CN105931125A - A Production Prediction Method for Segmented Multi-cluster Volume Fractured Horizontal Wells in Tight Oil - Google Patents

Abstract

The invention provides a yield prediction method for a compact oil subsection multi-cluster volume fracturing horizontal well, which is characterized in that on the basis of analysis of yield influence factors of a compact oil field development test, the change of horizontal oil content of a horizontal section is reflected by a horizontal heterogeneous coefficient of an oil layer, the size of the oil content of the horizontal section obtained by logging is reflected by the area of an envelope surface of a standard gas logging full hydrocarbon value of the oil layer along the process, the change of permeability of the reservoir is reflected by logging interpretation permeability, and the development degree of an artificial fracture is comprehensively reflected by a logging brittleness index and the inflow amount of the artificial fracture, so that the yield of the compact oil subsection multi-cluster volume fracturing horizontal well is well predicted, the investment risk in the compact oil scale development is reduced, and the aim of improving the yield benefit is fulfilled.

Description

Method for predicting yield of compact oil staged multi-cluster volume fracturing horizontal well

Technical Field

The invention belongs to the technical field of oilfield development, and particularly relates to a yield prediction method for a compact oil staged multi-cluster volume fracturing horizontal well.

Background

The compact oil refers to oil gas gathering formed by clamping or being close to a compact reservoir stratum of a high-quality hydrocarbon source rock stratum system and not carrying out large-scale long-distance migration, generally has no fracturing and natural capacity, and the staged multi-cluster volume fracturing development of the horizontal well becomes a main means for developing the compact oil at present; the most obvious difference between the development of the compact oil horizontal well and the development of the low-permeability reservoir horizontal well in the past is that the investment of a single well is large, the construction period is long, the investment risk in the scale development of the compact oil is reduced, the goal of improving the construction benefit is achieved, the yield prediction of the staged multi-cluster volume fracturing horizontal well becomes a hot point problem of the compact oil development, and meanwhile, the yield prediction is also a difficult problem and is mainly reflected in the following 2 aspects.

1. The transverse oil-containing property of a compact oil reservoir changes greatly, the yield of a horizontal well and the transverse oil-containing property have a close relation, and the change of the transverse oil-containing property heterogeneity is difficult to reflect by the existing horizontal well logging interpretation model and the testing method. The horizontal well is different from a vertical well, the horizontal well penetrates through a stratum nearly horizontally, media around a well hole are not radially symmetrical and are influenced by gravity factors, the logging state of an instrument is usually eccentric, the eccentricity has different degrees of influence on measurement of various logging instruments, and most notably, under the condition of equivalent modification scale, the correlation between oil saturation and yield of logging interpretation is poor, and influence factors sensitive to the yield need to be screened.

2. The rock brittleness index of a compact reservoir is larger, the reservoir reconstruction scale is larger, the formed fracture network is more complex, the technology for describing the length, the width and the height of the fracturing fracture of the artificial fracture network is not mature, and the result of the underground micro-seismic monitoring method which is the conventional artificial fracture detection technology is only a micro-seismic signal parameter and cannot represent the real fracture form.

From the aspect of literature investigation on the condition of a fractured horizontal well yield prediction method, the existing prediction method can be summarized into two types: one is a numerical simulation method, and the other is a theoretical analytical model prediction method. However, no matter a numerical simulation method or a theoretical analytical model prediction method is adopted, when the yield is predicted, the precision of the existing method is poor when the method is applied to a mine field due to the fact that a compact oil subsection multi-cluster volume fracturing horizontal well artificial fracture parameter description technology is not mature and the problem that the oil saturation cannot reflect the change of the horizontal well transverse oil content through conventional well logging explanation. The method is characterized in that parameters sensitive to actual yield change of the compact oil horizontal well are screened from three aspects of oiliness, permeability and fracture development degree which affect the segmented multi-cluster volume fracturing yield of the compact oil horizontal well.

Disclosure of Invention

The invention aims to solve the problems that a numerical simulation method and a theoretical analysis method are difficult to better reflect the large change of the transverse oil content of a compact oil reservoir and the difficulty in describing the development degree of an artificial fracture.

Therefore, the invention provides a method for predicting the yield of a compact oil staged multi-cluster volume fracturing horizontal well, which comprises the following steps of:

step 1) obtaining the horizontal heterogeneous coefficient HE of an oil layer after the drilling of the horizontal well is finished_f；

Step 2) obtaining the logging permeability enveloping surface area K' of the horizontal section in-process oil layer according to the permeability of the horizontal section in-process oil layer in the logging result;

step 3) obtaining a standard gas logging total hydrocarbon value Q for eliminating drilling time and inlet drilling fluid flow according to real-time logging results in the drilling process of the horizontal well_TObtaining the full hydrocarbon value enveloping surface area Q of the horizontal well section along the on-way oil layer standard gas logging by applying definite integral_T'；

