Fracturing pumping stop pressure drop data inversion evaluation method based on wavelet transform

Abstract

The invention discloses a wavelet transform-based fracturing pump stop pressure drop data inversion evaluation method, which comprises the following steps of: performing de-noising processing on fracturing pump stop pressure drop data signals through a wavelet transform method, eliminating oscillation signals generated by a water hammer effect, and obtaining filtered field pressure drop data; establishing a shaft fracture seepage model and a shaft fluid flow model based on the multi-section horizontal well fracturing physical model, realizing connection between the models through a coefficient matrix coupling method, and establishing a multi-section fracturing horizontal well flowback mathematical model; calculating wellhead simulation pressure drop data according to the on-site construction fracturing data, the physical property parameters and the crack parameters, and fitting the wellhead simulation pressure drop data with the filtered on-site pressure drop data; based on the filtered field pressure drop data and the simulated pressure drop data, a double logarithmic pressure and derivative fitting chart is obtained, and then the fracture parameters and the formation filtration condition after formation pressure are obtained from the chart, so that the fracturing effect is evaluated in real time, and the purpose of improving the productivity is achieved.

Description

Technical Field

[0001] The invention relates to the field of automation technology and oil and gas production engineering, and more specifically to an inversion evaluation method for pump-off pressure drop data of fracturing based on wavelet transformation. Background Art

[0002] During the hydraulic fracturing construction and mining process, fracturing fluid is injected into the formation to expand the cracks and achieve the imbibition replacement effect, thereby achieving the purpose of increasing production capacity. However, when the pump is stopped during fracturing, a water hammer effect will occur, resulting in interference signals in the collected wellhead field pressure drop data, which cannot reflect the actual fracturing seepage conditions, thus causing a certain impact on the later fracturing effect evaluation.

[0003] Therefore, it is necessary to perform wavelet transform denoising on the collected pressure drop data, select the appropriate threshold value to process the wavelet decomposition coefficient required by the data, and achieve the filtering effect. The filtered field pressure drop data and the simulated pressure drop data are fitted, and the double logarithmic derivative chart is drawn to evaluate the fracturing effect and fracture network parameters.

[0004] During the fracturing process, the fracturing fluid is injected into the formation for a period of time and then the well is shut down and the pump is stopped. At this time, the injection volume at the wellhead suddenly drops to 0. The fluid at the wellhead flows due to inertia, resulting in a decrease in density and pressure. This change propagates to the bottom of the wellbore in the form of a rarefaction wave. When the pressure wave reaches the fracture, the fluid in the wellbore is lower in density than the fluid in the fracture. The fluid in the fracture enters the wellbore due to the pressure difference, resulting in an increase in the density of the fluid in the wellbore and an increase in pressure. This change propagates to the wellhead in the form of a compression wave. When it reaches the wellhead, wall emission occurs, and the fluid pressure rises again. This change propagates to the bottom of the well in the form of a compression wave. When the signal reaches the fracture, because the fluid density in the wellbore is higher than the fluid in the fracture, under the action of pressure, the fluid in the wellbore enters the fracture, resulting in a decrease in the pressure in the wellbore at the fracture. This change propagates to the wellhead in the form of a tensile wave. When the tensile wave signal reaches the wellhead, the entire pump-stopping water hammer wave completes a cycle of propagation. In this cycle, the pressure change is a large fluctuation when the pump is stopped, but the trend will gradually slow down and become flat. This phenomenon is called the water hammer effect.

[0005] Wavelet transform overcomes the defects of Fourier transform in time domain and frequency domain localization, has advantages in non-stationary and complex signal processing, and realizes multi-resolution analysis function. Especially for complex signals, wavelet transform can better amplify signal details, allowing us to analyze and process signals. Summary of the invention

[0006] In order to solve the above-mentioned defects in the evaluation of pump-off pressure drop data, the present invention proposes an inversion evaluation method for fracturing pump-off pressure drop data based on wavelet transform, the purpose of which is to eliminate the oscillation noise signal through the wavelet transform method, retain the wellhead field pressure drop data signal, solve the simulated pressure drop data based on the multi-stage horizontal well fracturing seepage model, perform data fitting, draw a double logarithmic derivative chart to evaluate important parameters such as formation permeability, fracture half-length, and skin coefficient.

[0007] The present invention provides a method for inversion evaluation of fracturing pump stop pressure drop data based on wavelet transform, which specifically comprises the following steps:

[0008] Step 1: De-noise the fracturing pump stop pressure drop data signal by wavelet transform method to eliminate the oscillation signal caused by water hammer effect and obtain filtered field pressure drop data;

[0009] Step 2: Based on the multi-stage horizontal well fracturing physical model, a wellbore fracture seepage model and a wellbore fluid flow model are established. The connection between the models is achieved through the coefficient matrix coupling method, and a multi-stage horizontal well flowback mathematical model is established;

[0010] Step 3: Calculate the wellhead simulated pressure drop data according to the field construction fracturing data, physical property parameters and fracture parameters, and fit it with the filtered field pressure drop data;

[0011] Step 4: Based on the filtered field pressure drop data and simulated pressure drop data, a double logarithmic pressure and derivative fitting chart is obtained, and then the post-fracturing fracture parameters and formation filtration conditions of the formation are obtained from the chart, so as to evaluate the fracturing effect in real time.

