CN114048695B - Effective shale gas seam net volume inversion method based on flowback data - Google Patents

Abstract

The invention discloses an effective fracture network volume inversion method for shale gas based on flowback data. The steps are as follows: first, a mathematical model of gas-water two-phase flow in a tree-shaped fractal network is established; , considering the effects of shale gas reverse imbibition displacement, fracture network pressurization effect, fracture closure effect, and matrix gas intrusion, the flow material balance equation of the shale fracture system is derived; based on the adsorption and desorption effect combined with the channeling equation, the The flow material balance equation of the rock matrix system; finally, a shale gas fracturing fluid flowback model is established. Based on the flowback production data after shale gas well fracture network fracturing, combined with an efficient genetic algorithm, an effective fracture network suitable for shale gas is established. Genetic algorithm for volume inversion. The present invention forms an evaluation method for fracture network volume after shale gas pressure fracturing through the flowback data of shale gas fracturing fluid, and enriches and develops a post-evaluation technology system for shale gas pressure.

Description

An effective fracture network volume inversion method for shale gas based on flowback data

technical field

The invention relates to the technical field of stimulation and transformation of unconventional oil and gas, in particular to an effective fracture network volume inversion method for shale gas based on flowback data.

Background technique

In recent years, with the increasing consumption of conventional oil and gas resources, the development of oil and gas reservoirs has gradually become more difficult. Unconventional oil and gas resources such as shale gas occupy the main position of oil and gas production, and their development scale has continued to expand. Due to the poor physical properties and low permeability of shale reservoirs, it is necessary to use horizontal well fracture network fracturing technology to pump fracturing fluid accompanied by proppant and additives into tight shale reservoirs under high pressure to create fractures and increase seepage channels, thereby enabling achieve commercial development.

Whether the fracturing stimulation effect is sufficient is determined by the effective fracture network volume. At present, the post-fracture evaluation methods of shale gas wells are mainly based on microseismic monitoring and SRV dynamic numerical simulation. At present, microseismic monitoring is usually used in mines to evaluate fracture networks, but this method is expensive. In the SRV dynamic numerical simulation method, a large number of models are realized by multi-field coupled fracture propagation. Moreover, these evaluation methods may overestimate the effective fracture network volume (ESRV) of shale gas, and it is possible that the fracture network reconstruction volume (SRV) calculated by microseismic monitoring and numerical simulation is large enough, but the field test production is not consistent with that. matching situation. The main reason is that the microseismic monitoring technology and numerical simulation technology cannot effectively evaluate the degree of connectivity between fractures, and overestimate the isolated fractures that do not contribute to the production. less than its estimated value. The effective fracture network of shale gas is the main seepage channel for fracturing fluid flowback and shale gas production, which determines the level of fracturing fluid flowback rate, the gas production capacity of shale gas wells and the size of technically recoverable reserves. As the flow channel of fracturing fluid and shale gas, it means that the flowback production data of shale gas wells must carry the characteristic information of shale gas effective fracture network, and the accurate interpretation of flowback production data will inevitably obtain effective fractures. Important reservoir characteristic parameters such as network volume. In the past, shale gas fracturing fluid flowback data was mostly ignored. In the past decade, some scholars have begun to pay attention and try to explain the shale gas effective fracture network volume included in the fracturing fluid flowback and production data to evaluate the effect of fracture network fracturing. Due to the special two-phase seepage characteristics of shale gas, the evaluation of fracturing effect based on post-fracture flowback is still in its infancy. The existing flowback model does not take into account the reverse imbibition and displacement of fracturing fluid, the supercharging effect of the fracture network, the effect of shut-in in the middle, and the wrong estimation of the initial fracture pressure. Evaluation and prediction. In view of this, it is necessary to propose an effective fracture network volume inversion method for shale gas based on fracturing fluid flowback, which can quickly evaluate the fracturing effect of shale gas wells and accurately predict shale gas production.

SUMMARY OF THE INVENTION

The purpose of the present invention is to provide a method for inversion of the effective fracture network volume of shale gas based on flowback data, aiming at the problem that the existing technical methods cannot accurately predict the effective volume of the fracture network of shale gas wells.

