CN114048695B

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

Info

Publication number: CN114048695B
Application number: CN202111328017.6A
Authority: CN
Inventors: 赵金洲; 任岚; 林然; 唐登济; 吴建发; 付永强; 宋毅
Original assignee: Southwest Petroleum University
Current assignee: Southwest Petroleum University
Priority date: 2021-11-10
Filing date: 2021-11-10
Publication date: 2022-09-09
Anticipated expiration: 2041-11-10
Also published as: GB2606473B; GB2606473A; GB202209350D0; CN114048695A

Abstract

The invention discloses a shale gas effective gap net volume inversion method based on flowback data, which comprises the following steps of: firstly, establishing a tree-shaped fractal crack network gas-water two-phase flow mathematical model; based on the flowback characteristics of the shale gas fracturing fluid, the flowing substance balance equation of the shale fracture system is deduced by considering the influences of the reverse shale gas imbibition and displacement effect, the fracture network pressurization effect, the fracture closure effect and the matrix gas invasion effect; establishing a flowing substance balance equation of the shale matrix system based on the adsorption and desorption effect in combination with the cross flow equation; finally, a shale gas fracturing fluid flowback model is established, and a genetic algorithm suitable for shale gas effective fracture network volume inversion is established based on flowback production data after fracture of a shale gas well fracture network and in combination with an efficient genetic algorithm. According to the shale gas fracturing fluid flowback data, the shale gas fracturing post-fracture network volume evaluation method is formed, and a shale gas pressure post-evaluation technical system is developed.

Description

Effective shale gas seam network volume inversion method based on flowback data

Technical Field

The invention relates to the technical field of unconventional oil and gas yield increasing transformation, in particular to a shale gas effective seam network volume inversion method based on flowback data.

Background

In recent years, along with the aggravation of the consumption of conventional oil and gas resources, the development difficulty of oil and gas reservoirs is gradually increased, the unconventional oil and gas resources such as shale gas occupy the dominant position of oil and gas production, and the development scale of the unconventional oil and gas resources is continuously enlarged. Due to the poor physical properties and low permeability of the shale reservoir, a fracturing fluid accompanied with a propping agent and an additive needs to be pumped into the compact shale reservoir under high pressure by adopting a horizontal well fracture network fracturing technology to create a fracture and increase a seepage channel, so that the commercial development can be realized.

Whether the fracturing transformation effect is fully determined by the effective fracture network volume or not is determined, and the conventional evaluation method of the shale gas well after fracturing mainly comprises microseismic monitoring and SRV dynamic numerical simulation. At present, a crack network is generally evaluated by microseism monitoring on a mine field, but the method has higher cost. In the SRV dynamic numerical simulation method, a large number of models are realized by extending multi-field coupling cracks. Moreover, the evaluation methods may overestimate the effective fracture network volume (ESRV) of the shale gas, and the fracture network modified volume (SRV) calculated by microseismic monitoring and numerical simulation may be large enough, but the field test yield is not matched with the fracture network modified volume (SRV). The reason is mainly that the micro-seismic monitoring technology and the numerical simulation technology cannot effectively evaluate the communication degree between fractures, isolated fractures which do not participate in yield contribution are excessively estimated, and the effective fracture network volume formed by fracture network fracturing is far smaller than the estimated value. The effective shale gas fracture network is a main seepage channel for the flowback of the fracturing fluid and the production of shale gas, and determines the flowback rate of the fracturing fluid, the gas production capacity of the shale gas well and the recoverable technical reserve. The shale gas well flow channel is used as a flow channel of fracturing fluid and shale gas, which means that effective fracture network characteristic information of the shale gas is inevitably carried in flowback production data of the shale gas well, and important characteristic parameters of reservoirs such as effective fracture network volume and the like can be inevitably obtained by accurately explaining the flowback production data. In the past, most shale gas fracturing fluid flowback data are ignored, and in recent decades, some scholars pay attention to and try to explain effective shale gas fracture network volume isofracture network characteristic information for evaluating fracture network fracturing effects contained in fracturing fluid flowback and production data. The existing flowback model does not consider the problems of reverse imbibition and displacement of fracturing fluid, seam network supercharging effect, influence of midway well closing, initial fracture pressure error estimation and the like, and can not accurately evaluate and predict the after-pressure effect and production of shale gas wells. In view of this, a shale gas effective fracture network volume inversion method based on fracturing fluid flowback needs to be provided, so that the rapid evaluation of the fracturing effect of the shale gas well and the accurate prediction of the shale gas production are realized.