Step 4), calculating the rock brittleness index by using a Barnett shale brittleness index formula through longitudinal wave time difference, transverse wave time difference and rock volume density value;

step 5) according to the rock brittleness index obtained through calculation, applying a definite integral principle to obtain the oil layer brittleness index enveloping surface area BI' of the horizontal segment along the process;

step 6) calculating the total underground liquid amount L of the single well according to the accumulated summation of the underground liquid amounts of each section in the segmented multi-cluster volume fracturing process_v；

Step 7) obtaining a yield Q prediction formula of the segmented multi-cluster volume fracturing horizontal well:

Q＝1.628*Ln(HE_f×K'×Q_T'×BI'×L_V)-50.717。

step 1) the horizontal heterogeneous coefficient HE of the oil layer_fTotal length L of oil layer for drilling water level section_oThe ratio of the number of discontinuous oil layer sections to N:

${\mathrm{HE}}_f=\frac{L_o}{N}=\frac{\underset{i=1}{\overset{N}{\mathrm{\Σ}}}{L}_i}{N}$

in the formula, HE_fThe horizontal heterogeneous coefficient of the oil layer is m/section; l is_oThe total length m of the oil layer in the water level section is drilled; n is the number of oil layer sections in the drilling horizontal section; l is_iFor drilling the length of the ith oil layer section m in the water-level section.

Step 2), calculating the area K' of the logging permeability enveloping surface of the oil layer along the horizontal section by the following formula:

$K^{\′}=\underset{i=1}{\overset{N}{\mathrm{\Σ}}}(\underset{j=1}{\overset{m}{\mathrm{\Σ}}}{k}_{ij}\×\mathrm{\Δ}l)$

k' is the area of a permeability enveloping surface of a horizontal section along in-process oil layer logging, and mD.m;

k_ijthe permeability mD at the jth sampling point in the ith oil layer section in the drilling water horizontal section is obtained;

and delta l is the logging sampling interval, m.

Step 3) measuring the total hydrocarbon value enveloping surface area Q of the standard gas of the in-situ oil layer at the horizontal well section_T' calculated by the following formula:

${Q_T}^{\′}=\underset{i=1}{\overset{N}{\mathrm{\Σ}}}(\underset{j=1}{\overset{m}{\mathrm{\Σ}}}{Q}_{Tij}\×\mathrm{\Δ}l)$

$Q_{Tij}=\frac{2}{\mathrm{\π}}\×100\×arctg\[\frac{{\mathrm{\ν}}_{ij}{t}_{ij}}{{\mathrm{\ν}}_o{t}_o}tg(\frac{\mathrm{\π}}{2}{q}_{tij}\×\frac{1}{100})\]$

wherein Q is_TThe area of an envelope surface of a standard gas measurement total hydrocarbon value of an in-situ oil layer at a horizontal section,%. m; q_TijMeasuring the total hydrocarbon value% of the standard gas corresponding to the jth sampling point of the ith oil layer section in the drilling water horizontal section;

step 4), calculating the rock brittleness index according to the following formula:

${\mathrm{BI}}_{ij}=\frac{{\mathrm{\ΔE}}_{ij}+{\mathrm{\Δ\μ}}_{ij}}{2}\×100$

wherein,

$E_{ij}=\frac{{\mathrm{\ρ}}_{bij}}{{{\mathrm{\Δt}}_{sij}}^2}\×\left(\frac{3{{\mathrm{\Δt}}_{sij}}^2-4{{\mathrm{\Δt}}_{p_{ij}}}^2}{{{\mathrm{\Δt}}_{sij}}^2-{{\mathrm{\Δt}}_{p_{ij}}}^2}\right)\×{10}^5,{\mathrm{\μ}}_{ij}=\frac{{{\mathrm{\Δt}}_{sij}}^2-2{{\mathrm{\Δt}}_{p_{ij}}}^2}{2({{\mathrm{\Δt}}_{sij}}^2-{{\mathrm{\Δt}}_{p_{ij}}}^2)};$

${\mathrm{\Δt}}_{sij}=\frac{{\mathrm{\Δt}}_{p_{ij}}}{{\[1-1.15\frac{1/{\mathrm{\ρ}}_{bij}+{(1/{\mathrm{\ρ}}_{bij})}^3}{e^{1/{\mathrm{\ρ}}_{b_{ij}}}}\]}^{1.5}}$

in the formula, BI_ijLogging brittleness index,%, corresponding to the jth sampling point of the ith oil layer section in the drilling water horizontal section; delta E_ijThe normalized Young modulus corresponding to the jth sampling point of the ith oil layer section in the drilling water horizontal section is dimensionless; Δ μ_ijThe normalized Poisson's ratio corresponding to the jth sampling point of the ith oil layer section in the drilling water horizontal section is dimensionless; e_ijFor drilling the corresponding Young's modulus at the jth sampling point of the ith oil interval in the water-level segment, 10⁴MPa；μ_ijThe Poisson ratio corresponding to the jth sampling point of the ith oil layer section in the drilling water horizontal section is dimensionless; rho_bijCorresponding rock volume density, g/cm, at the jth sampling point of the ith oil layer section in the drilling water horizontal section³；Δt_sijThe transverse wave time difference of the rock corresponding to the jth sampling point of the ith oil layer section in the drilling water horizontal section is [ mu ] s/m; Δ t_pijAnd (3) drilling longitudinal wave time difference (mu s/m) of the rock corresponding to the jth sampling point of the ith oil layer section in the water level section.