The main steps of the volume inversion method for shale gas effective fracture network based on flowback data provided by the present invention are as follows:

S1: In order to characterize the fracture bifurcation characteristics in the process of shale gas fracturing, the fractal theory is applied to establish a tree-shaped fractal network gas-water two-phase flow equation that reflects the characteristics of the complex underground fracture network.

S2: Considering the effects of reverse imbibition and displacement of shale gas, pressurization effect of fracture network, fracture closure effect and matrix gas intrusion, establish the flow material balance equation of shale fracture system.

S3: Considering the adsorption and desorption effect of matrix gas, combined with the channeling equation, establish the flow material balance equation of the shale matrix system.

S4: Combine the shale gas tree-shaped fractal two-phase flow model with the flow material balance model of the fracture system and the flow material balance model of the matrix system to form a shale gas fracturing fluid flowback production model, and use the dichotomy method for the flowback The model is solved to obtain the average pressure of fracture network and matrix system, as well as fracturing fluid flowback and shale gas production under bottom hole pressure conditions at different times.

S5: Apply the established shale gas fracturing fluid flowback production model, based on the flowback production data after fracture network fracturing in shale gas wells, combined with an efficient genetic algorithm, to establish a genetic model suitable for shale gas effective fracture network volume inversion Algorithmic Workflow.

Each step is described in detail below:

In the step S1, the flow equation model of the tree-shaped fractal fracture is:

Due to the symmetry of the reservoir, only 1/2 of the single-cluster fracture network was taken for research. According to the Hagen-Poiseuille equation, the flow rate of the rectangular fracture at the k-th level of the tree fracture is:

where ΔP _k is the pressure difference of the k-th level horizontal fracture; μ is the fluid viscosity; l _k , W _fk and h _fk are the length, width and height of the k-th level branch fracture, respectively.

The length, width and height of the crack at the k-th level satisfy the following equations:

where l ₀ , W _f0 and h _f0 are the initial length, width and height of the tree fractal crack, respectively; R _L , R _W and _Rh are the ratio of the length, width and height of the crack, respectively.

From formula (1), it can be known that the viscous resistance of fluid flow in a single fracture is

According to the parallel and series principle of fluid pressure drop, the total viscous resistance of the network is calculated, and the total flow resistance of the tree fractal fracture network can be expressed as:

in

N _k =n ^k (6)

In the formula, n is the number of branches of fractal cracks, and n=2 in the present invention; m is the number of crack series, and k is the k-th level crack network.

Then the flow rate of the single-phase flow tree-shaped fractal fracture network is:

where ΔP is the total pressure difference of the tree-fractal fracture network, ΔP=P _f -P _wf .

As the flowback fluid is produced, the fracture pressure decreases, and the fracture will compress under the closing stress. At this time, it is assumed that its height and length remain unchanged, and it is assumed that a fracture with a width of W _fk in the k-th stage has a compressed width of W _fkc , then the volume change satisfies:

V _fk -V _fkc =C _f V _fk ΔP _f (8)

where C _f is the fracture compression coefficient; V _fk is the volume of the k-th grade single fracture under the original fracture pressure; V _fkc is the volume of the k-th grade single fracture under the current fracture pressure; ΔP _f is the pressure drop of the fracture system, ΔP _f =P _fi - P _f .

in

V _fk =W _fk h _fk l _k (9)

V _fkc = W _fkc h _fk l _k (10)

In the formula: W _fkc is the width of the k-th single fracture under the current fracture pressure.