Disclosure of Invention

The invention aims to provide a shale gas effective fracture network volume inversion method based on flowback data, aiming at the problem that the effective volume of a shale gas well fracture network cannot be accurately predicted by the prior art.

The invention provides a shale gas effective seam network volume inversion method based on flowback data, which mainly comprises the following steps:

s1: in order to represent the fracture bifurcation characteristics in the shale gas fracturing process, a fractal theory is applied to establish a tree-shaped fractal fracture network gas-water two-phase flow equation reflecting the underground complex fracture network characteristics.

S2: and (3) considering the influences of the shale gas reverse imbibition displacement effect, the fracture network pressurization effect, the fracture closing effect and the matrix gas invasion effect, and establishing a flowing substance balance equation of the shale fracture system.

S3: and (3) considering the adsorption and desorption effect of the matrix gas, and combining with a channeling equation to establish a flowing substance balance equation of the shale matrix system.

S4: the shale gas tree-shaped fractal two-phase flow model is combined with a flowing substance balance model of a fracture system and a flowing substance balance model of a matrix system to form a shale gas fracturing fluid flowback production model, the flowback model is solved through a dichotomy method, and fracture network average pressure, matrix system average pressure, fracturing fluid flowback volume and shale gas yield under the condition of well bottom pressure at different moments are obtained.

S5: and establishing a genetic algorithm workflow suitable for shale gas effective fracture network volume inversion by applying the established shale gas fracturing fluid flowback production model and combining an efficient genetic algorithm based on flowback production data after fracture network fracturing of a shale gas well.

The following steps are described in detail:

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

because the reservoir has symmetry, only 1/2 reservoirs with single cluster of seam networks are taken for research. According to the Hagen-Poiseuille equation, the flow rate of the rectangular crack at the k-th level of the tree-shaped crack is as follows:

in the formula,. DELTA.P _k The k-th level horizontal fracture differential pressure; μ is the fluid viscosity; l _k 、W _fk And h _fk Respectively the length, width and height of the branch fracture of the k-th fraction.

The fracture length, width and height of the kth level satisfy the following formula:

in the formula I ₀ 、W _f0 And h _f0 The initial length, width and height of the tree-shaped fractal crack are respectively; r _L 、R _W And R _h Respectively, the crack length, width and height ratio.

From equation (1), the viscous resistance to fluid flow in a single fracture is given by

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

wherein

N _k ＝n ^k (6)

In the formula, n is the branch number of the fractal crack, and n is 2; m is the fracture order, k is the kth fracture network.

The flow of the single-phase flow tree-shaped fractal fracture network is as follows:

in the formula, Δ P is the total pressure difference of the tree-shaped fractal crack network, and Δ P ═ P _f -P _wf 。

As the flow-back fluid is produced, the fracture pressure is reduced, the fracture will compress under the closing stress, and at this time, the height and the length of the fracture are assumed to be unchanged, and the width of a certain k-th-stage fracture is assumed to be W _fk Has a width W after compression of the crack _fkc Then the volume change satisfies:

V _fk -V _fkc ＝C _f V _fk ΔP _f (8)

in the formula: c _f Is the fracture compressibility; v _fk Volume of the kth-level single fracture under the original fracture pressure; v _fkc The volume of the kth-level single fracture under the current fracture pressure; delta P _f For pressure drop of the fracture system, Δ P _f ＝P _fi -P _f 。

Wherein

V _fk ＝W _fk h _fk l _k (9)

V _fkc ＝W _fkc h _fk l _k (10)

In the formula: w _fkc The current fracture pressure width of the kth single fracture.

Substituting the formula (9) and the formula (10) into the formula (8) for arrangement to obtain the product

W _fkc ＝(1-C _f ΔP _f )W _fk (11)

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

Wherein

W _f0c ＝(1-C _f ΔP _f )W _f0 (13)

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

wherein, P _f Is the average pressure of the slotted net, which varies with fluid production, P _f Solving a system of equations established by the shale fracture system flowing substance equilibrium equation established in the step S2 and the shale matrix system flowing substance equilibrium equation established in the step S3, P _wf For bottom hole flow pressure of horizontal well bore, B _i Is the volume coefficient of the fluid, i is gas and water; k _ri (S _w ) The gas/water relative permeability in the tree-shaped crack network adopts a linear relative permeability model

K _rw ＝S _w (15)

K _rg ＝1-S _w (16)

Wherein S is _w Saturated with water in the cracksAnd degree.

