CN108319738A - A kind of shale gas well yield prediction technique - Google Patents

A kind of shale gas well yield prediction technique Download PDF

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CN108319738A
CN108319738A CN201710046501.7A CN201710046501A CN108319738A CN 108319738 A CN108319738 A CN 108319738A CN 201710046501 A CN201710046501 A CN 201710046501A CN 108319738 A CN108319738 A CN 108319738A
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shale gas
gas well
yield
data
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庞伟
杜娟
张同义
吴琼
邸德家
毛军
艾爽
贺英
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China Petroleum and Chemical Corp
Sinopec Research Institute of Petroleum Engineering
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Sinopec Research Institute of Petroleum Engineering
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Abstract

A kind of shale gas well yield prediction technique comprising：Step 1: according to shale gas well well Test Analysis Model, the double-log plate of theoretical model data is built；Step 2: obtaining the measured data of shale gas well to be analyzed, the double-log plate of measured data is built according to measured data, wherein measured data includes historical production data and formation data；Step 3: the double-log plate of the double-log plate and measured data to theoretical model data is fitted, the model parameter of shale gas well yield prediction to be analyzed is determined；Step 4: according to the model parameter that default shale gas well yield prediction model and shale gas well yield are predicted, the forecast production of shale gas well to be analyzed is determined.This method is suitable for the shale gas well of irregular cracks, and which raises the reliabilities of input parameter when production forecast, have ensured the accuracy of production forecast result, plays an important roll to evaluation shale gas well fracturing transformation effect, Production development, economic benefit.

Description

Shale gas well yield prediction method
Technical Field
The invention relates to the technical field of oil and gas exploration and development, in particular to a shale gas well yield prediction method.
Background
The shale gas is unconventional natural gas which exists in the organic matter-rich shale and the interlayer thereof and takes adsorption and free states as main existing modes, and the component of the shale gas is mainly methane. Shale gas tends to be distributed in the relatively thick, widely distributed shale source rock formations within the basin. Unlike conventional reservoir gas reservoirs, shale is both a source rock for natural gas generation and a reservoir and cap rock for gathering and storing natural gas, so black shale, high carbon mudstone and the like with high organic matter content are often the best conditions for shale gas development.
Because the shale gas reservoir has low permeability and high exploitation difficulty, effective development can be realized only by horizontal well drilling and a multi-section fracturing technology. With the development of horizontal well drilling and multi-section fracturing technologies, shale gas is commercially developed in the United states, Canada and China. In the united states, shale gas has been produced in a proportion of over 20% of the total natural gas production. China is the third country in the world where shale gas breakthrough is made, the shale gas resource amount reaches 25.1 trillion square, and the resource amount is huge.
The yield prediction is the basis of shale gas well fracturing effect evaluation, production dynamic analysis, recoverable reserves and recovery rate prediction, fracturing optimization design and economic evaluation, and has very important functions. Due to the fact that complex factors such as multi-scale flow mechanism coupling, fracture form recognition, interaction of artificial fractures and natural fractures, flow field diagnosis and the like are involved, the shale gas well yield prediction is difficult, uncertain factors are multiple, and accuracy is poor.
Disclosure of Invention
In order to solve the problems, the invention provides a shale gas well yield prediction method, which comprises the following steps:
firstly, constructing a double logarithm chart of theoretical model data according to a shale gas well test analysis model;
acquiring measured data of the shale gas well to be analyzed, and constructing a log-log chart of the measured data according to the measured data, wherein the measured data comprises historical production data and stratum data;
fitting the double-logarithm chart of the theoretical model data and the double-logarithm chart of the measured data to determine model parameters of the yield prediction of the shale gas well to be analyzed;
and step four, determining the predicted yield of the shale gas well to be analyzed according to a preset shale gas well yield prediction model and model parameters of shale gas well yield prediction.
According to one embodiment of the invention, the step of constructing a log-log version of the theoretical model data comprises:
calculating the yield normalized pressure and the yield normalized pressure derivative under the theoretical model data, and drawing a log-log curve of the yield normalized pressure and the material balance time and a log-log curve of the yield normalized pressure derivative and the material balance time under the theoretical model data based on the shale gas well test analysis model to obtain a log-log chart of the theoretical model data; or,
and calculating a yield normalized pressure integral and a yield normalized pressure integral derivative under the theoretical model data, and drawing a log-log curve of the yield normalized pressure integral and the material balance time and a log-log curve of the yield normalized pressure integral derivative and the material balance time under the theoretical model data based on the shale gas well test analysis model to obtain a log-log chart of the theoretical model data.