Step 5), obtaining the area BI' of the on-way oil layer brittleness index enveloping surface of the horizontal section through the following formula:

${\mathrm{BI}}^{\′}=\underset{i=1}{\overset{N}{\mathrm{\Σ}}}(\underset{j=1}{\overset{m}{\mathrm{\Σ}}}{\mathrm{BI}}_{ij}\×\mathrm{\Δ}l).$

the total amount of the ground liquid entering the single well in the step 6)Wherein L is_vTotal amount of ground liquid per well m³；L_viThe volume of the i-th section of the staged multi-cluster fracturing is measured in the ground³。

The standard gas measured total hydrocarbon value Q_TGas logging full hydrocarbon value q obtained by real-time logging in the process of drilling horizontal well through inverse trigonometric function method_tAnd (3) correcting to obtain:

$Q_{Tij}=\frac{2}{\mathrm{\π}}\×100\×arctg\[\frac{{\mathrm{\ν}}_{ij}{t}_{ij}}{{\mathrm{\ν}}_o{t}_o}tg(\frac{\mathrm{\π}}{2}{q}_{tij}\×\frac{1}{100})\]$

in the formula, v_ijFor drilling the actual drilling fluid flow m at the jth sampling point of the ith oil layer section in the water level section³/min；t_ijThe actual drilling time is min/m at the jth sampling point of the ith oil layer section in the drilling water horizontal section; v is_oFor block standard drilling fluid inlet, m³/min；t_oIn the standard drilling time of the block, min/m; q. q.s_tijAnd (4) measuring the total hydrocarbon value while drilling at the jth sampling point of the ith oil layer section in the drilling water horizontal section.

The transverse wave time difference Deltat of the rock_sijWhen the calculation formula is used for logging, only the longitudinal wave time difference delta t is measured_pijThe test was performed without testing the cross-wave moveout.

The invention has the beneficial effects that: on the basis of analysis of yield influence factors of development tests of compact oil fields, the method provided by the invention reflects the change of horizontal oil content of a horizontal section by using a horizontal heterogeneous coefficient of an oil layer, reflects the size of the oil content by using the enveloping area of a full hydrocarbon value of a horizontal section obtained by logging along a process oil layer standard gas logging, reflects the change of reservoir permeability by using logging interpretation permeability, and comprehensively reflects the development degree of artificial fractures by using a logging brittleness index and the inflow amount of the artificial fractures into the ground, so that the yield of a compact oil segmented multi-cluster volume fracturing horizontal well is well predicted, the investment risk in the scale development of compact oil is reduced, and the aim of improving the yield benefit is fulfilled.

The following will be described in further detail with reference to the accompanying drawings.

Drawings

FIG. 1 is the horizontal heterogeneous coefficients HE of the reservoir_fA relation curve with the daily yield of a single well of the horizontal well;

FIG. 2 is a curve of average permeability k at a single well fracture versus daily production of a single well of a horizontal well;

FIG. 3 is the average log porosity at a single well fractureA relation curve with the daily yield of a single well of the horizontal well;

FIG. 4 average log oil saturation S at single well fracture_oA relation curve with the daily yield of a single well of the horizontal well;

FIG. 5 is a relation curve of average rock brittleness index BI at a single well fracture and daily production of a single well of a horizontal well;

FIG. 6 average Standard gas Total Hydrocarbon number Q at fracture_TA relation curve with the daily yield of a single well of the horizontal well;

FIG. 7 is a plot of log permeability envelope area K' versus daily production for a single well of a horizontal well;

FIG. 8 is a plot of the log porosity envelope area Φ' versus the daily production of a single well of a horizontal well;

FIG. 9 is the logging oil saturation envelope surface area S_o' a curve relating the daily production of a single well of a horizontal well;

FIG. 10 is a plot of well log brittleness index envelope area BI' versus daily production for a single well of a horizontal well;

FIG. 11 is a plot of the standard gas log total hydrocarbon number envelope area Q_T' a curve relating the daily production of a single well of a horizontal well;

FIG. 12 staged multi-cluster volume fracturing fluid volume in the earth L_vA relation curve with the daily yield of a single well of the horizontal well;

FIG. 13 is a curve of the relationship between the number STA of the segmented multi-cluster volume fracture sections of the well and the daily yield of a single well of the horizontal well;

FIG. 14 is a curve of the average sand adding amount SAN of the single-well staged multi-cluster volume fracturing and the daily yield of a single well of a horizontal well;

FIG. 15 is a graph of average displacement PR of single well staged multi-cluster volume fracturing versus daily production of a single well of a horizontal well;

FIG. 16 is a plot of the average sand ratio PC for single well staged multiple cluster volume fracturing versus the daily production for a single well of a horizontal well;

FIG. 17 is a plot of envelope coefficients versus daily production for a single well of a horizontal well;

FIG. 18 is a GP47-64 well logging interpretation single well card.