[0012] In the above steps, step 1 comprises:

[0013] Step 1.1: Based on the principle of wavelet transform method, the objective function is expanded in a specific digital form so that the objective function is transformed in the frequency domain. A discrete time series x n The continuous wavelet transform of (t) is:

[0014] In formula (1), WT(s, t) is the result of wavelet transform calculation; * is the complex conjugate root; s is the resolution scale; t is time; n′ is the time shift; Δt is the sampling interval; Ψ is the mother wavelet; Ψ0 is the dimensionless result; n is the time quantity; x n is a discrete time series; N is the signal length;

[0015] Step 1.2: Since formula (1) requires a lot of calculation, it can be converted into the calculation of x by using convolution theory. n (t) and Ψ * Inverse transform of the Fourier transform product:

[0016]

[0017] In formula (11):

[0018]

[0019] The inverse transform of the continuous wavelet transform is obtained as:

[0020]

[0021] In formula (2): x nA (t) is x n (t) analytical signal; C δ is the reconstruction coefficient; W δ (s) is the result of each scale of the mother wavelet; R e is the real part of the complex number; s j is the scale number; j is the scale variable; δ is the threshold.

[0022] In the above steps, step 2 includes: establishing a wellbore fracture seepage model based on a multi-stage horizontal well fracturing physical model, and solving the pressure, specifically including:

[0023] Step 2.1: Establish computational models such as fracture equivalent model and wellbore fluid flow model for multi-stage fracturing horizontal wells in unconventional reservoirs;

[0024] Step 2.2: Provide a calculation and solution method for the model, achieve effective connection between models through coupling methods, and realize calculation simulation of pressure during fracturing flowback.

[0025] In the above steps, step 2.1 specifically includes:

[0026] Step 2.1.1: Establish a physical model of a horizontal hydraulic fracturing well with a horizontal well located in the center of the formation and multiple fractures intersecting vertically with it, based on the following physical model assumptions:

[0027] (1) Seepage in horizontal, uniform, isotropic formations;

[0028] (2) Seepage of a single-phase uniform weakly compressible fluid in a formation;

[0029] (3) All cracks in the rock mass are vertical cracks;

[0030] (4) The effects of gravity and capillary forces on rock mechanical properties are ignored;

[0031] (5) The movement of fluids obeys Darcy's law;

[0032] (6) The calculation does not take into account the temperature effect.

[0033] Step 2.1.2: In the field of seepage mechanics, the change in the point potential studied at any point can be regarded as the superposition of the fields formed by all sources and sinks in the region at this point. On this basis, the formation with a complex fracture network is discretized and the fields formed after the discretization are superimposed to obtain the seepage field and pressure distribution of the entire region. For some closed layers with a square shape, the source function method shows significant superiority in dealing with such problems. The pressure distribution in the flow field can be solved by the point source function method. For the non-steady-state seepage problem of single-phase weakly compressible liquid, the basic equation is:

[0034]

[0035] The partial differential equation for fluid flow in a fracture can be expressed as:

[0036]

[0037] Transformed into:

[0038] Since the fluid in each unit, the flow of fluid at both ends will cause a change in pressure, so the pressure expression at any point in the unit can be obtained.

[0039]

[0040] Where: t is time, s; C t is the comprehensive compression coefficient; p fD is the free flow pressure in the crack; q fD is the dimensionless flow from the formation to each point source; C fD Therefore, there is no flow conductivity; t D is dimensionless time; x D is the distance from the discrete point in the crack; u is the Laplace variable

[0041] Step 2.1.3: Using the discrete form of the fracture network, the coordinates of the fracture center are used as parameters to discretize the fracture grid, thereby obtaining a simplified seepage equation. In a uniform and isotropic medium, according to the law of conservation of mass, the non-steady-state seepage continuity equation of a compressible weakly compressible fluid can be expressed as:

[0042]

[0043] The continuity equation, momentum equation and state equation are sorted out. This differential equation is applicable to unsteady seepage and single-phase weakly compressible fluid:

[0044]

[0045] Find:

[0046]

[0047] When considering the wellbore storage coefficient and skin factor in Laplace space, the bottom hole pressure can be expressed as:

[0048]

[0049] Step 2.1.4: The treatment of reservoir fractures in horizontal wells still uses fracture-formation coupling, fracture discrete unit coupling and fracture-to-fracture coupling methods. The difference is that due to the relatively long length of the horizontal well, it is necessary to consider the pressure drop loss in the wellbore. The pressure drop of the horizontal well is mainly manifested as: acceleration pressure drop loss; friction loss; fluid directional pressure drop; gravity pressure drop. The artificial fractures pressed out in the horizontal well section are divided into N small sections. The fluid flow rate of fracture F1 into the wellbore is The fluid flow rate out of the wellbore from fracture F2 is The pressure loss can be expressed as:

[0050]

[0051] In the above steps, step 2.2 specifically includes:

[0052] In the process of horizontal well mining, in addition to the pressure loss caused by formation seepage, there is also pressure loss in the horizontal section. This method involves three aspects: formation seepage, fracture internal seepage and downhole fluid.