According to an embodiment of the present invention, the step of constructing a log-log layout of measured data from the measured data comprises:
calculating the yield normalized pressure and the yield normalized pressure derivative under the actual measurement data, and drawing a log-log curve of the yield normalized pressure and the material balance time and a log-log curve of the yield normalized pressure derivative and the material balance time under the actual measurement data based on the shale gas well test analysis model to obtain a log-log chart of the actual measurement data; or,
and calculating a yield normalized pressure integral and a yield normalized pressure integral derivative under the measured data, and drawing a log-log curve of the yield normalized pressure integral and the material balance time and a log-log curve of the yield normalized pressure integral derivative and the material balance time under the measured data based on the shale gas well test analysis model to obtain a log-log chart of the measured data.
According to an embodiment of the invention, in the third step, a gas production profile test is performed on the shale gas well to be analyzed to obtain the yield of each fracture of the shale gas well to be analyzed, and the length proportion of each fracture is determined according to the yield of each fracture.
According to one embodiment of the invention, the length ratio of the individual cracks is equal to the ratio of the individual production volumes.
According to an embodiment of the invention, fitting is performed on the log-log version of the theoretical model data and the log-log version of the measured data according to the length proportion of each crack.
According to one embodiment of the invention, daily yield, accumulated yield and pressure fitting are carried out on the fitted log-log chart, the length, permeability and SRV volume of each crack in the shale gas well to be analyzed are determined, and model parameters for predicting the yield of the shale gas well to be analyzed are obtained.
According to one embodiment of the invention, in step four:
calculating the bottom hole standard pressure of the shale gas well to be analyzed according to the yield prediction parameters of the shale gas well;
and determining the predicted yield of the shale gas well to be analyzed according to the bottom hole standard pressure under preset production condition parameters and abandonment condition parameters based on the preset shale gas well yield prediction model.
According to one embodiment of the invention, the preset shale gas well yield prediction model is as follows:
wherein m iswDRepresenting shaleDimensionless bottom hole standard pressure of gas well, tDRepresenting dimensionless time, n representing the number of fracture segments, qDjDimensionless yield, S, representing the jth fracture of shale gas wellxDDimensionless Green function, S, representing the x-directionyDDimensionless Green function, x, representing the y-directionwDDenotes the dimensionless coordinate position of the crack on the horizontal axis, xwDjDenotes the dimensionless coordinate position of the jth crack on the horizontal axis, ywDDenotes the coordinate position of the crack on the longitudinal axis, ywDjThe dimensionless coordinate position of the jth crack on the vertical axis is shown.
According to the method provided by the invention, the shale gas well stress sensitivity, desorption, diffusion and mixed gas high-pressure physical property parameters are defined as standard pressure, and an irregular crack shale gas horizontal well yield prediction model is established. Meanwhile, the history fitting method adopted by the method is based on plate fitting, basic parameter values are determined through fitting of measured data and a typical curve plate, history fitting of pressure and yield is completed through a time fitting value and a pressure fitting value, and fracture parameters and reservoir parameters of irregular fractures are obtained through production data well testing plate fitting and history fitting.
The method also obtains the proportion between the lengths of the irregular cracks through a gas production profile test, and the obtained fitting result is consistent with the actual test result. The method improves the shale gas well yield and pressure history fitting effect, greatly improves the model precision and reduces the multi-solution property. In addition, after parameters such as different accurate crack lengths, permeability, SRV volumes and the like are obtained, a production system and abandonment conditions are set for shale gas well yield prediction, and basic input parameters and prediction results are more reliable.
The invention provides a yield prediction method particularly suitable for an irregular fractured shale gas well, which can be used for obtaining accurate fracture parameters (such as fracture lengths) of different fractured sections and is suitable for the irregular fractured shale gas well, and the reliability of input parameters in yield prediction is improved based on the chart fitting and history fitting of production data, so that the accuracy of yield prediction results is ensured, and the yield prediction method has an important effect on evaluating the fracturing modification effect, production dynamics and economic benefits of the shale gas well.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required in the description of the embodiments or the prior art:
FIG. 1 is a schematic flow chart of an implementation of a shale gas well production prediction method according to an embodiment of the invention;
FIG. 2 is a schematic flow chart of constructing a log-log graph of theoretical data according to one embodiment of the present invention;
FIG. 3 is a schematic diagram of a log-log graph plate according to one embodiment of the invention;
FIG. 4 is a schematic diagram of a log-log fitting of shale gas well production data analysis according to an embodiment of the present invention;
FIG. 5 is a shale gas well pressure history fit graph according to an embodiment of the present invention;
FIG. 6 is a historical fit of the daily and cumulative production of a shale gas well according to one embodiment of the present invention;
FIG. 7 is a graph of gas production profile test results for a shale gas well in accordance with an embodiment of the present invention;
FIG. 8 is a schematic illustration of shale gas well production fracture location and fracture half-length according to an embodiment of the present invention;
FIG. 9 is a graph of predicted comparisons of regular fracture to irregular fracture shale gas well production according to one embodiment of the present invention.
