and the second fracture network parameter.

It should be noted that, the units, devices, modules, etc. illustrated in the above embodiments may be implemented by a computer chip or an entity, or implemented by a product with certain functions. For convenience of description, the above devices are described as being divided into various modules by functions, and are described separately. It is to be understood that, in implementing the present specification, functions of each module may be implemented in one or more pieces of software and/or hardware, or a module that implements the same function may be implemented by a combination of a plurality of sub-modules or sub-units, or the like. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of some interfaces, devices or units, and may be an electric or other form.

As can be seen from the above, based on the quantitative evaluation device for shale gas reservoir fracturing fracture network parameters provided in the embodiments of the present specification, the preset normalization processing may be performed on the acquired production data of the flowback stage and the production data of the production stage of the target region to obtain the normalized production data of the flowback stage and the normalized production data of the production stage; determining a first fracture network parameter based on the flow characteristics according to the production data normalized in the flow-back stage; according to the production data after the production stage normalization, a linear analysis function of a matrix linear flow stage under a target area discrete fracture network is constructed; determining a second fracture network parameter according to the function; and then the first fracture network parameters and the second fracture network parameters can be comprehensively utilized, and the target fracture parameters of the discrete fracture network in the target area can be accurately determined by combining the normalized production data in the flowback stage and the normalized production data in the production stage, so that the determination error is reduced.

Although the present specification provides method steps as described in the examples or flowcharts, additional or fewer steps may be included based on conventional or non-inventive means. The order of steps recited in the embodiments is merely one manner of performing the steps in a multitude of orders and does not represent the only order of execution. When an apparatus or client product in practice executes, it may execute sequentially or in parallel (e.g., in a parallel processor or multithreaded processing environment, or even in a distributed data processing environment) according to the embodiments or methods shown in the figures. The terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, the presence of additional identical or equivalent elements in a process, method, article, or apparatus that comprises the recited elements is not excluded. The terms first, second, etc. are used to denote names, but not any particular order.

Those skilled in the art will also appreciate that, in addition to implementing the controller as pure computer readable program code, the same functionality can be implemented by logically programming method steps such that the controller is in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers and the like. Such a controller may therefore be considered as a hardware component, and the means included therein for performing the various functions may also be considered as a structure within the hardware component. Or even means for performing the functions may be regarded as being both a software module for performing the method and a structure within a hardware component.

This description may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, classes, etc. that perform particular tasks or implement particular abstract data types. The specification may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer-readable storage media including memory storage devices.

From the above description of the embodiments, it is clear to those skilled in the art that the present specification can be implemented by software plus necessary general hardware platform. With this understanding, the technical solutions in the present specification may be essentially embodied in the form of a software product, which may be stored in a storage medium, such as a ROM/RAM, a magnetic disk, an optical disk, etc., and includes several instructions for enabling a computer device (which may be a personal computer, a mobile terminal, a server, or a network device, etc.) to execute the methods described in the embodiments or some parts of the embodiments in the present specification.

The embodiments in the present specification are described in a progressive manner, and the same or similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. The description is operational with numerous general purpose or special purpose computing system environments or configurations. For example: personal computers, server computers, hand-held or portable devices, tablet-type devices, multiprocessor systems, microprocessor-based systems, set top boxes, programmable electronic devices, network PCs, minicomputers, mainframe computers, distributed computing environments that include any of the above systems or devices, and the like.

While the specification has been described with examples, those skilled in the art will appreciate that there are numerous variations and permutations of the specification that do not depart from the spirit of the specification, and it is intended that the appended claims include such variations and modifications that do not depart from the spirit of the specification.

Claims (10)

1. A quantitative evaluation method for shale gas reservoir fracturing fracture network parameters is characterized by comprising the following steps:

acquiring production data of a flowback stage and production data of a production stage of a target area;

respectively performing preset normalization processing by using the production data of the flowback stage and the production data of the production stage to obtain the normalized production data of the flowback stage and the normalized production data of the production stage;

determining a first fracture network parameter according to the normalized production data of the flowback stage;

according to the production data normalized in the production stage, a linear analysis function of a matrix linear flow stage in a discrete fracture network in a target area is constructed; determining a second fracture network parameter according to the straight line analysis function;

and determining a target crack parameter of the discrete crack network in the target area according to the production data after the normalization of the flowback stage, the production data after the normalization of the production stage, the first crack network parameter and the second crack network parameter.