The gas and water yield are superposed to be respectively

Wherein: n is a radical of _f Total cluster number for staged fracturing of horizontal well, which satisfies the following relationship

N _f ＝n _f ·n _CL (19)

In the formula: n is _f Is the number of fracturing stages; n is a radical of an alkyl radical _CL The number of clusters per segment.

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

the volume of the tree fractal crack network is as follows:

V _fi the method is used as an important parameter for primarily evaluating the fracturing effect of the shale gas fracture network.

Wherein

V ₀ ＝W _f0 h _f0 l ₀ (21)

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

in the formula: and theta is the branch angle of the tree-shaped crack.

Defining shale reverse imbibition index I _imb Describing the reverse imbibition degree of the reservoir, wherein the reverse imbibition degree is the ratio of free gas in the fracture network to the fracture volume, and I is more than or equal to 0 _imb Less than or equal to 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)

the water volume in the fracture is then:

V _wi ＝(1-I _imb )V _fi (25)

the fracture water saturation under initial conditions is:

in the flowback process, certain fracturing fluid amount (W) is flowback discharged from the crack _p ) Thereafter, the pressure of the fracture system is reduced from the original fracture pressure P _fi Down to the current fracture pressure P _f Pressure drop across the crack of Δ P _f ＝P _fi -P _f . The reduction in fracture volume, expansion of the free gas volume, and the entry of matrix gas into the fracture all reduce the volume of the fracturing fluid.

(1) Reduction of fracture volume:

ΔV _f ＝V _fi C _f ΔP _f (27)

(2) increment of qi

The gas increment is the sum of the expansion of the fracture free gas and the invasion of the matrix gas, and then the produced free gas is subtracted.

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

in the formula, B _gf 、B _gfi Is the free gas product coefficient, m, at the current fracture pressure and the original fracture pressure, respectively ³ /m ³ 。

2) Matrix shale gas invasion volume V _mf

The ground volume of the invasion amount of the matrix shale gas channeling into the tree-shaped fractal fracture network is obtained by considering the compressibility of matrix pores and the desorption effect of the shale matrix adsorbed gas:

in the formula, V _b The ESRV volume is followed by a specific calculation formula; phi is a _m Porosity of shale gas reservoir matrix, B _gm 、B _gmi Respectively, the volume factor of matrix gas, m, under the conditions of the current matrix pressure and the original matrix pressure ³ /m ³ ；C _m The compression coefficient of the rock of the shale matrix is 1/MPa; v _Ei 、V _E Is the unit shale adsorption gas volume m under the conditions of original matrix pressure and current matrix pressure ³ /m ³ 。

Wherein:

ΔP _m ＝P _mi -P _m (30)

multiplying the gas volume coefficient under the current fracture pressure, and obtaining the underground volume of the invasion amount of the matrix shale gas as follows:

V _mf ＝G _mf B _gf (33)

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

ΔV _gp ＝G _p B _gf (34)

and (3) obtaining a gas storage amount calculation formula of the crack by simultaneous formula (28), formula (33) and formula (34):

ΔV _g ＝ΔV _gf +V _mf -ΔV _gp (35)

(3) residual volume of fracture fracturing fluid

Crack (crack)The reduction in pore volume, the amount of expansion of the fracturing fluid in the fracture, and the amount of fracture gas present will all reduce the volume of fracturing fluid in the fracture. Therefore, when the fracture is at the initial pressure P _fi Decrease to P _f The volume of the fracture fracturing fluid is as follows:

V _w ＝V _wi -ΔV _f -ΔV _g (36)

substituting equation (27) and equation (35) into equation (36) yields:

the remaining fracturing fluid is accumulated to surface conditions of

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

the volume W of the remaining fracturing fluid _res Bringing into the above formula yields:

finishing to obtain:

the gas compression coefficient and the water compression coefficient are respectively:

further finishing to obtain:

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)

as can be seen from the above equation, the main driving force for flowback of the fracturing fluid and production of shale gas consists of fracturing fluid expansion, fracture compression, free gas expansion, and shale matrix shale gas blow-by supply.