Detailed Description
The following detailed description of the embodiments of the present invention will be provided with reference to the drawings and examples, so that how to apply the technical means to solve the technical problems and achieve the technical effects can be fully understood and implemented. It should be noted that, as long as there is no conflict, the embodiments and the features of the embodiments of the present invention may be combined with each other, and the technical solutions formed are within the scope of the present invention.
In the following description, for purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of the embodiments of the invention. It will be apparent, however, to one skilled in the art that the present invention may be practiced without some of these specific details or with other methods described herein.
Additionally, the steps illustrated in the flow charts of the figures may be performed in a computer system such as a set of computer-executable instructions and, although a logical order is illustrated in the flow charts, in some cases, the steps illustrated or described may be performed in an order different than here.
The existing shale gas yield prediction method mainly comprises three methods, namely: a yield decrement model method, an oil reservoir numerical simulation method and an analytical model method. The accuracy of the oil deposit numerical simulation method is highest, but the implementation time of the method is very long, the required data is the most, and many data cannot be obtained or the accuracy of the data cannot be determined even if the data is obtained, so that the oil deposit numerical simulation method is mainly applied to shale gas wells with relatively rich and complete data.
The yield decrement model method adopts an empirical or semi-empirical method to predict the yield, wherein the shale gas yield decrement model mainly comprises an Arps model, an SEDM model and a Duong model. The yield decreasing model method needs less data in the implementation process, but because the yield decreasing models are all experience or semi-experience models, technicians are often required to select the models according to experience when the yield decreasing model method is applied on site, so that the influence of subjective factors is large, the prediction effect is good and bad, a reasonable prediction result is difficult to obtain, and the application of the yield decreasing model method is limited.
The calculation speed of the analytical model method is faster than that of the oil reservoir numerical simulation method, and the accuracy of the result is higher than that of the yield decreasing model, so that the analytical model method is more widely applied. The existing shale gas well yield prediction analysis model method mainly aims at a regular artificial fracture horizontal well, and fractures are assumed to be uniformly distributed in fracture intervals and equal in length in the implementation process. However, current analytical modeling methods cannot predict shale gas horizontal well production when fractures are irregular (e.g., unequal fracture spacing or unequal length).
Most fractures of shale gas wells in actual production are irregular due to severe anisotropy of shale reservoirs and different amounts of fracturing fluid and sand in construction. The current yield prediction method does not consider the irregular condition of the crack, and simultaneously parameters such as the length of the crack, permeability and the like used in the prediction are all artificially given input parameters, and the parameters are not accurate due to a plurality of uncertain factors, so that the error in the prediction is large.
In view of the above problems in the prior art, the present embodiment provides a new shale gas well production prediction method. The method can obtain accurate fracture parameters (such as fracture length) of different fracture sections, is suitable for shale gas wells with irregular fractures, and improves the reliability of basic parameters during yield prediction based on the plate fitting and history fitting of production data
Fig. 1 shows a schematic implementation flow diagram of the shale gas production prediction method provided by the embodiment.
As shown in fig. 1, the method provided in this embodiment first establishes a shale gas well testing analysis model in step S101. Specifically, in this embodiment, the method first determines a corresponding gas reservoir model, well type, fluid type, fracture morphology, wellbore condition, and outer boundary according to the shale gas well to be analyzed in step S101. For example, for shale gas wells, the method preferably uses a two-hole model as its gas reservoir model and determines its well pattern as a multi-staged fractured horizontal well in step S101. For shale gas reservoirs, if only gas is produced, then the gas phase may be the fluid type; and if gas and water are produced simultaneously, a gas-water two-phase model can be used as the fluid type of the gas-water two-phase model. In addition, the method preferably determines the fracture morphology of the shale gas well to be analyzed as a multi-stage fracture.
In determining wellbore conditions, the method may use limited diversion, unlimited diversion, or even production as its wellbore conditions, depending on the actual condition of the shale gas well being analyzed. Meanwhile, the method preferably has a closed boundary or a constant pressure boundary as its outer boundary, depending on the actual condition of the shale gas reservoir.