[0053] First, in the initial state, the pressure loss between two adjacent wellbore nodes is set to 0; then, by assembling and transforming, the value is brought into the matrix to obtain the numerical solution of the liquid flow rate qi of each wellbore node. Using formulas (8) to (10) to calculate the formula, the pressure difference ΔP is obtained. i ' is located between the wellbore nodes, and the calculation results are compared with the initial values ​​to check whether the error meets the calculation accuracy requirements. If the error meets the requirements, the next step of calculation is performed; if it does not meet the requirements, the calculation results are adjusted according to the relevant weight coefficients, and then the calculation is recalculated until the accuracy requirements are met. Among them, through the gray correlation method, the weight coefficient needs to be set according to the actual field parameters. Mainly including geological parameters, reservoir physical parameters, fracture parameters and working condition parameters.

[0054] When the error precision reaches the specified value, the current time step is judged again. If yes, the operation is terminated; otherwise, the result that meets the precision requirement is used as the new initial value, and this process is repeated until the calculation is completed. This method can better complete the numerical calculation of fluid dynamics and obtain accurate results.

[0055] In the above steps, step 3 specifically includes:

[0056] Step 3.1: Preprocess the data according to the on-site metering report. First, draw a scatter plot to analyze the trend of the pump stop pressure drop data, including the filtered on-site pressure drop data, liquid volume, nozzle size, etc.

[0057] Among them, the scatter plot of filtered field pressure drop data is drawn to analyze the pressure change trend during the entire fracturing flowback process. For obvious pressure fluctuations, the field working conditions are preliminarily evaluated in combination with the field fracturing construction plan.

[0058] Effect of nozzle size and liquid volume: When simulating pressure calculations using the flowback mathematical model we established, the first step of time division is based on the nozzle size change time. When the nozzle size is the same, the second step of time division is based on the obvious change point of the liquid volume.

[0059] Step 3.2: According to the on-site hydraulic fracturing engineering design, the geological overview of the surrounding blocks of the fracturing well, well logging results, formation fluid properties, well segmentation and clustering, perforation parameters; and related physical parameters, including: permeability, porosity, reservoir thickness, volume coefficient, skin factor, fracture half-length, fracture coordinate parameters, and the simulated bottom hole pressure is obtained based on the physical parameters;

[0060] Step 3.3: Draw a fitting diagram of the filtered field pressure drop data and the simulated pressure drop data. The specific steps are as follows:

[0061] (1) Calculate the original formation pressure and liquid column pressure based on the well depth and pressure coefficient;

[0062] (2) Divide the stages according to the change of nozzle size and displacement, with a step length of 3 hours. Because the displacement statistics on site are once every 1 hour, the time point is too long, so we set a step length of 3 hours when calculating the simulated pressure drop data;

[0063] (3) Substitute the calculated bottom hole casing pressure and subtract the liquid column pressure to obtain the simulated pressure drop data;

[0064] (4) Fitting the filtered field pressure drop data with the simulated pressure drop data, and continuously adjusting the parameters to make them fit accurately. The adjustment parameters generally include adjusting the skin factor, crack half-length, number of cracks, crack conductivity and other parameters. The specific adjustment method should be based on the filtered field pressure drop data. If the calculated simulated pressure drop data is larger than the filtered field pressure drop data, we need to adjust the parameters to reduce the simulated pressure drop data value so that it fits the filtered field pressure drop data, and vice versa.

[0065] In the above steps, step 4 specifically includes: drawing a double logarithmic derivative chart based on the filtered field pressure drop data and simulated pressure drop data obtained in step 3, interpreting and evaluating important parameters such as formation permeability, fracture half-length, and skin factor. By comparing with the field data, the fracturing effect is evaluated in real time.

[0066] The present invention has the following advantages:

[0067] (1) The pump stop pressure drop data is denoised by wavelet transform, and the corrected pressure obtained is highly consistent with the actual field pressure data;

[0068] (2) Combined with the discretization method of semi-analytical equivalent fractures, a fracture equivalent model was established; based on the oil and gas seepage law, a variable production prediction method under complex fracture distribution conditions was formed; and a dynamic parameter calculation method for each flow stage was established.

[0069] (3) By analyzing the production dynamics of multi-stage horizontal wells, based on the principle of pressure superposition, a bottom hole pressure prediction method under variable flow conditions is established to analyze the flow characteristics.