Detailed Description

Example 1:

the embodiment provides a yield prediction method for a compact oil staged multi-cluster volume fracturing horizontal well, which comprises the following steps of:

step 1) obtaining the horizontal heterogeneous coefficient HE of an oil layer after the drilling of the horizontal well is finished_f；

Step 2) obtaining the logging permeability enveloping surface area K' of the horizontal section in-process oil layer according to the permeability of the horizontal section in-process oil layer in the logging result;

step 3) obtaining a standard gas logging total hydrocarbon value Q for eliminating drilling time and inlet drilling fluid flow according to real-time logging results in the drilling process of the horizontal well_TApplying definite integral to obtain standard gas logging total hydrocarbon of oil layer along horizontal well sectionValue envelope surface area Q_T'；

Step 4), calculating the rock brittleness index by using a Barnett shale brittleness index formula through longitudinal wave time difference, transverse wave time difference and rock volume density value;

step 5) according to the rock brittleness index obtained through calculation, applying a definite integral principle to obtain the oil layer brittleness index enveloping surface area BI' of the horizontal segment along the process;

step 6) calculating the total underground liquid amount L of the single well according to the accumulated summation of the underground liquid amounts of each section in the segmented multi-cluster volume fracturing process_v；

Step 7) obtaining a yield Q prediction formula of the segmented multi-cluster volume fracturing horizontal well:

Q＝1.628*Ln(HE_f×K'×Q_T'×BI'×L_V)-50.717。

the method reflects the size of oil content by using the enveloping surface area of the full hydrocarbon value of the horizontal segment along the in-process oil layer standard gas logging obtained by logging, reflects the change of reservoir permeability by using logging interpretation permeability, comprehensively reflects the development degree of artificial fractures by using logging brittleness indexes and the amount of liquid entering the ground of the artificial fractures, and guides to establish the yield prediction method of the compact oil segmented multi-cluster volume fracturing horizontal well.

Example 2:

screening of yield sensitive parameters of compact oil horizontal well

The influence factors influencing the segmented multi-cluster volume fracturing yield of the compact oil horizontal well comprise geological factors and engineering factors. Reservoir oiliness, reservoir permeability and reservoir seam network formation difficulty are considered in geological factors, wherein the reservoir oiliness can be characterized by 4 parameters of an oil layer transverse heterogeneous coefficient, a logging gas logging total hydrocarbon value, a logging oil saturation and a logging porosity, the reservoir permeability is characterized by a logging permeability, and the reservoir seam network formation difficulty is characterized by a rock brittleness index; engineering factors mainly influence the development degree of a reservoir fracture network after volume fracturing modification, and mainly comprise 5 parameters of the ground liquid entering amount, the number of the artificial fracturing modification sections, the sand adding amount, the discharge amount and the sand ratio;

the method comprises the following steps: geological factor screening

(1) Horizontal heterogeneous coefficient HE of reservoir_f: according to the well logging interpretation conclusion, the length L of the oil layer encountered by the horizontal section of each sample horizontal well is counted_oAnd the number N of oil layer sections of the horizontal section to obtain the horizontal heterogeneous coefficient HE of the oil layer of each sample horizontal well_f；

${\mathrm{HE}}_f=\frac{L_o}{N}=\frac{\underset{i=1}{\overset{N}{\mathrm{\Σ}}}{L}_i}{N}---\left(1\right)$

(2) Calculating horizontal heterogeneous coefficient HE of sample horizontal well according to formula (1)_fMaking a scatter diagram of the transverse heterogeneous coefficient and the yield of the corresponding horizontal well, wherein the correlation between a regression formula and a sample point is better as shown in figure 1, so that the transverse heterogeneous coefficient of an oil layer is taken as a main geological parameter influencing the yield factor of the compact oil horizontal well;

the method comprises the steps that geological parameters at a horizontal section fracturing position represent parameters of the whole horizontal well for analyzing influence factors of single well yield of a conventional horizontal well, and for fracturing a compact oil horizontal well with a large discharge volume, the influence factors of the compact oil horizontal well are analyzed by applying the same parameter statistical method;

(3) average logging permeability k at the single well fracture;

$k=\frac{\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{k}_i}{n}---\left(2\right)$

(4) average logging porosity at single well fracture

(5) Average logging oil saturation S at single well fracture_o；

$S_o=\frac{\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{S}_{oi}}{n}---\left(4\right)$

(6) Single well fractureMeasured total hydrocarbon number Q of average standard gas_T；

$Q_T=\frac{\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{Q}_{Ti}}{n}---\left(5\right)$

Gas logging total hydrocarbon value q obtained by real-time logging in the drilling process of horizontal well_tCorrecting and correcting by using an inverse trigonometric function method to obtain a standard gas-logging total hydrocarbon value Q for eliminating the drilling time and the inlet drilling fluid flow_T；