The gas flow in shale involves various conditions such as diffusion effect, adsorption effect, seepage and the like, and also considers pressure-sensitive effect (the permeability and the porosity change along with the pressure change). For the pressure-sensitive effect in the shale gas reservoir, the standard pressure m can be calculated according to the following expression:
wherein phi isiRepresenting original formation porosity, kiRepresenting the original formation permeability, k representing the formation permeability, p representing the pressure of the gas in the formation, piRepresenting the original pressure of the gas in the bottom layer, z representing the gas deviation factor of the gas in the equation of state, ziRepresents the original gas deviation factor of the gas in the equation of state, mu represents the gas viscosity, muiRepresenting the original gas viscosity.
The dimensionless (i.e., dimensionless) of the standard pressure m can be expressed as:
mDrepresents a dimensionless standard pressure, miRepresenting the standard pressure corresponding to the pressure of the original stratum, m (r, t) representing the standard pressure at the r position at the t moment in the shale reservoir, qscRepresenting the ground production, BgiRepresenting the original volume factor and h the formation thickness.
In laplace space, the standard pressure seepage equation considering diffusion and adsorption effects is established as follows:
in the formula,
wherein,denotes the standard pressure, x, in Laplace spaceDRepresenting dimensionless x-axis coordinate position, yDrepresenting dimensionless y-axis coordinate position, x representing horizontal axis coordinate position, y representing vertical axis coordinate position, L representing half-length sum of crack, omega representing storage-capacity ratio, α representing comprehensive storage-capacity coefficient, s representing Laplace operator, lambda representing channeling coefficient, q representing total length of crack, and the likescDenotes the yield under standard conditions, BiRepresenting the original volume coefficient, mLDenotes Langmuir adsorption standard pressure, micDenotes the standard pressure in the original state, phi denotes the formation porosity, CgDenotes the isothermal compressibility, τ denotes the adsorption time in shale gas, R denotes the outer radius of gas diffusion in shale, D denotes the gas diffusion coefficient in shale, xfiRepresents the half-length of the i-th crack, and n represents the total number of cracks.
For the pressure distribution of a multi-staged fractured horizontal well, a rectangular boundary x is usede×yeFor example, the horizontal well position is (x)w,yw) The source function is a sideband source function S in a sideband closed boundaryxMultiple linear primitive function S in the closed boundary with the stripyThe product of (a).
Wherein, the sideband source function S in the sideband closed boundaryxCan be expressed as:
multiple line primitive function S in strip closed boundaryyCan be expressed as:
wherein x iswDenotes the coordinate position of the crack on the horizontal axis, t denotes time, xfDenotes the half-length of the crack, xerepresenting the size of the boundary, η, in the x-axis directionxDenotes the coefficient of pressure conduction in the x-direction, ywDenotes the coordinate position of the crack on the longitudinal axis, yerepresenting the size of the boundary, η, in the x-axis directionyThe impulse coefficient in the y direction is shown.
The source function S of a multi-staged fractured horizontal well can therefore be expressed as:
wherein q isjRepresents the yield of the jth crack, and q represents the total yield of all cracks.
To solve the standard pressure in Laplace spaceDimensionless expression (14) is defined as:
qDj＝qj/q (15)
therefore, the relationship between the shale gas well yield and the standard pressure in the Laplace space can be established as follows:
in the formula,
wherein,representing the dimensionless yield of the jth crack in the Laplace space, s representing the Laplace variable,represents the dimensionless standard pressure of the ith crack in Laplace space,represents the dimensionless standard pressure S caused by the production of the jth crack to the ith crack in the Laplace spacexDDimensionless Green function, S, representing the x-directionyDDimensionless Green function, t, representing the y-directionDRepresenting dimensionless time, xeDSize of dimensionless boundary, y, representing the x-axis directioneDthe dimensionless boundary size in the y-axis direction is represented, alpha represents the heterogeneous coefficient, xwDRepresenting the dimensionless coordinate position of the crack on the x-axis, ywDDenotes the coordinate position of the crack on the y-axis, xDRepresenting dimensionless horizontal axis coordinate position, yDrepresenting dimensionless ordinate positions of the longitudinal axis, ηxexpressing the pressure coefficient, η, in the x-directionyThe pressure coefficient in the y direction is expressed, t is time, k is permeability, phi is porosity, mu is viscosity, and c is compressibility.
Since all fractures are connected together by a horizontal well, it can be assumed that the pressure of each fracture at the horizontal well is equal. According to the standard pressure definition, the following matrix equation is provided:
solving the expression (24), performing inverse Laplace transformation, and calculating the yield of each fracture, wherein the standard pressure distribution in the shale gas reservoir is finally obtained as follows:
dimensionless bottom hole standard pressure mwDThe calculation expression of (a) is:
as shown in fig. 1, after a shale gas well test analysis model of a shale gas well to be analyzed is established, in step S102, according to the shale gas well test analysis model, a log-log chart of theoretical model data is established.