[0070] (4) Through the measured pressure drop data and the simulated pressure drop data, a double logarithmic derivative chart is established to invert important parameters such as formation permeability, fracture half-length, and skin coefficient, which is used for subsequent real-time adjustment and

[0071] It provides a strong basis for the evaluation of fracturing effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0072] In order to more clearly illustrate the technical solutions in the embodiments of this article or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of this article. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0073] Figure 1 It is a general flow chart of a method for inversion evaluation of pump-off pressure drop data of fracturing based on wavelet transform according to an embodiment of the present invention;

[0074] Figure 2 The figure shows the physical model of fracture distribution of multi-stage horizontal well fracturing in an embodiment of the present invention;

[0075] Figure 3 The figure shows a schematic diagram of horizontal wellbore discreteness in an embodiment of the present invention;

[0076] Figure 4 Shown is a schematic diagram of a horizontal wellbore coefficient matrix in an embodiment of the present invention;

[0077] Figure 5The figure is a flow chart of the coefficient matrix calculation process in an embodiment of the present invention;

[0078] Figure 6 The figure shows a schematic diagram of double logarithms of pressure and pressure derivative before and after wavelet transformation in an embodiment of the present invention;

[0079] Figure 7 Shown is a double logarithmic derivative interpretation chart of a multi-stage fractured horizontal well in an embodiment of the present invention. DETAILED DESCRIPTION

[0080] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0081] This specification provides method operation steps as described in the embodiments or flow charts, but more or fewer operation steps may be included based on routine or non-creative work. The order of steps listed in the embodiments is only one way of executing the order of many steps and does not represent the only execution order. When the system or device product is executed in practice, it can be executed in the order of the method shown in the embodiments or the drawings or in parallel.

[0082] It should be noted that the present invention is a wavelet transform-based inversion method for fracturing pump-off pressure drop data, which can be used in the field of oil and gas engineering to evaluate fracturing effects based on pump-off pressure drop data. It can also be used for other problems such as pressure drop data fitting and fracture network evaluation in fracturing fracture seepage models.

[0083] The present invention provides a method for inversion and evaluation of fracturing pump-off pressure drop data based on wavelet transform, which can realize wavelet transform of pump-off pressure drop data to eliminate noise signals, perform bottom hole flow pressure fitting based on a multi-stage fracturing horizontal well fracture model, and draw a double logarithmic derivative chart to interpret and evaluate important parameters such as formation permeability, fracture half-length, skin coefficient, etc., so as to adjust the fracturing process in real time and achieve the purpose of improving production capacity.

[0084] like Figure 1 The figure shows a general flow chart of a method for inversion evaluation of pump-off pressure drop data of fracturing based on wavelet transform according to an embodiment of the present invention, which specifically includes the following steps:

[0085] Step 101: Based on the principle of wavelet transform method, the objective function is expanded in a specific digital form so that the objective function is transformed in the frequency domain. A discrete time series x n The continuous wavelet transform of (t) is:

[0086] In formula (1), WT(s, t) is the result of wavelet transform calculation; * is the complex conjugate root; s is the resolution scale, m; t is time; n′ is the time shift; Δt is the sampling interval, s; Ψ is the mother wavelet; Ψ0 is the dimensionless result.

[0087] The factor (1) has a large amount of calculation, which can be converted into the calculation of x through convolution theory. n (t) and Ψ * Inverse transform of the Fourier transform product:

[0088]

[0089] In formula (11):

[0090]

[0091] The inverse transform of the continuous wavelet transform is obtained as:

[0092]

[0093] In formula (2): x nA (t) is x n (t) analytical signal; C δ is the reconstruction coefficient; W δ (s) is the result of each scale of mother wavelet; R e is the real part of the complex number; s j is the scale number; j is the scale variable; δ is the threshold.

[0094] Step 102 includes: establishing a wellbore fracture seepage model based on a multi-stage horizontal well fracturing physical model, and solving the pressure, specifically including: establishing computational models such as an equivalent model of a multi-stage horizontal well fracture in an unconventional reservoir and a wellbore fluid flow model; providing a computational solution method for the model, achieving effective connection between models through a coupling method, and realizing computational simulation of pressure during fracturing flowback.

[0095] A physical model of a horizontal hydraulic fracturing well with a horizontal well located in the center of the formation and multiple fractures intersecting vertically with it is established based on the following physical model assumptions:

[0096] (1) Seepage in horizontal, uniform, isotropic formations;

[0097] (2) Seepage of a single-phase uniform weakly compressible fluid in a formation;

[0098] (3) All cracks in the rock mass are vertical cracks;

[0099] (4) The effects of gravity and capillary forces on rock mechanical properties are ignored;

[0100] (5) The movement of fluids obeys Darcy's law;

[0101] (6) The calculation does not take into account the temperature effect.