Standard gas survey total hydrocarbon number

$Q_{Ti}=\frac{2}{\mathrm{\π}}\×100\×arctg\[\frac{{\mathrm{\ν}}_i{t}_i}{{\mathrm{\ν}}_o{t}_o}tg(\frac{\mathrm{\π}}{2}{q}_{ti}\×\frac{1}{100})\]$

(7) Average rock brittleness index BI at a single well fracture;

$BI=\frac{\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{\mathrm{BI}}_i}{n}---\left(6\right)$

the rock brittleness index BI cannot be directly obtained through a logging curve, and a Barnett shale brittleness index calculation formula is used for calculating the brittleness index of the long-7 compact reservoir according to the longitudinal wave time difference, the transverse wave time difference and the rock volume density value;

index of brittleness

Normalized Young's modulus

Normalized Poisson's ratio

Young's modulus

Poisson ratio

The method is characterized in that an empirical formula which is suitable for gas-free sandstone or argillaceous sandstone formations and is used for estimating transverse waves is used for calculating to obtain the formation transverse wave time difference delta t_s；

${\mathrm{\Δt}}_{si}=\frac{{\mathrm{\Δt}}_{pi}}{{\[1-1.15\frac{1/{\mathrm{\ρ}}_{bi}+{(1/{\mathrm{\ρ}}_{bi})}^3}{e^{1/{\mathrm{\ρ}}_{ib}}}\]}^{1.5}}$

(8) Calculating average geological parameters at the cracks of the horizontal well according to formulas (1) to (6), and making a scatter diagram of each geological parameter and the daily yield of the single well of the horizontal well, as shown in fig. 2 to 6, as can be seen from the correlation coefficient of the regression trend line in table 1, the correlation between the average value of each geological parameter crack and the yield is poor, so that the relation between the area of a geological parameter envelope surface of the heterogeneity of an oil layer along the whole horizontal section and the yield is analyzed and considered;

(9) according to the permeability of an oil layer in a horizontal section in a logging interpretation conclusion after the drilling of the horizontal well is finished, applying a definite integral principle to obtain the logging permeability enveloping surface area K' of the oil layer in the horizontal section along the way:

$K^{\′}=\underset{i=1}{\overset{N}{\mathrm{\Σ}}}(\underset{j=1}{\overset{m}{\mathrm{\Σ}}}{k}_{ij}\×\mathrm{\Δ}l)---\left(7\right)$

(10) according to the porosity of an oil layer at a horizontal section in a logging interpretation conclusion after the drilling of the horizontal well is finished, applying a definite integral principle to obtain the logging porosity enveloping surface area phi' of the oil layer at the horizontal section along the way:

(11) according to the oil saturation of the oil reservoir in the horizontal section in the well logging interpretation conclusion after the well drilling of the horizontal well is finished, the oil saturation enveloping surface area S of the logging oil saturation of the oil reservoir in the horizontal section along the way is obtained by applying the definite integral principle_o'：

${S_o}^{\′}=\underset{i=1}{\overset{N}{\mathrm{\Σ}}}\underset{j=1}{\overset{m}{\mathrm{\Σ}}}{S}_{oij}\×\mathrm{\Δ}l---\left(9\right)$

(12) Gas logging total hydrocarbon value q obtained by real-time logging in the drilling process of horizontal well_tCorrecting and correcting by using an inverse trigonometric function method to obtain a standard gas-logging total hydrocarbon value Q for eliminating the drilling time and the inlet drilling fluid flow_TObtaining the envelope surface area Q of the standard gas-measured total hydrocarbon value of the oil layer along the horizontal section by applying the definite integral principle_T'：

Standard gas survey total hydrocarbon number

$Q_{Tij}=\frac{2}{\mathrm{\π}}\×100\×arctg\[\frac{{\mathrm{\ν}}_{ij}{t}_{ij}}{{\mathrm{\ν}}_o{t}_o}tg(\frac{\mathrm{\π}}{2}{q}_{tij}\×\frac{1}{100})\]$

The area of the envelope surface of the full hydrocarbon value of the horizontal section along the standard gas logging of the in-situ oil layer is as follows:

${Q_T}^{\′}=\underset{i=1}{\overset{N}{\mathrm{\Σ}}}(\underset{j=1}{\overset{m}{\mathrm{\Σ}}}{Q}_{Tij}\×\mathrm{\Δ}l)---\left(10\right)$

(13) the rock brittleness index BI cannot be directly obtained through a logging curve, and a Barnett shale brittleness index calculation formula is used for calculating the brittleness index of the long-7 compact reservoir according to the longitudinal wave time difference, the transverse wave time difference and the rock volume density value;

index of brittleness of rock

Normalized Young's modulus

Normalized Poisson's ratio

Young's modulus

Poisson ratio

The method is characterized in that an empirical formula which is suitable for gas-free sandstone or argillaceous sandstone formations and is used for estimating transverse waves is used for calculating to obtain the formation transverse wave time difference delta t_s：