In this embodiment, the method includes the steps ofS102 according to the obtained mwD-tDAnd m'wD-tDAnd drawing a log-log graph plate according to the relation. Wherein m'wDThe derivative of the downhole gauge pressure is represented by a derivative of the expression (26) scale. Specifically, as shown in fig. 2, in step S201, the method first calculates the yield normalized pressure and the yield normalized pressure derivative under the theoretical model data, and dimensionless the data, and then in step S202, based on the shale gas well test well analysis model, draws a log-log curve of the yield normalized pressure and the material balance time and a log-log curve of the yield normalized pressure derivative and the material balance time under the theoretical model data, so as to obtain a log-log version of the theoretical model data.
It should be noted that the non-dimensionalization is only a processing means, and is to facilitate the calculation and the interpretation of the well test model parameters by using the log-log chart, and in other embodiments of the present invention, the production normalized pressure and the production normalized pressure derivative under the theoretical model data may not be dimensionalized.
By using the same method, the method can also establish a log-log chart of the measured data based on the measured data of the shale gas well to be analyzed. In this embodiment, the measured data includes historical production data and formation data. Specifically, the historical production data preferably includes: daily gas production, cumulative gas production, daily water production, cumulative water production, and bottom hole flow pressure. Wherein, if there is no bottom hole flowing pressure, the bottom hole flowing pressure is obtained by converting the wellhead oil pressure or casing pressure. The formation data preferably includes: porosity, permeability, original formation pressure, formation temperature, reservoir thickness, fluid composition, gas density, facies permeability curve (if gas and water are selected), fracture number, fracture half-length, fracture spacing, fracture conductivity, and gas supply area corresponding to the shale gas well.
Specifically, as shown in fig. 1, the method obtains measured data of a shale gas well to be analyzed in step S103, and then constructs a log-log graph of the measured data according to the measured data in step S104. The specific principle and process for constructing the log-log chart of the measured data are similar to those of the log-log chart of the theoretical model data, so that the specific content of the log-log chart of the measured data is not repeated here.
It should be noted that, in other embodiments of the present invention, when constructing the log-log graph of theoretical model data and the log-log graph of actual measurement data, the method may also be constructed by yield normalized pressure integral and yield normalized pressure integral derivative, which have a similar principle to the above-mentioned principle based on yield normalized pressure and yield normalized pressure derivative, and therefore, the details are not repeated herein.
After obtaining the log-log chart of the theoretical model data and the log-log chart of the measured data, the method fits the log-log chart of the theoretical model data and the log-log chart of the measured data, so as to determine the model parameters of the yield prediction of the shale gas well to be analyzed.
When the shale gas well production data well testing analysis and the yield prediction are carried out, in order to obtain an accurate model and basic input parameters, the chart fitting, the yield (including daily yield and accumulated yield) and the historical fitting of pressure are carried out. In the present embodiment, the log-log graph is given by expression (26), specifically as shown in fig. 3.
As shown in fig. 1, the method performs fitting on the log-log version of the theoretical model data and the log-log version of the measured data in step S105, and determines whether the fitting result satisfies a first preset fitting accuracy in step S106.
If the first preset fitting accuracy cannot be met, returning to the step S101 to reconstruct the shale gas well testing analysis model. If the first preset fitting accuracy can be satisfied, in step S107, the method performs yield and pressure fitting based on the fitted log-log plate, and in step S108, determines whether the fitting result can satisfy the second preset fitting accuracy. If the second preset fitting accuracy cannot be met, returning to the step S101 to reconstruct the shale gas well testing analysis model. If the second preset fitting accuracy can be met, the method can determine the model parameters of the yield prediction of the shale gas well to be analyzed according to the fitting result in step S109.
It should be noted that, in different embodiments of the present invention, specific values of the first preset fitting accuracy and the second preset fitting accuracy may be configured to be different reasonable values according to actual needs, and the present invention does not limit the specific values of the first preset fitting accuracy and the second preset fitting accuracy.
Meanwhile, it should be noted that, when the shale gas well test well analysis model is reconstructed, if different gas reservoir models, well types, fluid types, fracture types, wellbore types, outer boundary conditions and the like are selected, the shale gas well test well analysis model is established in the same form, and is in the form of an expression (25) and an expression (26), but the parameter S is insidexDAnd SyDThere will be differences in the values of (c).