[0102] Step 103 includes: discretizing the formation with a complex fracture network and superimposing the fields formed after the discretization to obtain the seepage field and pressure distribution of the entire region. The pressure distribution in the flow field can be solved by the point source function method. For the unsteady seepage problem of single-phase weakly compressible liquid, the basic equation is:

[0103]

[0104] The partial differential equation for fluid flow in a fracture can be expressed as:

[0105]

[0106] Transformed into:

[0107] Since the fluid in each unit, the flow of fluid at both ends will cause a change in pressure, so the pressure expression at any point in the unit can be obtained.

[0108]

[0109] In the above formula: φ: is the porosity; is the instantaneous injection volume in the formation at a certain moment; p s is the source function expression; C η is the dimensionless diffusion coefficient; is the average flow pressure in the fracture; is the average flow rate of each point source in the formation; t is time, s; C t is the comprehensive compression coefficient; p fD is the free flow pressure in the crack; q fD is the dimensionless flow from the formation to each point source; C fD Therefore, there is no flow conductivity; t D is dimensionless time; x D is the distance from the discrete point in the crack; u is the Laplace variable.

[0110] Step 104 includes: using the discrete form of the fracture network, taking the coordinates of the fracture center as parameters, discretizing the fracture grid, thereby obtaining a simplified seepage equation. In a uniform and isotropic medium, according to the law of conservation of mass, the non-steady-state seepage continuity equation of a compressible weakly compressible fluid can be expressed as:

[0111]

[0112] The continuity equation, momentum equation and state equation are sorted out. This differential equation is applicable to unsteady seepage and single-phase weakly compressible fluid:

[0113]

[0114] Find:

[0115]

[0116] When considering the wellbore storage coefficient and skin factor in Laplace space, the bottom hole pressure can be expressed as:

[0117]

[0118] Step 105 includes: the treatment of reservoir fractures in horizontal wells still adopts fracture-formation coupling, fracture discrete unit coupling and fracture-fracture coupling methods. The pressure drop of horizontal wells is mainly manifested as: accelerated pressure drop loss; friction loss; fluid directional pressure drop; gravity pressure drop. The artificial fractures pressed out in the horizontal well section are divided into N small sections. The fluid flow rate of fracture F1 into the wellbore is The fluid flow rate out of the wellbore from fracture F2 is The pressure loss can be expressed as:

[0119]

[0120] Step 106 includes: During the production process of the horizontal well, in addition to the pressure loss caused by formation seepage, there is also pressure loss in the horizontal section. This method involves three aspects: formation seepage, fracture internal seepage and downhole fluid.

[0121] First, in the initial state, the pressure loss between two adjacent wellbore nodes is set to 0; then, by assembling and transforming, the value is brought into the matrix to obtain the numerical solution of the liquid flow rate qi of each wellbore node. Using the calculation formulas (8) to (10), the pressure difference ΔP is obtained. i ' is located between the wellbore nodes, and the calculation result is compared with the initial value to check whether the error meets the calculation accuracy requirements. If the error meets the requirements, the next step of calculation is performed; if it does not meet the requirements, the calculation result is adjusted according to the relevant weight coefficients, and then the calculation is recalculated until the accuracy requirements are met. When the error accuracy reaches the specified value, the current time step is judged again. If it is, the operation is terminated; otherwise, the result that meets the accuracy requirements is used as the new initial value, and this is repeated until the calculation is completed. This method can better complete the numerical calculation of fluid dynamics and obtain accurate results.

[0122] Step 107 includes: pre-processing data according to the on-site metering report, first drawing a scatter plot, analyzing the trend of the pump-off pressure drop data, including the wellhead on-site pressure drop data, liquid volume, nozzle size, etc.; according to the on-site hydraulic fracturing engineering design, obtaining the basic situation of the fracturing well, including the geological overview, oil well conditions, well logging diagrams and formation fluid conditions, and physical parameters such as permeability, porosity, reservoir thickness, volume coefficient, and skin factor; obtaining fracturing fracture data, including horizontal well segmentation and clustering and perforation parameter data, fracture half-length, main fracture height, fracture width, fracture coordinates, and other fracture parameters. Input the physical parameters, fracture parameters, and other data into the Iuput file to calculate the simulated bottom hole pressure;

[0123] Step 108 includes: drawing a fitted pressure drop data curve graph, the specific steps are as follows:

[0124] (1) Calculate the original formation pressure and liquid column pressure based on the well depth and pressure coefficient;

[0125] (2) Divide the stages according to the change of nozzle size and displacement, with a step length of 3 hours;

[0126] (3) Substitute the calculated bottom hole casing pressure and subtract the liquid column pressure to obtain the simulated pressure drop data;

[0127] (4) Fit the filtered field pressure drop data with the simulated pressure drop data, and continuously adjust the parameters to ensure accurate fit.

[0128] Step 109 includes: drawing a double logarithmic derivative chart based on the simulated pressure drop data and the actual wellhead pressure drop data obtained in step 3, interpreting and evaluating important parameters such as formation permeability, fracture half-length, and skin factor, and evaluating the fracturing effect in real time by comparing with the field data.