2. The method of claim 1, wherein the target region comprises a shale gas reservoir region.

3. The method of claim 2, wherein obtaining production data for the flowback stage and production data for the production stage of the target area comprises:

acquiring production data of a flowback stage by acquiring a daily measured value, a daily gas production rate and a daily water production rate of the bottom hole pressure of a target area in the flowback stage;

and acquiring the daily measured value, the daily gas production rate and the daily water production rate of the bottom hole pressure of the target area in the production stage to obtain the production data of the production stage.

4. The method of claim 3, wherein the pre-normalization using the production data of the flow-back stage comprises:

and respectively carrying out preset normalization processing on the time parameter and the pressure parameter of the flow-back stage by using the production data of the flow-back stage according to the following formula:

wherein X is a normalized time parameter (mu)_gc^* _mt)_iIs the product of the gas viscosity at the initial pressure and the integrated compression factor, mu_gIs the viscosity of the gas at the initial pressure，c^* _mtIs a comprehensive compression factor, q, considering the adsorption and desorption of the shale gas under the initial pressure_gThe amount of the generated gas is the daily gas amount,

is the product of the gas viscosity at the average bottom hole pressure and the integrated compressibility factor, t is time; y is the normalized pressure parameter, p_iAs initial pressure, p_wM () represents the corresponding pseudo pressure of the gas as a daily measurement of the bottom hole pressure.

5. The method of claim 3, wherein determining a first fracture network parameter from the normalized production data of the flowback stage comprises:

determining the water-gas two-phase dynamic flow characteristics of each flow stage in a plurality of flow stages contained in the flow-back stage according to the normalized production data of the flow-back stage;

and determining a first fracture network parameter according to the water-gas two-phase dynamic flow characteristics of each of the plurality of flow stages.

6. The method of claim 3, wherein constructing a linear analysis function of the linear flow phase of the matrix under the target area discrete fracture network according to the normalized production data of the production phase comprises:

calculating a dimensionless bottom hole pressure local solution of the discrete fracture network of the target area in the matrix linear flow stage according to the normalized production data of the production stage;

and constructing a linear analysis function of the matrix linear flow stage under the target area discrete fracture network according to the dimensionless bottom hole pressure local solution of the target area discrete fracture network in the matrix linear flow stage.

7. The method of claim 6, wherein constructing a straight line analysis function of the linear flow phase of the matrix under the target area discrete fracture network comprises:

constructing a linear analysis function of a matrix linear flow stage under a target area discrete fracture network according to the following formula:

Y＝mX+b

wherein the content of the first and second substances,

wherein X is a normalized time parameter, Y is a normalized pressure parameter, m is a preset slope term, b is a preset intercept term, h is the reservoir thickness of the target area, T is the temperature, phi_mIs the formation porosity, L, of the target zone_hfLength of horizontal well volume fracture for target zone, w_hfWidth, k, of horizontal well volume fracture for target zone_mIs the permeability, k, of the formation in the target zone_hfPermeability of horizontal well volume fracturing fracture for target zone (mu)_gc^* _mt)_iIs the product of the gas viscosity at the initial pressure and the integrated compression factor.

8. The method of claim 3, wherein determining the target fracture parameters of the target area discrete fracture network from the production data normalized at the flowback stage, the production data normalized at the production stage, the first fracture network parameters, and the second fracture network parameters comprises:

and fitting the daily gas production rate by using the first crack network parameter, the second crack network parameter, the normalized production data in the flowback stage and the normalized production data in the production stage and adjusting the half length and the permeability of the crack so as to obtain the target crack parameter of the target area discrete crack network which meets the precision requirement.

9. The utility model provides a quantitative evaluation device of shale gas reservoir fracturing fracture network parameter which characterized in that includes:

the acquisition module is used for acquiring the production data of the flowback stage and the production data of the production stage of the target area;

the normalization module is used for respectively carrying out preset normalization processing on the production data of the flowback stage and the production data of the production stage to obtain the normalized production data of the flowback stage and the normalized production data of the production stage;

the first determining module is used for determining a first fracture network parameter according to the production data normalized in the flowback stage;

the second determining module is used for constructing a linear analysis function of the matrix linear flow stage under the discrete fracture network of the target area according to the production data normalized by the production stage; determining a second fracture network parameter according to the straight line analysis function;

and the third determining module is used for determining the target crack parameters of the target area discrete crack network according to the normalized production data of the flowback stage, the normalized production data of the production stage, the first crack network parameters and the second crack network parameters.

10. A computer-readable storage medium having stored thereon computer instructions which, when executed, implement the steps of the method of any one of claims 1 to 8.

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