In this embodiment, the method defines the material balance time, normalizes the measured data by calculating the ratio of cumulative yield to yield, and converts the gas pressure to the standard pressure using expression (1). Specifically, with the definition of the material equilibrium time, the method converts the raw data as follows:
wherein, tcDenotes the time of material equilibrium, μ denotes the viscosity, CtRepresenting the overall compression factor, q the daily output,denotes the mean pressure, t denotes the time, mdDenotes the production normalized pressure,. DELTA.m denotes the amount of change in the standard pressure, and mddDenotes the yield normalized pressure derivative, mdiRepresents the yield normalized pressure integral, mdidThe yield normalized pressure integral derivative is shown.
With material equilibration time tcAs abscissa, respectively normalized by the yield mdAnd yield normalized pressure derivative mddOr the yield normalized pressure integral mdiAnd yield normalized pressure integral derivative mdidFor the ordinate, a log-log curve of the measured data can be drawn, and a chart curve is dragged to fit with the log-log curve, and the result is shown in fig. 4, wherein the graph is implemented as a theoretical chart and the scattered points are the measured data.
In the process of fitting the log-log plate, the horizontal distance dragged by the plate is called as a time fitting value, the vertical distance is a pressure fitting value, and the specific definition is as follows:
wherein, TMRepresenting the time fit value, tTBA graphic value (dimensionless) representing the time corresponding to any one fitted point in the curve, tSJRepresenting the corresponding time of the fitting pointMeasured value of (a).
Wherein, PMRepresents the yield normalized pressure fit value, mTBGraphic values, m, representing yield-normalized pressure at any one of the fitted points in the curveSJThe measured values of the yield-normalized pressure corresponding to the fitting points are shown.
The historical fitting of pressure and yield is based on a plate fit, in which the method first calculates the corresponding material balance time t point by point according to expression (27) for known raw production datacThen, the measured value m of the yield normalization pressure at each time point is calculated by expression (32), expression (33) and log-log plate respectivelySJFinally, the pressure fitting data is derived from the production history data by using the expression (26), and the production fitting data and the accumulated production fitting data are derived from the pressure history data, as shown in fig. 5 and 6. In this embodiment, through log-log plate fitting and history fitting of yield and pressure, the method can obtain model parameters for yield prediction, such as total length of fracture, permeability, SRV volume, and the like.
In the embodiment, the yield of each crack of the shale gas well to be analyzed can be obtained by performing gas production section test on the shale gas well to be analyzed, the length proportion of each crack can be determined according to the yield of each crack, and the length of each crack can be determined by combining the total length of the crack.
Specifically, in this example, through the term profile test, the yield contributions of the different fractures as shown in fig. 7 can be obtained. Since the ratio of the lengths of the different fractures is equal to the ratio of their yield contributions, the ratio between the different fractures is fixed when performing the plate and history fits, which results in the lengths of the different fractures as shown in fig. 8.
As shown in fig. 1 again, after determining the yield prediction parameter of the shale gas well to be analyzed, in step S110, the method may determine the predicted yield of the shale gas well to be analyzed according to the shale gas well yield prediction model and the yield prediction parameter of the shale gas well.
Specifically, in this embodiment, the method calculates a bottom-hole standard pressure of the shale gas well to be analyzed according to the determined yield prediction parameter, and then determines the predicted yield of the shale gas well to be analyzed according to the bottom-hole standard pressure under a preset production condition parameter (for example, a fixed pressure or a fixed yield) and a preset abandonment condition parameter (for example, an abandonment yield or an abandonment pressure) according to a preset shale gas well yield prediction model.
The application of the shale gas well production prediction method provided by the invention is described by taking one multi-section fractured shale gas horizontal well of a certain oil field as an example. The basic parameters of the well are shown in table 1, specifically, the well production time is 18528 hours, the daily production and pressure data are 1 point per 24 hours, for 1048 groups of data.
TABLE 1
Parameter name Numerical value Parameter name Numerical value
Pressure of original formation 29MPa Porosity of 4％
Thickness of the formation 38m Length of horizontal section 1008m
Formation temperature 80℃ Number of stages of fracturing 15
The results of the gas profile test of the well are shown in fig. 7, and it can be seen that only 7 of the 15 slots contribute to production, and the 7 slots are 3 rd, 4 th, 5 th, 12 th, 13 th, 14 th and 15 th cracks, and contribute to the total production by 4.81%, 1.55%, 2.27%, 4.5%, 18.46%, 57.59% and 9.48%. The length ratios of the different fractures are set equal to their corresponding yield contribution ratios.