[0129] Figure 2 The figure shows the physical model of fracture distribution of multi-stage horizontal well fracturing in the embodiment of the present invention. The model is established based on the following physical model assumptions:

[0130] (1) Seepage in horizontal, uniform, isotropic formations;

[0131] (2) Seepage of a single-phase uniform weakly compressible fluid in a formation;

[0132] (3) All cracks in the rock mass are vertical cracks;

[0133] (4) The effects of gravity and capillary forces on rock mechanical properties are ignored;

[0134] (5) The movement of fluids obeys Darcy's law;

[0135] (6) The calculation does not take into account the temperature effect.

[0136] Figure 3 The figure shows a schematic diagram of the horizontal wellbore discretization in an embodiment of the present invention. Taking the fracture network as the research object, the fracture network is discretized using the coordinates of the fracture center as parameters to discretize the fracture grid, thereby obtaining a simplified seepage equation. The fracture discretization technology can effectively reduce the difficulty of solving the equation and enhance its applicability in complex fracture network structures. It includes the following steps:

[0137] Step 301 includes: by discretizing a single crack into small segments, a crack is processed into N segments, and each segment can be regarded as a line source. As the number of small units increases, the accuracy of the calculation results increases, but the resources required for calculation also increase accordingly. The flow at the boundaries of the two ends of the unit is and The flow rate of the formation into the fracture is At the same time, the conductivity of each unit is set in the coefficient matrix to achieve accurate simulation of the seepage process. To find the pressure at any point in the fracture discrete element, the two units Ω i With Ω i+1 The pressure formulas at the common interface are tabulated.

[0138]

[0139] The pressure equation at the intersection of all crack discrete elements is obtained as follows:

[0140]

[0141] Step 302 includes: for the case of multiple cracks crossing, each crack is discretized separately, coupled at each node, and the characteristics of their crossing are utilized. The discretization method of irregular cracks: First, we convert these cracks into a regular crack according to a certain arc. The formula that each crack unit connected to it bears the same pressure is:

[0142]

[0143] Step 303 includes: the artificial fractures formed in the horizontal well section can be divided into N small sections. The fluid flow rate of the fracture F1 into the wellbore is The fluid flow rate out of the wellbore from fracture F2 is Due to traffic and After entering the wellbore, the velocity drop caused by the change in flow rate and the resistance loss caused by the friction between the fluid inside the wellbore and the wellbore will lead to pressure loss in the horizontal well. Due to the change in kinetic energy, the pressure drop speed is accelerated. This phenomenon only occurs at the intersection of the fracture and the wellbore. The pressure loss can be expressed as:

[0144]

[0145] Figure 4 The figure shows a schematic diagram of the coefficient matrix of the horizontal wellbore in an embodiment of the present invention. The coefficient matrix of the horizontal wellbore has certain similarities in form with the coefficient matrix of the vertical fracturing well, but there are significant differences between them. Horizontal wellbores are usually longer, and this feature leads to obvious pressure loss in the wellbore. In the process of horizontal wellbore fracturing, the pressure drop Δpi between the fracture points is a key parameter. The number of these equations is equal to the number of fracturing sections in the horizontal wellbore, which reflects the complex coupling relationship between fractures and formations, and between fractures in the process of horizontal wellbore fracturing. As shown in the cross in the figure. This block indicates that there are as many equations as there are horizontal well sections divided into as many sections. The coupling between the systems is realized to achieve the purpose of dynamically calculating the flow parameters.

[0146] Figure 5 The figure shows a flow chart of the coefficient matrix calculation process in an embodiment of the present invention. In the process of mining a horizontal well, in addition to the pressure loss caused by formation seepage, there is also pressure loss in the horizontal section. This method involves three aspects: formation seepage, internal seepage in the fracture, and downhole fluid.

[0147] First, in the initial state, the pressure loss between two adjacent wellbore nodes is set to 0; the goal of this step is to ensure that the system is convenient for subsequent calculations and analysis under given initial conditions. Next, the values ​​are brought into the matrix through assembly and transformation. Through this set of processes, the numerical solution of the liquid flow rate qi of each wellbore node is obtained. Subsequently, the pressure difference ΔP is obtained using the calculation formula i ' is located between the wellbore nodes, and the calculation result is compared with the initial value to check whether the error meets the calculation accuracy requirements. If the error meets the requirements, the next step of calculation is performed; if it does not meet the requirements, the calculation result is adjusted according to the relevant weight coefficients, and then the calculation is recalculated until the accuracy requirements are met. When the error accuracy reaches the specified value, the current time step is judged again. If it is, the operation is terminated; otherwise, the result that meets the accuracy requirements is used as the new initial value, and this is repeated until the calculation is completed. This method can better complete the numerical calculation of fluid dynamics and obtain accurate results.