Moving the entries from the left side of equation (43) to the right of the equation yields a function h for fracture pressure and matrix pressure at time step k +1 as:

wherein:

fracture water saturation under current formation conditions:

the simplification results in:

with the function (44) equal to 0, the equation for the average pressure of the slotted net and the average pressure of the matrix system at time k +1 can be found as:

the above equation has two unknowns P _f ^k+1 And P _m ^k+1 Requiring solution of the equation we also need to establish a shale matrix system material balance equation.

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

when seam net average pressure P _f Below the breakthrough pressure P of the matrix gas _BT Later, channeling occurs between the matrix and the fracture, and the matrix gas breaks through the pressure P _BT Related to the porosity and permeability of the shale matrix, and the like, the channeling equation is as follows:

in the formula: alpha is alpha _mf Is the matrix to fracture channeling factor, m ^-2 ；q _m Is the flow of supply gas per unit of matrix pore volume matrix to microfracture ^-1 。

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

wherein V _b For ESRV volumes, it can be calculated by the following formula:

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

in the above formula, x _f Characterizing the extent of longitudinal expansion, w, of the effective stitched web volume _f The extent of lateral expansion of the effective stitched web volume is characterized. The ESRV is an important parameter (Naglan et al 2017, Linran 2018) commonly used for quantitative evaluation of effects in shale gas fracture network fracturing mines at present.

Wherein

In the formula, V _{b_overlap} Is the ESRV overlap region volume.

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

wherein:

in the formula, V _L Is the Langmuir volume, sm ³ /m ³ ；P _L Langmuir pressure, MPa.

Substituting equation (56) and equation (57) into equation (55) has:

combining the formula (51) and the formula (59), and obtaining a function g of the fracture pressure and the matrix pressure at the k +1 time step as follows:

with the function (60) equal to 0, one can obtain the equation for the average pressure of the slotted net and the average pressure of the matrix system at time k + 1:

the above equation has two unknowns P _f ^k+1 And P _m ^k+1 Simultaneously solving the equation (48) and the equation (61) can obtain the average pressure P of the seam network at the moment k +1 _f ^k+1 And the pressure P of the substrate _m ^k+1 Average pressure P of the slotted net at time k _f ^k And the mean pressure P of the matrix system _m ^k Is a known value.

And step S4, solving the tree-shaped fractal crack flow-back model through a dichotomy, wherein the specific flow is as follows.

(1) The tree-shaped crack network structure parameters are known, including 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 Under the condition, Q is calculated by using the formula (14) _W (k) And Q _g (k)，k＝1,2,…,Num；

(2) Solving the cumulant and the flow-back W in the k step _p ＝sum(Q _w (k))，Gp＝sum(Q _g (k))；

(3) If p is _f (k)>＝p _BT No matrix gas channeling into the fracture, G _mf When the value is 0, then p _m (k+1)＝p _m (k) Setting the fracture pressure p by bisection _f (k +1) range [1, p _fi ]Calculating the fracture pressure p in combination with the fracture material balance equation (44) _f (k + 1); and p is _f (k)<p _BT The matrix gas in the shale flows into the cracks, and the crack pressure p is given by using a dichotomy method _f (k +1) range [1, p _fi ]In the case of known p _f (k +1) Using dichotomy, a given substrate pressure p _m (k +1) range [1, p _mi ]Combined with matrix material balance equation (60)Calculating the matrix pressure p _m (k +1), then G is calculated using equation (29) _mf Then, the equation (44) is substituted, and p is solved by using the dichotomy _f (k+1)。

(4) P is to be _f (k+1)，p _m (k +1) is assigned to p _f (k)，p _m (k) And (3) repeating the steps (1), (2) and (3) until k is equal to Num.

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

wherein:

the decision variables are:

wherein:

the objective function is:

wherein x is in the range:

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

the constraint conditions are as follows:

V _fi ≤TIV (69)

wherein:

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

(1) and (3) starting the inversion workflow of the genetic algorithm, inputting the flowback data of the shale gas well, fracturing operation parameters, initial reservoir parameters and other basic parameters of the shale gas well, wherein the genetic parameters are shown in table 1, the tree-shaped fracture network parameter boundary is shown in table 2. (2) The bottom hole flow pressure was calculated using the Beggs-Brill model. (3) Generating fitting parameters x _i Initial population index of (a). (4) Calculating Q by dichotomy _w And Q _g . (5) And calculating the fitness value. (6) It is determined whether all objects are matched or a stopping criterion is reached. If yes, storing the fitting parameters, calculating the effective shale gas fracture network volume through the formula (53), and finishing. If not, copy, crossover and mutation are selected to create a new population and step (4) is repeated.