Substitute formula (9) and formula (10) into formula (8) and get

W _fkc =(1-C _f ΔP _f )W _fk (11)

Considering the fracture closure effect, the flow rate of 1/2 single-cluster fracture network single-phase flow tree-shaped fractal fracture network is

in

W _f0c =(1-C _f ΔP _f )W _f0 (13)

For oil and gas two-phase flow, the relative permeability is considered in the single-phase flow tree-shaped fracture network flow model, and the flow rate calculation formula of 1/2 single-cluster tree-shaped fracture network gas/water two-phase flow is obtained:

Among them, P _f is the average pressure of the fracture network, which changes with the fluid production. P _f is the equation established by the flow material balance equation of the shale fracture system established in step S2 and the flow material balance equation of the shale matrix system established in step S3 P _wf is the bottom hole flow pressure of the horizontal wellbore, B _i is the fluid volume coefficient, i is the gas and water; K _ri ( S _w ) is the gas/water relative permeability in the tree-shaped fracture network, and the linear relative permeability model is adopted

K _rw = S _w (15)

K _rg = 1-S _w (16)

Among them, _Sw is the water saturation in the fracture.

Then, the superposition of gas and water production are respectively

Among them: N _f is the total number of clusters of staged fracturing in horizontal wells, which satisfies the following relationship

N _f =n _f ·n _CL (19)

where n _f is the number of fracturing stages; n _CL is the number of clusters per stage.

In step S2, the material balance equation of the shale fracture system is:

The tree-shaped fractal crack network volume is:

V _fi is an important parameter to preliminarily evaluate the fracturing effect of shale gas fracture network.

in

V ₀ =W _f0 h _f0 l ₀ (21)

The equivalent crack half-length of the tree-shaped fractal crack network is:

where θ is the bifurcation angle of the tree crack.

The shale reverse imbibition index I _imb is defined to describe the degree of reverse imbibition of the reservoir, which is the ratio of the free gas in the fracture network to the fracture volume, _0≤Iimb≤1 . The original conditions include:

S _gi =I _imb (23)

S _gi is the initial gas saturation in the fracture network.

The underground volume of free gas in the fracture is:

V _gfi =I _imb V _fi (24)

Then the volume of water in the fracture is:

V _wi =(1-I _imb )V _fi (25)

The fracture water saturation under initial conditions is:

During the flowback process, after a certain amount of fracturing fluid (W _p ) is flowed back from the fracture, the pressure of the fracture system drops from the original fracture pressure P _fi to the current fracture pressure P _f , and the fracture pressure drop is ΔP _f =P _fi -P _f . The reduction of fracture volume, the expansion of free gas volume and the entry of matrix gas into the fracture will reduce the volume of fracturing fluid.

(1) Reduction of fracture volume:

ΔV _f =V _fi C _f ΔP _f (27)

(2) Gas increment

The gas increment is the sum of the expansion of the fracture free gas and the intrusion of the matrix gas, minus the produced free gas.

1) The expansion of free gas in the fracture network is:

where B _gf and B _gfi are the free gas volume coefficients under the current fracture pressure and the original fracture pressure, respectively, m ³ /m ³ .

2) Invasion amount of matrix shale gas V _mf

Considering the compressibility of matrix pores and the desorption effect of shale matrix adsorbed gas, the ground volume of matrix shale gas channeling into the tree-shaped fractal network is obtained as:

In the formula, V _b is the ESRV volume, and there is a specific calculation formula later; φ _m is the matrix porosity of the shale gas reservoir, B _gm , B _gmi are the matrix gas volume coefficients under the current matrix pressure and the original matrix pressure, respectively, m ³ /m ³ ; C _m is the rock compressibility coefficient of the shale matrix, 1/MPa; V _Ei and _VE are the unit shale adsorbed gas volume under the original matrix pressure and the current matrix pressure, m ³ /m ³ .

in:

ΔP _m =P _mi -P _m (30)

Multiplying the gas volume coefficient under the current fracture pressure, the subsurface volume of matrix shale gas intrusion is obtained as:

V _mf = G _mf B _gf (33)

3) The free gas (underground volume) produced is:

ΔV _gp = G _p B _gf (34)

Combine formula (28), formula (33) and formula (34) to obtain the formula for calculating the gas storage capacity of the fracture:

ΔV _g = ΔV _gf +V _mf -ΔV _gp (35)

(3) Remaining volume of fracturing fluid

The reduction of the fracture pore volume, the expansion of the fracturing fluid in the fracture and the amount of gas stored in the fracture will reduce the volume of the fracturing fluid in the fracture. Therefore, when the original fracture pressure P _fi is reduced to P _f , the fracture fracturing fluid volume is:

V _w =V _wi -ΔV _f -ΔV _g (36)

Substituting Equation (27) and Equation (35) into Equation (36) yields:

The remaining fracturing fluid volume is replaced by the ground condition, as

The basic form of the material balance equation of fracture fracturing fluid is:

Put the remaining fracturing fluid volume W _res into the above formula to get:

Arranged to get:

The gas compressibility and water compressibility are:

After further sorting, we get:

W _p B _wf +G _p B _gf =V _fi ΔP[(1-I _imb )C _wf +C _f +I _imb C _g ]+G _mf B _gf (43)

It can be seen from the above formula that the main driving force for flowback fracturing fluid and shale gas production is composed of fracturing fluid expansion, fracture compression, free gas expansion and shale matrix shale gas channeling supply.

Moving the production term on the left side of equation (43) to the right side of the equation, the function h about fracture pressure and matrix pressure at the k+1 time step is:

in:

Fracture water saturation under current formation conditions:

Simplify to get:

When the function (44) is equal to 0, the equation about the average pressure of the fracture network and the average pressure of the matrix system at time k+1 can be obtained as:

The above equation has two unknowns P _f ^k+1 and P _m ^k+1 . To solve this equation, we also need to establish the material balance equation of the shale matrix system.

In step S3, the establishment of the material balance equation of the shale matrix system includes:

When the average fracture network pressure _{Pf is} lower than the matrix gas breakthrough pressure _PBT , channeling will occur between the matrix and fractures. The matrix gas breakthrough pressure _PBT is related to the porosity and permeability of the shale matrix. The channeling equation is:

where α _mf is the channeling factor from matrix to fracture, m ^-2 ; q _m is the channeling gas flow rate from matrix to microfracture per unit pore volume of matrix, s ^-1 .

If P _BT ≤ P _f ^k , the channeling flow diffusion from the matrix to the fracture system from time k to time k+1 is 0:

ΔG _mf = 0 (50)

If P _BT > P _f ^k , the matrix shale gas will channel into the fracture network system, and the channeling flow diffusion from the matrix to the fracture system from time k to time k+1 is:

where V _b is the ESRV volume, which can be calculated by:

V _b =N _f w _f x _f h _f0 -V _{b_overlap} (52)

In the above formula, x _f represents the vertical expansion degree of the effective mesh volume, and w _f represents the lateral expansion degree of the effective mesh volume. ESRV is an important parameter that is often used to quantitatively evaluate the effect of shale gas fracture network fracturing (Ren Lan et al. 2017, Lin Ran 2018).

in

where V _{b_overlap} is the ESRV overlap volume.

The channeling flow diffusion from the matrix to the fracture system from time k to time k+1 can also be expressed as:

in:

In the formula, _VL is the Langmuir volume, sm ³ /m ³ ; _PL is the Langmuir pressure, MPa.

Substituting Equation (56) and Equation (57) into Equation (55) yields:

Combining formula (51) and formula (59), the function g of fracture pressure and matrix pressure at the k+1 time step is:

Equating the function (60) to 0, the equation about the average pressure of the fracture network and the average pressure of the matrix system at time k+1 can be obtained:

The above equation has two unknowns P _f ^k+1 and P _m ^k+1 . Solving equation (48) and equation (61) simultaneously can obtain the average fracture network pressure P _f ^k+1 and matrix pressure P at time k+1 _m ^k+1 , the average pressure P _f ^k of the fracture network and the average pressure P _m ^{k of the matrix system at time k} are known values.

In step S4, the tree-shaped fractal fracture flowback model is solved by the bisection method, and the specific process is as follows.