[0148] Figure 6The diagram shows the double logarithm of pressure and pressure derivative before and after wavelet transformation in the embodiment of the present invention. Before wavelet transformation, the fluctuation of the first 20% area of ​​the double logarithm of pressure and pressure derivative is obvious, and there is no rule to understand, which makes it impossible to conduct effective analysis. The original pressure at the wellhead is processed by wavelet transformation to eliminate the influence of water hammer effect, and a new pressure logarithm is obtained. The water hammer effect in the first half is eliminated, showing a straight line distribution with a slope of 1, indicating that the processed pressure curve can fit the actual pressure well before stopping the pump, in the pressure drop section, the pressure fluctuation section and the pressure flat section.

[0149] Figure 7 The double logarithmic derivative interpretation chart of multi-stage fracturing horizontal wells in the embodiment of the present invention is shown. According to the characteristics of the double logarithmic chart, the fracture model of the multi-stage fracturing horizontal well is selected for well test analysis, and the physical parameters such as fracture parameters, formation permeability, fracture half-length, skin coefficient and formation filtration of unconventional reservoirs after fracturing are analyzed, which are basically consistent with the well test analysis results.

Claims

1. A method for inversion evaluation of fracturing pump stop pressure drop data based on wavelet transform, characterized in that: The following steps are involved: Step 1: De-noise the fracturing pump stop pressure drop data signal by wavelet transform method to eliminate the oscillation signal caused by water hammer effect and obtain the filtered field pressure drop data Step 2: Based on the multi-stage horizontal well fracturing physical model, a wellbore fracture seepage model and a wellbore fluid flow model are established. The connection between the models is achieved through the coefficient matrix coupling method, and a multi-stage horizontal well flowback mathematical model is established; Step 3: Calculate the wellhead simulated pressure drop data according to the field construction fracturing data and physical property parameters, and fit it with the filtered field pressure drop data; Step 4: Based on the filtered field pressure drop data and simulated pressure drop data, a double logarithmic pressure and derivative fitting chart is obtained, and then the post-fracturing fracture parameters and formation filtration conditions are obtained from the chart to evaluate the fracturing effect in real time.

2. The method for inversion and evaluation of fracturing pump stop pressure drop data based on wavelet transform according to claim 1, characterized in that: The step 1 comprises: Step 1.1: Based on the principle of wavelet transform method, the objective function is expanded digitally so that the objective function is transformed in the frequency domain. A discrete time series x n The continuous wavelet transform of (t) is: In formula (1), WT(s, t) is the result of wavelet transform calculation; * is the complex conjugate root; s is the resolution scale; t is time; n′ is the time shift; Δt is the sampling interval; Ψ is the mother wavelet; Ψ0 is the dimensionless result; n is the time quantity; x n is a discrete time series; N is the signal length; Step 1.2: Formula (1) can be converted into the inverse Fourier transform through convolution theory, and the inverse transform of the continuous wavelet transform is obtained as: In formula (2): x nA (t) is x n (t) analytical signal; C δ is the reconstruction coefficient; W δ (s) is the result of each scale of mother wavelet; R e is the real part of the complex number; s j is the scale number; j is the scale variable; δ is the threshold.

3. The method for inversion evaluation of fracturing pump stop pressure drop data based on wavelet transform according to claim 1, characterized in that: The step 2 includes: establishing a wellbore fracture seepage model based on a multi-stage horizontal well fracturing physical model, and solving the pressure, specifically including: Step 2.1: Establish an equivalent fracture model and a wellbore fluid flow model for multi-stage fracturing horizontal wells in unconventional reservoirs; Step 2.2: Use coupling methods to achieve effective connection between models and realize calculation simulation of pressure during fracturing flowback.