TABLE 1 genetic parameter Table

TABLE 2 Tree crack network parameter boundary values

Compared with the prior art, the invention has the advantages that:

the method is used for accurately predicting the effective volume of the shale gas well fracturing network. The method establishes a gas-water two-phase flow mathematical model of the shale tree-shaped fractal fracture network, deduces a shale matrix-fracture network flowing substance balance equation, and designs a multi-target fitting genetic algorithm workflow for inverting the effective fracture network volume of the shale gas based on the fracturing fluid flowback data. The calculation result of the model is consistent with the actual situation, the method is beneficial to the utilization of the flowback data of the shale gas fracturing fluid, and enriches the evaluation method of the effect of the shale gas reservoir fracture network after fracturing.

Additional advantages, objects, and features of the invention will be set forth in part in the description which follows and in part will become apparent to those having ordinary skill in the art upon examination of the following or may be learned from practice of the invention.

Drawings

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

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

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

FIG. 4 is a graph of flowback production data for shale gas well H2 from south of Chuannan that was processed in accordance with an embodiment of the present invention.

FIG. 5 is a graph showing a fit of the present invention to the water and gas production of a shale gas well H2 from south of the Sichuan province.

FIG. 6 is a graphical representation of the present invention's calculation of the bottom hole flow pressure, fracture network pressure, shale matrix pressure, and wellhead choke size change for a shale gas well H2.

Fig. 7 is an initial effective fracture volume evaluation based on the Harmonic decreasing model.

FIG. 8 is an initial effective fracture volume evaluation of the Alkouh model.

FIG. 9 is a schematic diagram comparing the initial effective fracture volume evaluation of the model of the present invention with that of different models.

Detailed Description

The preferred embodiments of the present invention will be described in conjunction with the accompanying drawings, and it will be understood that they are described herein for the purpose of illustration and explanation and not limitation.

The shale gas effective gap net volume inversion method based on flowback data provided by the invention comprises the following assumed conditions in the steps of S1, S2 and S3: firstly, applying a fractal theory, enabling 1/2 single-cluster effective crack network to be equivalent to tree-shaped fractal crack network shown in figure 1, and assuming that the shape of the crack is rectangular and the crack is a vertical crack. ② reverse imbibition index (I) is used to consider reverse imbibition effect and redistribution of original free gas in activated natural fracture _imb ) Representing the combined effect of the two, the effective fracture network volume is initially saturated with fracturing fluid (water phase) and natural gas (gas phase). Taking the seam network supercharging effect into consideration, and opening well and flowback initial stage seam network average pressure (P) _f ) Equal to or greater than the mean pressure (P) of the matrix _m ) At P _f >P _m During the period (belonging to the early gas backflow stage and the EGP stage), in the EGP stage, due to the seam net pressurization effect, neglecting the matrix gas flowing into the effective seam net volume, the effective seam net system is similar to a uniform closed container system, and in the stage 1(EGP stage), the driving mechanism of gas-water flow comprises three aspects: 1) a slotted net supercharging effect; 2) a fracture closure effect; 3) expansion of the fluid (gas and water); at P _f <P _m During this period (which is the late gas production phase, LGP phase), the matrix gas breaks through into the effective fracture volume, as shown in figure 2. And fourthly, neglecting capillary pressure in the effective fracture network system and neglecting the influence of gravity. Neglecting water flow in the shale matrix due to the ultra-high irreducible water saturation and the capillary force of the shale matrix, only existing the flowing water in an effective fracture network system, considering the matrix as an air source due to the ultra-low permeability of the shale matrix, performing material exchange between the matrix system and the effective fracture network system through a cross flow equation, and enabling the water and the air to enter a wellbore only through fracture seepage. And the effective fracture network system is an elastic porous medium, and assuming that the compressibility of the effective fracture network system is far greater than that of a shale matrix, the tree-shaped fractal fracture permeability and the effective fracture volume are pressure-dependent variables. And the relative permeability curve of gravity separation is suitable for representing the gas-water flow in the effective seam net volume. And (viii) considering the adsorption and desorption effect of the matrix gas, and assuming that the matrix gas meets a Langmuir isothermal adsorption equation.