(1) Known tree-shaped fracture network structure parameters, including l ₀ , W _f0 , h _f0 , R _L , R _w , R _h , θ, m, n, C _f and original formation conditions (p _f (k=1 )=p _fi , p _m (k=1)=p _mi ) and given p _wf , use formula (14) to calculate Q _W (k) and Q _g (k), k=1,2,..., Num;

(2) Solving the cumulative amount of the kth step, the flowback amount _{W p} =sum(Qw(k)), Gp=sum( _Qg (k));

(3) If p _f (k)>=p _BT , then there is no matrix gas channeling into the fracture, G _mf =0, then p _m (k+1)=p _m (k), and then using the dichotomy method to give The range of fracture pressure p _f (k+1) is determined [1, p _fi ], and the fracture pressure p _f ( _k +1) _is calculated in combination with the fracture material balance equation (44). Matrix gas channeling into the fracture, using the bisection method, given the fracture pressure p _f (k+1) range [1, p _fi ], under the condition of known p _f (k+1), using the bisection method, given The matrix pressure p _m (k+1) is in the range [1, p _mi ], and the matrix pressure p _m (k+1) is calculated according to the matrix material balance formula (60), and then G _mf is calculated using the formula (29), and then enters Equation (44) is solved for pf( _k +1) using the bisection method.

(4) Assign p _f (k+1), p _m (k+1) to p _f (k), p _m (k), repeat steps (1) (2) (3) until k=Num.

Preferably, in step S5, an adaptive function is constructed based on the idea of maximizing the coefficient of determination between the predicted value and the observed value, and the specific function is as follows:

in:

The decision variables are:

in:

The objective function is:

where the range of x is:

LB _i ≤x _i ≤UB _i (i=1,2,...,12) (68)

The constraints are:

V _fi ≤ TIV (69)

in:

In step S5 , the genetic algorithm workflow is used to invert the effective fracture network volume of the fracture network fracturing shale gas well, and the specific process is shown in FIG. 3 . The calculation process of the inversion model is as follows:

(1) The genetic algorithm inversion workflow starts. The genetic parameters are shown in Table 1, and the parameter boundaries of the tree-shaped fracture network are shown in Table 2. Input the flowback data of shale gas wells, fracturing operation parameters, initial reservoir parameters, etc. Basic parameters of shale gas wells. (2) Calculate bottom hole flow pressure with Beggs-Brill model. (3) Generate the initial population index of the fitting parameter _xi . (4) _Qw and _Qg are calculated by the dichotomy method. (5) Calculate the fitness value. (6) Judge whether all objects are matched or the stopping criterion is met. If yes, store the fitting parameters, calculate the effective fracture network volume of shale gas by formula (53), and end. If not, select replication, crossover and mutation to create a new population and repeat step (4).

Table 1 Genetic parameters table

Table 2. Boundary values of tree-shaped crack network parameters

Compared with the prior art, the advantages of the present invention are:

The method of the invention is used to realize accurate prediction of the effective volume of the fracturing network of shale gas wells. In this method, a mathematical model of gas-water two-phase flow in shale tree-shaped fractal network was established, the material balance equation of shale matrix-fracture network flow was deduced, and the effective fracture network volume of shale gas was designed based on fracturing fluid flowback data. The multi-objective fitting genetic algorithm workflow. The calculation result of the model is consistent with the actual situation, and the present invention is beneficial to the utilization of shale gas fracturing fluid flowback data, and enriches the evaluation method of the post-fracturing effect of fracture network fracturing in shale gas reservoirs.

Other advantages, objects, and features of the present invention will appear in part from the description that follows, and in part will be appreciated by those skilled in the art from the study and practice of the invention.

Description of drawings

Figure 1 is a tree-shaped fractal fracture network of a 1/2 single-cluster fracture network.

Figure 2 is a schematic diagram of the characteristics of the shale gas fracturing fluid flowback EGP and LGP stages.

FIG. 3 is a flow chart of inversion of production data for flowback by genetic algorithm established in the present invention.

FIG. 4 is a flowback production data diagram of a shale gas well H2 in southern Sichuan processed in the specific implementation of the present invention.

FIG. 5 is a schematic diagram of fitting the water and gas production of a shale gas well H2 in southern Sichuan according to the present invention.

FIG. 6 is a schematic diagram of the calculation of the bottom hole flow pressure, fracture network pressure, shale matrix pressure and size change of the wellhead nozzle of the shale gas well H2 according to the present invention.