4. The method for inversion evaluation of fracturing pump stop pressure drop data based on wavelet transform according to claim 3, characterized in that: The step 2.1 also includes: Step 2.1.1: Establish a physical model of a horizontal well located in the center of the formation and multiple horizontal hydraulic fracturing wells with fractures vertically intersecting the horizontal well, based on the following physical model assumptions: (1) Seepage in horizontal, uniform, isotropic formations; (2) Seepage of a single-phase uniform weakly compressible fluid in a formation; (3) All cracks in the rock mass are vertical cracks; (4) The effects of gravity and capillary forces on rock mechanical properties are ignored; (5) The movement of fluids obeys Darcy's law; (6) Calculations that do not take temperature effects into account; Step 2.1.2: By discretizing the model in step 2.1.1 and superimposing the fields formed after the discretization, the seepage field and pressure distribution of the whole area are obtained; For the unsteady seepage problem of single-phase uniform weakly compressible fluid, the basic equation is: The partial differential equation for the flow of fluid in the fracture is expressed as: Transformed into: In formulas (3), (4) and (5): φ: porosity; is the instantaneous injection volume in the formation at a certain moment; p s is the source function expression; C η is the dimensionless diffusion coefficient; is the average flow pressure in the fracture; is the average flow rate of each point source in the formation; t is time, s; C t is the comprehensive compression coefficient; p fD is the free flow pressure in the crack; q fD is the dimensionless flow from the formation to each point source; C fD Therefore, there is no flow conductivity; t D is dimensionless time; x D is the distance from the discrete point in the crack; u is the Laplace variable; Step 2.1.3: In homogeneous media, according to the law of conservation of mass, the non-steady-state permeability continuity equation of a weakly compressible fluid can be expressed as: The continuity equation, momentum equation and state equation are sorted out. This differential equation is applicable to single-phase weakly compressible fluid under unsteady seepage: In formulas (6) and (7), η is defined as the pressure conductivity; p is the pressure; ρ is the fluid density; v x 、v y 、v z is the seepage velocity in the three-dimensional coordinate direction; x, y, z are the three-dimensional coordinate directions; Step 2.1.4: The treatment of reservoir fractures in horizontal wells still adopts the fracture-formation coupling, fracture discrete unit coupling and fracture-inter-fracture coupling methods. The artificial fractures squeezed out of the horizontal well section are divided into N small sections, indicating that the fluid flow rate of fracture F1 into the wellbore is q N1 , indicating that the fluid flow rate out of the wellbore from fracture F2 is q N2 , the pressure loss can be expressed as: In formulas (8), (9), and (10), r w is the distance from a point in the formation to the center of the well; v h is the flow velocity of the fluid in the wellbore; q w is the flow rate from a certain point in the formation to the center of the well; p wi 、p wi-1 are the pressures before and after the intersection of the fracture and the wellbore; B is the volume coefficient of the formation fluid; q w i, q w i -1 They are the flow rates before and after the intersection of the fracture and the wellbore, respectively.

5. The method for inversion and evaluation of fracturing pump stop pressure drop data based on wavelet transform according to claim 3, characterized in that: The step 2.2 specifically includes: In the initial state, the pressure loss between two adjacent wellbore nodes is set to 0; next, by assembling and transforming, the pressure value is brought into the matrix to obtain the numerical solution of the liquid flow rate qi of each wellbore node; Using formula (8), formula (9) and formula (10), we can get the pressure difference ΔP i ' is located between the wellbore nodes, and the calculation results are compared with the initial values ​​to check whether the error meets the requirements of calculation accuracy; If the error meets the requirement, proceed to the next step of calculation; If the requirements are not met, the calculation results are adjusted according to the relevant weight coefficients, and then the calculation is performed again until the accuracy requirements are met; When the error accuracy reaches the specified value, the current time step is judged again. If yes, the operation is terminated; otherwise, the result that meets the accuracy requirements is used as the new initial value; this process is repeated until the calculation is completed.

6. The method for inversion and evaluation of fracturing pump stop pressure drop data based on wavelet transform according to claim 1, characterized in that: The step 3 specifically includes: Step 3.1: Preprocess the data according to the on-site metering report, draw a scatter plot, and analyze the pump stop pressure drop data trend through the filtered on-site pressure drop data, liquid volume, and nozzle size; The purpose of drawing a scatter plot of the filtered field pressure drop data is to analyze the pressure change trend during the entire fracturing flowback process. For obvious pressure fluctuations, the field conditions are preliminarily evaluated in combination with the field fracturing construction plan. Effect of nozzle size and liquid volume: When simulating pressure calculation through the established flowback mathematical model, the first step of time division is based on the nozzle size change time. When the nozzle size is the same, the second step of time division is based on the obvious change point of liquid volume. Step 3.2: According to the on-site hydraulic fracturing engineering design, the geological overview, well logging results, formation fluid properties, well segmentation and clustering, and perforation parameters of the surrounding blocks of the fracturing well are obtained; And related physical parameters, including: permeability, porosity, reservoir thickness, volume coefficient, skin factor, fracture half-length, fracture coordinate parameters; The simulated bottom hole pressure is obtained according to the physical property parameters; Step 3.3: Draw a fitting diagram of the filtered field pressure drop data and the simulated pressure drop data. The specific steps are as follows: (1) Calculate the original formation pressure and liquid column pressure based on the well depth and pressure coefficient; (2) Divide the stages according to the change of nozzle size and displacement, with 3h as one step; (3) Substitute the calculated bottom hole casing pressure and subtract the liquid column pressure to obtain the simulated pressure drop data; (4) Fit the filtered field pressure drop data with the simulated pressure drop data, and continuously adjust the parameters to make them fit accurately.

7. The method for inversion and evaluation of fracturing pump-off pressure drop data based on wavelet transform according to claim 1, characterized in that: The step 4 specifically includes: drawing a double logarithmic derivative chart based on the filtered field pressure drop data and simulated pressure drop data obtained in step 3, interpreting and evaluating the formation permeability, fracture half-length, and skin coefficient, and evaluating the fracturing effect in real time by comparing with the field data.

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