The shale gas effective gap net volume inversion method based on flowback data provided by the invention has the following operation steps in practical application:

(1) the method comprises the steps of collecting and arranging basic data of the shale gas well after shale gas well pressure, wherein the basic data comprises high-frequency flowback production data (fracturing fluid flowback amount per hour, shale gas yield, oil pressure or casing pressure), well body structure data, shaft data, formation temperature, formation pressure, reservoir thickness, reservoir hole saturation data, shale gas isothermal adsorption experiment data, fracturing engineering design data (total injected liquid volume, fracturing section number, cluster number in the section, horizontal section length and the like) and the like.

(2) Calculating bottom hole flowing pressure P in middle of shale reservoir by using Beggs-Brill model _wf The bottom hole flowing pressure P in the tree-shaped fractal fracture two-phase flow equation (14) established as the step S1 _wf The shale gas yield and the fracturing fluid return displacement of a single-cluster fracture network are calculated 1/2 by combining the fracture network structure parameters and other model parameters (the parameter search range is shown in table 2) of the genetic algorithm pre-estimation search, and then the model shale gas yield and the fracturing fluid return displacement under the original fracture network pressure and the original formation pressure are calculated by using yield superposition formulas (17) and (18).

(3) After the gas yield and the water yield accumulated in the first hour are obtained, a shale gas fracturing fluid flowback production model established in the step S4 is used for carrying out dichotomy solving, and the fracture network average pressure and the matrix system average pressure as well as the shale gas yield and the fracturing fluid flowback volume in each time step are solved by combining the fracture system material balance equation and the matrix system material balance equation established in the step S2 and the step S3 respectively.

(4) Calculating fitness values under different seam network structure parameters and other model parameter conditions by using the genetic algorithm fitness function formula (63) established in the step S5, judging whether the fitness values reach a stop condition, if not, entering a genetic algorithm to generate new seam network structure parameters and other model parameter population flows, mainly comprising gene selection and replication, gene crossing and mutation, if so, storing the optimal seam network structure parameters and other model parameters, further calculating important pressure after-evaluation parameters such as shale gas effective seam network volume (formula 53) and the like, and predicting the production of the shale gas well.

In a specific embodiment, flowback production data (fig. 4) of a shale gas well H2 from south china was applied in situ, and the statistics of the basic parameters of the well are shown in table 3.

TABLE 3 shale gas well H2 basic parameter statistical table

Parameter(s)

Unit of

Value of

Parameter(s)

Unit of

Value of

P

_mi

10 ⁶ Pa

58.79

T _i

K

367.8

TIV

m ³

51062.1

d _casing

m

0.1143

L _w

m

1500

h _f0

m

43

C

_m

10 ^-9 Pa ^-1

0.3

C _w

10 ^-9 Pa ^-1

0.46

μ

_w

10 ^-3 Pa·s

0.28

μ

_g

10 ^-3 Pa·s

0.042

T _pc

K

190

P

_pc

10 ⁶ Pa

4.61

P

_L

10 ⁶ Pa

2.98

V _L

sm ³ /m ³

0.29

n _f

dless

28

n _CL

dless

3

φ _m

dless

0.054

K

_m

10 ^-9 μm ²

380

B _w

dless

1.05

n

dless

2

According to the invention, shale gas effective fracture network volume inversion is carried out on H2 well flowback production data by utilizing the data in the table 3. The water gas transient history fit of H2 is shown in fig. 5. Wherein R is 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 statistical recommendations, R ² >0.64,0.85<K<1.15, or IA>The 0.80 evaluation is better, indicating that the fracture characteristics of the H2 well are reliably inverted. Q _w And Q _g The root mean square error RMSE of the predicted value and the measured value of (1.54 m) ³ H and 0.14X 10 ⁴ m ⁴ H is used as the reference value. The downhole flow pressure, fracture network pressure, shale matrix pressure, and wellhead choke size changes during flowback are shown in figure 6. Visible fracture network after well openingThe pressure reduction amplitude is larger than that of a shale matrix, after the well is shut in for the first time, due to the fact that pressure difference exists between a fracture network system and the matrix system, shale gas channeling in the matrix enters the fracture network, the fracture network pressure gradually rises back to be equal to the matrix pressure, after the well is opened for the second time, the fracture network pressure begins to reduce again until the well is shut in for the second time, the fracture network pressure gradually rises back, and due to the fact that the well is shut in for the second time, the fracture network pressure does not rise back to be equal to the matrix pressure. As is evident from fig. 5, the early part of the flowback data of the well is not well fitted, and it is likely that the early flowback data of this well is inaccurate and unrepresentative because the nozzle size is changed 4 and 9 times before the first and second shut-in, respectively, see fig. 6.