Figure 7 shows the initial effective fracture volume evaluation based on the Harmonic decline model.

Figure 8 shows the initial effective fracture volume evaluation of the Alkouh model.

FIG. 9 is a schematic diagram showing the comparison of the initial effective fracture volume evaluation of the model of the present invention and different models.

Detailed ways

The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, but not to limit the present invention.

In the volume inversion method of shale gas effective fracture network based on flowback data provided by the present invention, in step S1, step S2 and step S3, the following assumptions are included: 1. Applying fractal theory, 1/2 of the effective fracture network of a single cluster, etc. The effect is the tree-shaped fractal fracture network shown in Figure 1, and it is assumed that the fracture shape is a rectangle and the fracture is a vertical fracture. ② Considering the reverse imbibition effect and the redistribution of the original free gas in the activated natural fractures, the reverse imbibition index (I _imb ) is used to represent the combined effect of the two, and the effective fracture network volume is initially saturated with fracturing fluid (water phase). ) and natural gas (gas phase). ③ Considering the supercharging effect of the fracture network, the average pressure of the fracture network (P _f ) is greater than or equal to the average pressure of the matrix (P _m ) in the initial stage of well flowback, and during the period of P _f > P _m (belonging to the early gas flowback stage, EGP stage) , in the EGP stage, due to the pressurization effect of the fracture network, ignoring the flow of matrix gas into the effective fracture network volume, the effective fracture network system is approximately a uniform closed container system, and the driving mechanism of gas-water flow in stage 1 (EGP stage) includes: Three aspects: 1) pressurization effect of fracture network; 2) fracture closure effect; 3) expansion of fluid (gas and water); during the period of P _f < P _m (belonging to late gas production stage, LGP stage), matrix gas breakthrough into the effective fracture volume, as shown in Figure 2. ④ Ignore the capillary pressure in the effective fracture network system and ignore the influence of gravity. ⑤Because of the ultra-high irreducible water saturation and capillary force of the shale matrix, the water flow in the matrix is ignored, and the water that can flow only exists in the effective fracture network system. Due to the ultra-low permeability of the shale matrix, the matrix is only considered as gas. The material exchange between the source, the matrix system and the effective fracture network system is carried out through the channeling equation, and the water and gas only flow into the wellbore through the fracture seepage. ⑥ The effective fracture network system is an elastic porous medium, and assuming that its compressibility is much greater than that of the shale matrix, the tree-fractal fracture permeability and effective fracture volume are pressure-dependent variables. ⑦ The relative permeability curve of gravity separation is suitable for characterizing the gas-water flow in the effective fracture network volume. ⑧ Consider the adsorption and desorption effect of the matrix gas, assuming that it satisfies the Langmuir isotherm adsorption equation.

The volume inversion method of shale gas effective fracture network based on flowback data provided by the present invention, in practical application, the operation steps are as follows:

(1) Collect and organize the basic data of shale gas wells after fracturing, including high-frequency flowback production data (fracturing fluid flowback per hour, shale gas production, oil pressure or casing pressure), wellbore structure data , wellbore data, formation temperature, formation pressure, reservoir thickness, reservoir porosity and saturation data, shale gas isothermal adsorption experimental data, fracturing engineering design data (total injected liquid volume, fracturing stage number, number of clusters in the stage, horizontal segment length, etc.), etc.

(2) Use the Beggs-Brill model to calculate the bottom hole flow pressure P _wf in the middle of the shale reservoir, as the input value of the bottom hole flow pressure P _wf in the tree-fractal fracture two-phase flow equation (14) established in step S1, and predict with the genetic algorithm The searched fracture network structure parameters and other model parameters (see Table 2 for the parameter search range), calculate the shale gas production and fracturing fluid flowback of 1/2 single-cluster fracture network, and then use the production superposition formulas (17) and ( 18) Calculate the model shale gas production and fracturing fluid flowback under the original fracture network pressure and original formation pressure.