${\mathrm{\Δt}}_{sij}=\frac{{\mathrm{\Δt}}_{p_{ij}}}{{\[1-1.15\frac{1/{\mathrm{\ρ}}_{bij}+{(1/{\mathrm{\ρ}}_{bij})}^3}{e^{1/{\mathrm{\ρ}}_{b_{ij}}}}\]}^{1.5}}$

According to the rock brittleness index obtained through calculation, obtaining the area BI' of the oil layer logging index enveloping surface of the horizontal segment along the way by applying a definite integral principle;

${\mathrm{BI}}^{\′}=\underset{i=1}{\overset{N}{\mathrm{\Σ}}}(\underset{j=1}{\overset{m}{\mathrm{\Σ}}}{\mathrm{BI}}_{ij}\×\mathrm{\Δ}l)---\left(11\right)$

(14) the sampling intervals of the logging series used in the field of the Changqing are all 0.125m, i.e. Δ l is 0.125m, so the equations (7) to (11) can be simplified into the following forms:

$K^{\′}=\underset{i=1}{\overset{N}{\mathrm{\Σ}}}(\underset{j=1}{\overset{m}{\mathrm{\Σ}}}{k}_{ij}\×\mathrm{\Δ}l)=\underset{i=1}{\overset{N}{\mathrm{\Σ}}}(\underset{j=1}{\overset{m}{\mathrm{\Σ}}}{k}_{ij}\×0.125)---\left(12\right)$

${S_o}^{\′}=\underset{i=1}{\overset{N}{\mathrm{\Σ}}}(\underset{j=1}{\overset{m}{\mathrm{\Σ}}}{S}_{oij}\×\mathrm{\Δ}l)=\underset{i=1}{\overset{N}{\mathrm{\Σ}}}(\underset{j=1}{\overset{m}{\mathrm{\Σ}}}{S}_{oij}\×0.125)---\left(14\right)$

${Q_T}^{\′}=\underset{i=1}{\overset{N}{\mathrm{\Σ}}}(\underset{j=1}{\overset{m}{\mathrm{\Σ}}}{Q}_{Tij}\×\mathrm{\Δ}l)=\underset{i=1}{\overset{N}{\mathrm{\Σ}}}(\underset{j=1}{\overset{m}{\mathrm{\Σ}}}{Q}_{Tij}\×0.125)---\left(15\right)$

${\mathrm{BI}}^{\′}=\underset{i=1}{\overset{N}{\mathrm{\Σ}}}(\underset{j=1}{\overset{m}{\mathrm{\Σ}}}{\mathrm{BI}}_{ij}\×\mathrm{\Δ}l)=\underset{i=1}{\overset{N}{\mathrm{\Σ}}}(\underset{j=1}{\overset{m}{\mathrm{\Σ}}}{\mathrm{BI}}_{ij}\×0.125)---\left(16\right)$

(15) and (4) calculating the area of the in-situ oil layer envelope surface of the horizontal section of the geological parameter of each sample horizontal well according to the formulas (12) to (16), and making scatter diagrams of the parameters and the daily yield of the single well (figures 7 to 13). Obtaining the correlation coefficient R of the trend line according to a regression formula²(see table 1), it can be seen that the relation between the area of each geological parameter envelope and the daily production of a single well is better than the relation between the average value of the fracture and the daily production of a single well. Meanwhile, the area of an oil layer logging permeability enveloping surface, the area of a standard gas logging total hydrocarbon value enveloping surface and the area of a brittleness index enveloping surface which have good correlation are screened out to be used as main factors influencing the yield of the compact oil horizontal well.

Step two: engineering factor screening

Engineering factors mainly influence the development degree of a reservoir fracture network after volume fracturing transformation, and mainly comprise 5 parameters of the ground liquid entering amount, the number of artificial fracture sections, the sand adding amount, the discharge amount and the sand ratio;

(16) single-well staged multi-cluster volume fracturing ground entering liquid quantity L_v；

$L_v=\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{L}_{vi}---\left(17\right)$

(17) The method comprises the following steps that (1) the number STA of multiple volume fracture sections is segmented in a single well;

STA＝n (18)

(18) the average sand adding amount SAN of the single-well subsection multi-cluster volume fracturing;

$SAN=\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{\mathrm{SAN}}_i---\left(19\right)$

(19) the average displacement PR of the single-well staged multi-cluster volume fracturing;

$PR=\frac{\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{\mathrm{PR}}_i}{n}---\left(20\right)$

(20) single-well subsection multi-cluster volume fracturing average sand ratio PC;

$PC=\frac{\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{\mathrm{PC}}_i}{n}---\left(21\right)$

according to the single-well engineering parameters of each sample horizontal well calculated by the formulas (17) - (21), making a scatter diagram (fig. 12-16) of each engineering parameter and the daily yield of each well, and preferably selecting the single-well earth-entering liquid amount as a main factor influencing the yield of the compact oil horizontal well according to the size of the correlation coefficient (table 1);

(II) regression of compact oil horizontal well yield formula

Analyzing the relation between each influence factor and the daily yield of a single well, and obtaining a yield prediction formula of the compact oil subsection multi-cluster volume fracturing horizontal well by 5 parameter regression as shown in figure 17;

Q＝1.628*Ln(HE_f×K'×Q_T'×BI'×L_V)-50.717 (22)

q is the volume fractured horizontal well yield, t/d.