The production data is processed and fitted to a theoretical plate (as shown in FIG. 4) and historical data fitting of daily output and pressure data (as shown in FIGS. 5 and 6), and the fitting result is a time fitting value TM17.55(1/hr), yield normalized pressure fit value PMIs 0.22MPa-1. The half length of the 7 cracks is respectively 30m, 10m, 15m, 30m, 120m, 350m and 60m (shown in figure 8), the formation permeability is 0.065md, the surface factor of a shaft is 0.4, and the formation boundary is 1475m multiplied by 933 m.
As can be seen from the well test fitting of the production data in fig. 4, 5, and 6, the obtained historical fitting result slightly fluctuates around the original data, the offset is extremely small, and the basic trend is consistent, so that the fitting effect is considered to be very good, and the fracture and reservoir parameters obtained through the well test interpretation of the production data are reliable.
When prediction is carried out, constant pressure production is set, the bottom hole pressure is 6MPa, and the waste yield is 1 ten thousand square per day. In order to compare the production effects of the regular seam shale gas horizontal well and the irregular seam shale gas horizontal well, 7 seams in the regular seam shale gas horizontal well are set to be equal-length and equal-interval fractures, and the total length of the fractures is equal to that of the irregular seams. The prediction results are shown in fig. 9, and it can be seen from fig. 9 that the irregular fractured shale gas horizontal well can only produce 18 years, and the cumulative production is 1.43 x 108m3, while the regular fractured shale gas horizontal well can produce 22 years, and the cumulative production can reach 1.73 x 108m 3. Thus, if the well is predicted by regular fractures, 21% more cumulative production will be produced than actually produced.
The comparison shows that the yield prediction method of the irregular crack shale gas horizontal well limits the proportion between the lengths of the irregular cracks through gas production profile testing, obtains the crack parameters and the reservoir parameters of the irregular cracks through production data well testing plate fitting and history fitting, obtains the basic parameters required by yield prediction through history fitting, ensures the reliability, has the yield prediction result of the irregular crack shale gas horizontal well which is about 21 percent less than that of a regular crack horizontal well, better accords with the actual condition, greatly improves the model prediction precision, and verifies the correctness and the practicability of the method.
According to the method provided by the invention, the shale gas well stress sensitivity, desorption, diffusion and mixed gas high-pressure physical property parameters are defined as standard pressure, and an irregular crack shale gas horizontal well yield prediction model is established. Meanwhile, the history fitting method adopted by the method is based on plate fitting, basic parameter values are determined through fitting of measured data and a typical curve plate, history fitting of pressure and yield is completed through a time fitting value and a pressure fitting value, and fracture parameters and reservoir parameters of irregular fractures are obtained through production data well testing plate fitting and history fitting.
The method also obtains the proportion between the lengths of the irregular cracks through a gas production profile test, and the obtained fitting result is consistent with the actual test result. The method improves the shale gas well yield and pressure history fitting effect, greatly improves the model precision and reduces the multi-solution property. In addition, after parameters such as different accurate crack lengths, permeability, SRV volumes and the like are obtained, a production system and abandonment conditions are set for shale gas well yield prediction, and basic input parameters and prediction results are more reliable.
The invention provides a yield prediction method particularly suitable for an irregular fractured shale gas well, which can be used for obtaining accurate fracture parameters (such as fracture lengths) of different fractured sections and is suitable for the irregular fractured shale gas well, and the reliability of input parameters in yield prediction is improved based on the chart fitting and history fitting of production data, so that the accuracy of yield prediction results is ensured, and the yield prediction method has an important effect on evaluating the fracturing modification effect, production dynamics and economic benefits of the shale gas well.
It is to be understood that the disclosed embodiments of the invention are not limited to the particular structures or process steps disclosed herein, but extend to equivalents thereof as would be understood by those skilled in the relevant art. It is also to be understood that the terminology used herein is for the purpose of describing particular embodiments only, and is not intended to be limiting.
Reference in the specification to "one embodiment" or "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the invention. Thus, the appearances of the phrase "one embodiment" or "an embodiment" in various places throughout this specification are not necessarily all referring to the same embodiment.
While the above examples are illustrative of the principles of the present invention in one or more applications, it will be apparent to those of ordinary skill in the art that various changes in form, usage and details of implementation can be made without departing from the principles and concepts of the invention. Accordingly, the invention is defined by the appended claims.

Claims (9)

1. A shale gas well yield prediction method is characterized by comprising the following steps:
firstly, constructing a double logarithm chart of theoretical model data according to a shale gas well test analysis model;
acquiring measured data of the shale gas well to be analyzed, and constructing a log-log chart of the measured data according to the measured data, wherein the measured data comprises historical production data and stratum data;
fitting the double-logarithm chart of the theoretical model data and the double-logarithm chart of the measured data to determine model parameters of the yield prediction of the shale gas well to be analyzed;
and step four, determining the predicted yield of the shale gas well to be analyzed according to a preset shale gas well yield prediction model and model parameters of shale gas well yield prediction.