(3) After obtaining the cumulative gas production and cumulative water production in the first hour, use the shale gas fracturing fluid flowback production model established in step S4 to solve the dichotomy step, and combine the fracture system material balance established in steps S2 and S3 respectively. equation and matrix system material balance equation to solve the average pressure of fracture network and matrix system at each time step, as well as shale gas production and fracturing fluid flowback.

(4) Use the genetic algorithm adaptive function formula (63) established in step S5 to calculate the fitness value under the conditions of different seam network structure parameters and other model parameters, and judge whether it reaches the stop condition, if not, enter the genetic algorithm to generate The population flow of new fracture network structure parameters and other model parameters mainly includes gene selection and replication, and gene crossover and mutation. If yes, store the optimal fracture network structure parameters and other model parameters, and then calculate the effective fracture network of shale gas. Volume (Equation 53) and other important post-pressure evaluation parameters and the production prediction of the shale gas well.

In a specific embodiment, the flowback production data of a shale gas well H2 in southern Sichuan (Fig. 4) is applied on-site, and the statistics of the basic parameters of the well are shown in Table 3.

Table 3 Statistics of basic parameters of H2 in shale gas wells

parameter unit value parameter unit value P_mi 10⁶Pa 58.79 T_i K 367.8 TIV m³ 51062.1 d_casing m 0.1143 L_w m 1500 h_f0 m 43 C_m 10^-9Pa^-1 0.3 C_w 10^-9Pa^-1 0.46 μ_w 10^-3Pa·s 0.28 μ_g 10^-3Pa·s 0.042 T_pc K 190 P_pc 10⁶Pa 4.61 P_L 10⁶Pa 2.98 V_L sm³/m³ 0.29 n_f dless 28 n_CL dless 3 φ_m dless 0.054 K_m 10^-9μm² 380 B_w dless 1.05 n dless 2

According to the present invention, using the data in Table 3, the volume inversion of the effective fracture network of shale gas is carried out for the flowback production data of Well H2. The water vapor transient history fit of H2 is shown in Figure 5. where R ² (Q _w )=0.883, R ² (Q _g )=0.927, IA(Q _w )=0.969, IA(Q _g )=0.982, K(Q _w )=1.03, K(Q _g )=0.95 , according to the statistical recommendation, R ² >0.64, 0.85<K<1.15, or IA>0.80 is a good evaluation, indicating that the fracture feature inversion of Well H2 is reliable. The root mean square error RMSE of the predicted and measured values of Q _w and Q _g is 1.54 m ³ /h and 0.14×10 ⁴ m ⁴ /h, respectively. Figure 6 shows the changes of bottom hole flow pressure, fracture network pressure, shale matrix pressure and wellhead nozzle size during the flowback process. It can be seen that after the well is opened, the fracture network pressure decreases more than the shale matrix pressure. After the first shut-in, due to the pressure difference between the fracture network system and the matrix system, the shale gas in the matrix flows into the fracture network, and the fractures The network pressure gradually recovered to be equal to the matrix pressure. After the second well opening, the fracture network pressure began to decrease again until the second shut-in, and the fracture pressure gradually recovered. Because the second shut-in time was short, the fracture network pressure did not recover. to be equal to the substrate pressure. It can be clearly seen from Fig. 5 that the fitting effect of the early part of the flowback water data of this well is not ideal. Maybe the early flowback data of this well is inaccurate and unrepresentative, because the size of the nozzle is in the first and second shutoffs. The well front was changed 4 and 9 times, respectively, see Figure 6.

The fracture characteristics of H2 obtained by the genetic algorithm workflow inversion are shown in Table 4, including the tree-fractal fracture network structure parameters, the original pressure of the fracture system, the matrix breakthrough pressure, the fracture compressibility, the reverse imbibition index, and the effective fracture network volume (ESRV). ), equivalent main fracture half-length and effective fracture volume (Table 5).