TABLE 1 correlation coefficient of tight oil horizontal well yield influencing factors and yield scatter plots

Example 3:

the water combining length 7 is controlled by multiple sources in the west, the southwest and the south, the southwest source is taken as the main source, and two types of sedimentary facies such as delta and lake are developed; mainly develop the nepheloid rock reservoir formed by collapse of the front edge of the delta. The turbid water channel sand is used as the skeleton sand body of the region and distributed in an lobate shape and a block shape, the sand body is large in thickness, the oil layer is relatively stable in distribution, the thickness is large, the oil reservoir has a large scale, and the resource potential is large.

GP47-64 is a water-length-combined 7-reservoir one-mouth development horizontal well (figure 18), the length of the horizontal section is 680m, oil-encountering drilling intervals are 647m, the number of the oil-encountering drilling intervals is 7, a hydraulic jet annulus sand-adding volume fracturing transformation mode is adopted, and the amount of liquid entering the ground is 3550m³The area of the oil layer section logging permeability enveloping surface is 143.8 mD.m, the area of the gas logging total hydrocarbon value enveloping surface is 19137.1%. m, the area of the brittleness index enveloping surface is 34938.2%. m, and the transverse heterogeneous coefficient of the oil layer is 96.3 m/section. According to a compact oil horizontal well yield prediction formula, the daily yield of each well of GP47-64 wells is calculated to be 11.1t/d, the actual daily yield of each well is 10.5t/d, the prediction error is 5.9%, the effect is good, and the specific calculation process is shown in the GP47-64 yield prediction process.

GP47-64 yield prediction process:

the method comprises the following steps: calculating horizontal heterogeneous coefficient HE of oil reservoir_f：

Step two: calculating the area of the logging permeability enveloping surface of the horizontal section along the in-situ oil layer (see table 2):

$K^{\′}=\underset{i=1}{\overset{7}{\mathrm{\Σ}}}(\underset{j=1}{\overset{m}{\mathrm{\Σ}}}{k}_{ij}\×0.125)=143.8mD\·m$

TABLE 2 horizontal section in-situ oil layer logging permeability enveloping surface area calculation step

Step three: calculating the area of the envelope surface of the standard gas logging total hydrocarbon value of the horizontal section along the in-situ oil layer (see table 3):

${Q_T}^{\′}=\underset{i=1}{\overset{7}{\mathrm{\Σ}}}(\underset{j=1}{\overset{m}{\mathrm{\Σ}}}{Q}_{Tij}\×0.125)=17933.3\%\·m$

TABLE 3 horizontal section calculation step of full hydrocarbon value envelope area along in-situ oil layer standard gas logging

Step four: calculating the area of the brittleness index enveloping surface of the horizontal section along the in-situ oil layer logging (see table 4):

${\mathrm{BI}}^{\′}=\underset{i=1}{\overset{7}{\mathrm{\Σ}}}(\underset{j=1}{\overset{m}{\mathrm{\Σ}}}{\mathrm{BI}}_{ij}\×0.125)=34938.2\%\·m$

TABLE 4 calculation step of in-flight oil layer brittleness index envelope surface area

Step five: calculating the total amount L of the ground liquid entering the single well according to the amount of the ground liquid entering each section in the segmented multi-cluster volume fracturing process_v：

$L_v=\underset{i=1}{\overset{8}{\mathrm{\Σ}}}{L}_{vi}=386+324+443+553+520+464+494+366=3550m^3$

Step six: calculating the yield of GP 47-64:

Q＝1.628*Ln(HE_f×K'×Q_T'×BI'×L_V)-50.717

＝1.628×Ln(96.3×143.8×19137.1×34938.2×3550)-50.717

＝11.1t/d

the actual yield of GP47-64 is 10.5t/d, and the error between the calculated value and the actual value is 5.9%.

The above examples are merely illustrative of the present invention and should not be construed as limiting the scope of the invention, which is intended to be covered by the claims and any design similar or equivalent to the scope of the invention.