The fracture characteristics of H2 obtained by genetic algorithm workflow inversion are shown in table 4, and include tree-form fractal fracture network structure parameters, fracture system initial pressure, matrix breakthrough pressure, fracture compression coefficient, reverse imbibition index, effective fracture network volume (ESRV), equivalent major fracture half-length, effective fracture volume (table 5), and other parameters.

Fracture characteristics of Table 4H2

Parameter(s)	Unit	Value of	Parameter(s)	Unit of	Value of
						l ₀	m	50.9	W _f0	m	0.0154
m	dless	24	R _L	dless	0.618
						R _W	dless	0.614	R _h	dless	0.616
θ	rad	1.07	P _BT	10 ⁶ Pa	58.79
						P _fi	10 ⁶ Pa	58.81	α _mf	m ^-2	575
C _f	10 ^-9 Pa ^-1	179	I _imb	dless	0
						ESRV	10 ⁴ m ³	1172	x _f	m	90.85

Effective fracture volume of Table 5H2

Model (model)	Unit of	Value of
			HD	m ³	21192
Alkouh	m ³	15895
			The invention	m ³	10643

As shown in fig. 7, when the HD model is applied to H2 well for estimation, the early water flow data is higher, which results in higher effective fracture volume. Abbasi (Alkouh et al, 2014) observed a linear relationship between flow normalized pressure and material equilibrium time during flowback, which resulted in an effective fracture network volume (Table 5). However, in the Abbasi model, when the total compression coefficient is calculated, the fracture compression coefficient is ignored, and therefore, the effective fracture volume is higher. The method provided by the invention considers gas-water two-phase flow and crack compressibility, and the calculation result is in the same order of magnitude as the results of the HD model and the Abbasic model and is smaller than the calculation results of the HD model and the Abbasic model, which shows that the shale gas effective gap net volume inversion model based on the flowback provided by the invention is reasonable and has stronger applicability.

Although the present invention has been described with reference to the preferred embodiments, it will be understood by those skilled in the art that various changes may be made and equivalents may be substituted for elements thereof without departing from the scope of the present invention.

Claims

1. A shale gas effective gap net volume inversion method based on flowback data is characterized by comprising the following steps:

s1: establishing a tree-shaped fractal fracture network gas-water two-phase flow equation reflecting the characteristics of the underground complex fracture network;

s2: considering the influences of the shale gas reverse imbibition displacement effect, the seam network pressurization effect, the seam closing effect and the matrix gas invasion effect, and establishing a flowing substance balance equation of a shale fracture system;

s3: considering the adsorption and desorption effect of the matrix gas, and combining with a channeling equation, establishing a flowing substance balance equation of the shale matrix system;

s4: combining the tree-shaped fractal fracture network gas-water two-phase flow equation model in the step S1, the shale fracture system flowing substance balance equation model in the step S2 and the shale matrix system flowing substance balance equation model in the step S3 to form a shale gas fracturing fluid flowback production model, and solving the flowback model through a dichotomy to obtain fracture network average pressure and matrix system average pressure as well as fracturing fluid flowback volume and shale gas yield under the conditions of well bottom pressure at different moments;

2. The shale gas effective fracture network volume inversion method based on flowback data of claim 1, wherein in step S1, a 1/2 single-cluster tree-shaped fracture network gas/water two-phase flow calculation formula is as follows:

wherein l ₀ 、W _f0 And h _f0 The initial length, width and height of the tree-shaped fractal crack are respectively; r _L 、R _W And R _h The crack length, width and height ratios, respectively; n is the number of branches of the fractal crack, m is the number of crack stages, P _f To seam average pressure, P _wf Is the bottom hole flowing pressure of the horizontal shaft; mu.s _i Is fluid viscosity, i is gas or water; b is _i Is the fluid volume coefficient, K _ri (S _w ) The gas/water relative permeability in the tree-shaped crack network is determined by adopting a linear relative permeability model:

K _rw ＝S _w (15)

K _rg ＝1-S _w (16)

wherein S is _w The water saturation in the fracture;

the gas and water yield are superposed to be respectively

N _f ＝n _f ·n _CL (19)

In the formula: n is _f Is the number of fracturing stages; n is _CL The number of clusters per segment.