Fracture Characteristics of Table 4H2

parameter unit value parameter unit value l₀ m 50.9 W_f0 m 0.0154 m dless twenty four R_L dless 0.618 R_W dless 0.614 R_h dless 0.616 θ rad 1.07 P_BT 10⁶Pa 58.79 P_fi 10⁶Pa 58.81 α_mf m^-2 575 C_f 10^-9Pa^-1 179 I_imb dless 0 ESRV 10⁴m³ 1172 x_f m 90.85

Table 5. Effective fracture volume for H2

Model unit value HD m³ 21192 Alkouh m³ 15895 this invention m³ 10643

It can be seen from Fig. 7 that when the HD model is used for prediction in Well H2, the water flow data in the early stage is high, so the effective fracture volume is high. Abbasi (Alkouh et al., 2014) observed a linear relationship between flow-normalized pressure and material equilibrium time during the flowback process, and the effective fracture network volume can be obtained (Table 5). However, the Abbasi model ignores the fracture compressibility when calculating the total compressibility, so the effective fracture volume is also high. The method proposed in the present invention takes into account the gas-water two-phase flow and fracture compressibility, and the calculation results belong to the same order of magnitude as the results of the HD model and the Abbasi model, and are smaller than the calculation results of the two models. The flowback shale gas effective fracture network volume inversion model is reasonable and more applicable.

The above are only preferred embodiments of the present invention, and do not limit the present invention in any form. Although the present invention has been disclosed above with preferred embodiments, it is not intended to limit the present invention. Technical personnel, within the scope of the technical solution of the present invention, can make some changes or modifications to equivalent embodiments of equivalent changes by using the technical content disclosed above, but any content that does not depart from the technical solution of the present invention, according to the present invention Any simple modifications, equivalent changes and modifications made to the above embodiments still fall within the scope of the technical solutions of the present invention.

Claims (2)

1. a shale gas effective fracture network volume inversion method based on flowback data, is characterized in that, comprises the following steps: S1: Establish a gas-water two-phase flow equation in a tree-shaped fractal network reflecting the characteristics of the complex underground fracture network; S2: Considering the effects of reverse imbibition displacement of shale gas, pressurization effect of fracture network, fracture closure effect and matrix gas intrusion, establish the flow material balance equation of shale fracture system; S3: Considering the adsorption and desorption effect of matrix gas, combined with the channeling equation, establish the flow material balance equation of the shale matrix system; S4: combine the gas-water two-phase flow equation model of the tree-shaped fractal network in step S1, the flow material balance equation model of the shale fracture system in step S2 and the shale matrix system flow material balance equation model in step S3 to form shale The fracturing fluid flowback production model is obtained, and the flowback model is solved by the bisection method to obtain the average pressure of the fracture network and the average pressure of the matrix system under the bottom hole pressure at different times, as well as the flowback volume of the fracturing fluid and the shale gas. Yield; S5: Apply the established shale gas fracturing fluid flowback production model, based on the flowback production data after fracture network fracturing in shale gas wells, combined with an efficient genetic algorithm, to establish a genetic model suitable for shale gas effective fracture network volume inversion Algorithmic Workflow. 2. The effective fracture network volume inversion method for shale gas based on flowback data according to claim 1, wherein in step S1, 1/2 single-cluster tree fracture network gas/water two-phase flow rate calculation The formula is as follows:

Among them, l ₀ , W _f0 and h _f0 are the initial length, width and height of the tree fractal crack, respectively; R _L , R _W and R _h are the ratio of the length, width and height of the crack, respectively; n is the number of branches of the fractal crack, m is the fracture series, P _f is the average pressure of the fracture network, P _wf is the bottom hole flow pressure of the horizontal wellbore; μ _i is the fluid viscosity, i is the gas or water; B _i is the fluid volume coefficient, K _ri ( _Sw ) is the tree The relative permeability of gas and water in the fracture network is calculated using the linear relative permeability model: K _rw = S _w (15) K _rg = 1-S _w (16) Among them, _Sw is the water saturation in the fracture; Then, the superposition of gas and water production are respectively

Among them: N _f is the total number of clusters of staged fracturing in horizontal wells, which satisfies the following relationship N _f =n _f ·n _CL (19) where n _f is the number of fracturing stages; n _CL is the number of clusters per stage.

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