Claims (9)

1. A method for predicting production of tight oil staged multi-cluster volume fracturing horizontal wells, characterized in that it comprises the following steps: Step 1) After the horizontal well drilling is completed, the lateral heterogeneity coefficient HE _f of the oil layer is obtained; Step 2) According to the permeability of the oil layer along the horizontal section in the logging results, the area K' of the logging permeability envelope surface of the oil layer along the horizontal section is obtained; Step 3) According to the real-time mud logging results during the horizontal well drilling process, the standard gas logging total hydrocarbon value Q _T is obtained to eliminate the drilling time and the inlet drilling fluid flow rate, and the standard gas logging total hydrocarbon value package of the oil layer along the horizontal well section is obtained by using definite integral Surface area Q _T '; Step 4) use the Barnett shale brittleness index formula to calculate the rock brittleness index through the compressional wave time difference, the shear wave time difference and the rock bulk density value; Step 5) According to the calculated rock brittleness index, apply the definite integral principle to obtain the enveloping surface area BI' of the oil layer brittleness index along the horizontal section; Step 6) Calculate the total ground fluid volume L _v of a single well according to the cumulative summation of the volume of ground fluid in each stage in the multi-cluster volumetric fracturing process; Step 7) Obtain the production Q prediction formula of the segmented multi-cluster volume fracturing horizontal well: Q=1.628*Ln(HE _f ×K'×Q _T '×BI'×L _V )−50.717. 2. a kind of tight oil subsection multi-cluster volume fracturing horizontal well output prediction method according to claim 1, it is characterized in that: step 1) described oil layer lateral heterogeneity coefficient _HE The ratio of the length L _o to the number N of discontinuous oil layers: In the formula, HE _f is the lateral heterogeneity coefficient of the oil layer, m/segment; L _o is the total length of the oil layer in the horizontal section encountered, m; N is the number of oil layer sections in the horizontal section encountered; L _i is the horizontal section encountered The length of the i-th oil layer in the segment, m. 3. A method for predicting production of a tight oil staged multi-cluster volumetric fracturing horizontal well according to claim 1, characterized in that: step 2) the logging permeability envelope area K' of the horizontal section along the oil layer is passed through the following The formula is calculated to get: Among them, K' is the area of the enveloping surface of logging permeability along the horizontal section, mD m; k _ij is the permeability at the j-th sampling point in the i-th oil layer section encountered in the horizontal section, mD; Δl is the logging sampling interval, m. 4. A method for predicting the output of a tight oil staged multi-cluster volumetric fracturing horizontal well according to claim 1, characterized in that: step 3) the enveloping surface area Q of the standard gas measurement total hydrocarbon value of the oil layer along the horizontal well section _T ' is calculated by the following formula: Among them, Q _T ' is the _enveloping surface area of the standard gas logging total hydrocarbon value of the oil layer along the horizontal section, % m; Hydrocarbon value, %, %. 5. a kind of tight oil staged multi-cluster volume fracturing horizontal well output prediction method according to claim 1, is characterized in that: step 4) rock brittleness index is calculated by following formula: in, In the formula, BI _ij is the logging brittleness index corresponding to the jth sampling point of the i-th oil layer in the horizontal section encountered, %; ΔE _ij corresponds to the j-th sampling point of the i-th oil layer in the horizontal section _Δμij is the normalized Poisson's ratio corresponding to the jth sampling point of the i-th oil layer segment encountered in the horizontal section, dimensionless; E _ij Young’s modulus corresponding to the jth sampling point of the i-th oil layer in the horizontal section, 10 ⁴ MPa; μ _ij is the Poisson’s ratio corresponding to the j-th sampling point of the i-th oil layer in the horizontal section, Dimensionless; is the rock bulk density corresponding to the jth sampling point of the i-th oil layer section in the horizontal section encountered, g/cm ³ ; is the shear wave time difference of the rock corresponding to the jth sampling point of the i-th oil layer section drilled in the horizontal section, μs/m; is the P-wave time difference of the rock corresponding to the jth sampling point of the i-th oil layer in the drilling horizontal section, μs/m. 6. A method for predicting production of a tight oil staged multi-cluster volumetric fracturing horizontal well according to claim 1, characterized in that: step 5) the enveloping surface area of the brittleness index of the oil layer along the horizontal section BI' is obtained by the following formula : 7. A method for predicting production of a tight oil staged multi-cluster volumetric fracturing horizontal well according to claim 1, characterized in that: the total amount of ground fluid entering a single well described in step 6) Among them, L _v is the total amount of ground fluid injected into a single well, m ³ ; L _vi is the amount of ground fluid injected into stage i of segmented multi-cluster volume fracturing, m ³ . 8. a kind of tight oil staged multi-cluster volume fracturing horizontal well output prediction method according to claim 4, it is characterized in that, described standard gas logging total hydrocarbon value Q _T is by inverse trigonometric function method to horizontal well drilling process The gas logging total hydrocarbon value q _t obtained in the real-time mud logging is corrected to obtain: In the formula, ν _ij is the actual drilling fluid flow rate at the jth sampling point of the i-th oil layer in the horizontal section encountered, m ³ /min; t _ij is the j-th sampling point of the i-th oil layer in the horizontal section encountered ν _o is the standard drilling fluid inlet of the block, m ³ /min; t _o is the standard drilling time of the block, min/m; q _tij is the i-th oil layer section encountered in the horizontal section The gas-while-drilling total hydrocarbon value corresponding to the jth sampling point, %. 9. A method for predicting production of tight oil staged multi-cluster volumetric fracturing horizontal wells according to claim 5, characterized in that: the shear time difference of the rock The calculation formula is only for compressional wave time difference when used in well logging For testing, the case of shear wave jet lag was not tested.