2. The method of claim 1, wherein the step of constructing a log-log version of the theoretical model data comprises:
calculating the yield normalized pressure and the yield normalized pressure derivative under the theoretical model data, and drawing a log-log curve of the yield normalized pressure and the material balance time and a log-log curve of the yield normalized pressure derivative and the material balance time under the theoretical model data based on the shale gas well test analysis model to obtain a log-log chart of the theoretical model data; or,
and calculating a yield normalized pressure integral and a yield normalized pressure integral derivative under the theoretical model data, and drawing a log-log curve of the yield normalized pressure integral and the material balance time and a log-log curve of the yield normalized pressure integral derivative and the material balance time under the theoretical model data based on the shale gas well test analysis model to obtain a log-log chart of the theoretical model data.
3. The method of claim 1 or 2, wherein the step of constructing a log-log version of the measured data from the measured data comprises:
calculating the yield normalized pressure and the yield normalized pressure derivative under the actual measurement data, and drawing a log-log curve of the yield normalized pressure and the material balance time and a log-log curve of the yield normalized pressure derivative and the material balance time under the actual measurement data based on the shale gas well test analysis model to obtain a log-log chart of the actual measurement data; or,
and calculating a yield normalized pressure integral and a yield normalized pressure integral derivative under the measured data, and drawing a log-log curve of the yield normalized pressure integral and the material balance time and a log-log curve of the yield normalized pressure integral derivative and the material balance time under the measured data based on the shale gas well test analysis model to obtain a log-log chart of the measured data.
4. The method according to any one of claims 1 to 3, wherein in the third step, a gas production profile test is performed on the shale gas well to be analyzed, the yield of each fracture of the shale gas well to be analyzed is obtained, and the length proportion of each fracture is determined according to the yield of each fracture.
5. The method of claim 4, wherein the length ratio of each fracture is equal to the ratio of the respective production volumes.
6. The method of claim 4 or 5, wherein a log-log version of the theoretical model data and a log-log version of the measured data are fitted based on the length ratio of each crack.
7. The method of claim 6, wherein the fitted log-log plates are subjected to daily production, cumulative production and pressure fitting to determine the length, permeability and SRV of each fracture in the shale gas well to be analyzed, and model parameters for production prediction of the shale gas well to be analyzed are obtained.
8. The method according to any one of claims 1 to 7, wherein in step four:
calculating the bottom hole standard pressure of the shale gas well to be analyzed according to the model parameters of the yield prediction of the shale gas well;
and determining the predicted yield of the shale gas well to be analyzed according to the bottom hole standard pressure under preset production condition parameters and abandonment condition parameters based on the preset shale gas well yield prediction model.
9. The method of claim 8 wherein the pre-set shale gas well production prediction model is:
wherein m iswDRepresents dimensionless bottom hole standard pressure of shale gas well, tDRepresenting dimensionless time, n representing the number of fracture segments, qDjDimensionless yield, S, representing the jth fracture of shale gas wellxDDimensionless Green function, S, representing the x-directionyDDimensionless Green function, x, representing the y-directionwDDenotes the dimensionless coordinate position of the crack on the horizontal axis, xwDjDenotes the dimensionless coordinate position of the jth crack on the horizontal axis, ywDDenotes the coordinate position of the crack on the longitudinal axis, ywDjThe dimensionless coordinate position of the jth crack on the vertical axis is shown.
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CN109057786A (en) * 2018-07-27 2018-12-21 中国石油大学(华东) A kind of adaptive model for the estimation of untraditional reservoir recoverable reserves
CN109190218A (en) * 2018-08-21 2019-01-11 中国石油大学(北京) A kind of compact reservoir effectively stitches the dynamic identifying method of net
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CN110084431A (en) * 2019-04-30 2019-08-02 四川洁能锐思石油技术有限公司 A kind of shale gas well yield analyzing and predicting method and system
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CN114575835A (en) * 2021-06-09 2022-06-03 中国石油天然气股份有限公司 Shale gas well yield prediction method based on development experiment
CN115199240A (en) * 2022-08-25 2022-10-18 西南石油大学 Shale gas well yield prediction method and device and storage medium
CN115796070A (en) * 2022-11-04 2023-03-14 北京科技大学 Method and device for identifying flow state change characteristics of reservoir of compact oil and gas reservoir
CN115796070B (en) * 2022-11-04 2023-12-01 北京科技大学 Method and device for recognizing fluid change characteristics of tight oil and gas reservoir
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