CN106988740B - A method for predicting recoverable reserves of shale gas wells based on early production data - Google Patents
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Abstract
本发明提供了一种基于早期产量数据预测页岩气井可采储量的方法，包括：步骤1、准备页岩气井的历史产量数据；步骤2、用β函数法进行流动阶段划分与数据处理；步骤3、根据幂指数递减曲线拟合每个生产时间段内页岩气井的产量，并根据拟合曲线预测可采储量的上限值；步骤4、根据日产气量线性外推模型预测每个生产时间段内页岩气井可采储量的下限值；步骤5、利用衰竭递减模型分别拟合可采储量的上限值、下限值，确定与可采储量的上限值相对应的预测上限值以及与可采储量的下限值相对应的预测下限值；步骤6、根据可采储量的预测上限值和预测下限值，确定出可采储量的上下限区间。利用本发明可以使得利用早期产量预测的可采储量更加可靠。
The invention provides a method for predicting the recoverable reserves of shale gas wells based on early production data, comprising: step 1, preparing historical production data of shale gas wells; step 2, dividing flow stages and data processing by a beta function method; 3. Fit the output of shale gas wells in each production period according to the power exponential decreasing curve, and predict the upper limit of recoverable reserves according to the fitted curve; Step 4. Predict each production time according to the linear extrapolation model of daily gas production The lower limit of recoverable reserves of shale gas wells in the interval; Step 5, use the depletion decreasing model to fit the upper limit and lower limit of recoverable reserves respectively, and determine the upper limit of prediction corresponding to the upper limit of recoverable reserves value and the predicted lower limit value corresponding to the lower limit value of recoverable reserves; step 6, according to the predicted upper limit value and predicted lower limit value of recoverable reserves, determine the upper and lower limit interval of recoverable reserves. The use of the present invention can make recoverable reserves predicted using early production more reliable.
Description
Technical Field
The invention relates to the technical field of shale gas exploitation, in particular to a method for predicting recoverable reserves of a shale gas well based on early yield data.
Background
The method for predicting recoverable reserves by using early production data of shale gas wells is very important work in shale gas development. For shale reservoirs, with the characteristics of compactness and desorption, the production cycle is as long as decades, and the flow in the formation will be in the unsteady flow stage for a long time, and the prediction of the recoverable reserves is very difficult. In particular, in the early development period, the conventional prediction methods, such as flow material balance, Arps, Fetkovich, Blasingeam, Agarwal-Gardner and NPI, do not satisfy the condition that the flow reaches the quasi-steady state. Although many shale gas well recoverable reserves prediction models have been developed, such as the capacity prediction models developed by al. Although the method is suitable for the characteristic of unsteady flow of the shale gas, special requirements exist, such as accurate determination of parameters of reservoir permeability, half-length of cracks and the like, otherwise, a prediction result is also uncertain greatly.
At present, the methods such as PLE, SEPD, Duong, LGM and the like are more convenient methods for predicting the yield and recoverable reserves of shale gas wells, and all meet the requirements of hypotonic adaptability and flow state adaptability. However, these methods are also difficult to satisfy early prediction (2 years of production), and the prediction of recoverable reserves by these methods is also prone to large deviations and ambiguity.
Currie et al created a continuous solution prediction technique in 2010 and used for the prediction of tight and shale gas well production and recoverable reserves. This continuous prediction technique is a process of predicting the production and recoverable reserves, respectively, using sets of time-spaced production data. Providing predicted upper and lower limits for a gas well before the well reaches a boundary control flow would be beneficial in reducing prediction uncertainty. However, the method does not quantitatively describe the change rule of the recoverable reserves in different time periods, and the reliability of the prediction result is poor. In addition, the method uses the yield data of all the early periods, and the yield data of the liquid discharge stage which has a large influence on the prediction result is not excluded, so that the prediction result deviates from the true value.
Disclosure of Invention
In view of the above, it is an object of the present invention to provide a method for predicting recoverable reserves of shale gas wells based on early production data to solve the problems set forth in the background.
The method for predicting the recoverable reserves of the shale gas well based on the early yield data comprises the following steps:
step 1: obtaining yield data from the shale gas production well, filtering the yield data, and removing data points which do not accord with the overall change trend in the yield data;
step 2, identifying the production time of the filtered yield data according to a β function method in a β parameter and production time double logarithm diagram, wherein the production time comprises a liquid discharge stage, a linear flow stage and a boundary control flow stage;
and step 3: removing the yield data of the liquid drainage stage, and creating yield data subsets of different production time periods for the yield data of the remaining linear flow stage and the boundary control flow stage, wherein the number of the yield data subsets is at least four, and the starting time of each yield data subset is the starting time of the linear flow;
and 4, step 4: drawing a log-log relation curve of daily gas production and time to construct a fitting model, fitting each yield data subset through a power exponential decreasing curve, predicting the yield of the shale gas well in each production time period, summing the accumulated yield and the predicted yield of each yield data subset, and predicting the upper limit value of the recoverable reserve of the shale gas well in each production time period;
and 5: drawing a rectangular coordinate relation graph of the accumulated yield and the daily gas production rate, establishing a daily gas production rate linear extrapolation model, and predicting a lower limit value of the recoverable reserve of the shale gas well in each production time period through the daily gas production rate linear extrapolation model;
step 6: drawing the predicted upper limit value and lower limit value of the recoverable reserves and the time variable in the same rectangular coordinate, fitting the recoverable reserves in each production time period by using a depletion decreasing model, calculating until the upper limit value and the lower limit value of the recoverable reserves are not changed any more, and respectively obtaining a predicted upper limit value corresponding to the upper limit value of the recoverable reserves and a predicted lower limit value corresponding to the lower limit value of the recoverable reserves in each production time period;
and 7: and obtaining the interval between the upper prediction limit value and the lower prediction limit value of the recoverable reserves according to the upper prediction limit value and the lower prediction limit value of the recoverable reserves.
According to the method for predicting the recoverable reserves of the shale gas well based on the early-stage yield data, the yield data in the liquid discharge stage are removed, and then the recoverable reserves predicted by the early-stage yield are more reliable by establishing the prediction method for quantitatively describing the recoverable reserve change rules in different time periods.
To the accomplishment of the foregoing and related ends, one or more aspects of the invention comprise the features hereinafter fully described. The following description and the annexed drawings set forth in detail certain illustrative aspects of the invention. These aspects are indicative, however, of but a few of the various ways in which the principles of the invention may be employed. Further, the present invention is intended to include all such aspects and their equivalents.
Drawings
Other objects and results of the present invention will become more apparent and more readily appreciated as the same becomes better understood by reference to the following description taken in conjunction with the accompanying drawings. In the drawings:
FIG. 1 is a flow chart of a method of predicting recoverable reserves of a shale gas well based on early production data in accordance with the present invention;
FIG. 2 is a flow phase identification diagram according to an embodiment of the invention;
FIG. 3 is a graph of predicted production for different production time periods using a power-exponential-decreasing model fit according to an embodiment of the present invention;
FIG. 4 is a recoverable reserves plot for different production periods as predicted by the linear extrapolation of solar gas production model according to an embodiment of the present invention;
fig. 5 is a diagram of the interval between the upper and lower limits of the recoverable amount according to the embodiment of the present invention.
Detailed Description
In the following description, for purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of one or more embodiments. It may be evident, however, that such embodiment(s) may be practiced without these specific details. In other instances, well-known structures and devices are shown in block diagram form in order to facilitate describing one or more embodiments.
FIG. 1 illustrates a flowchart of a method of predicting recoverable reserves of a shale gas well based on early production data in accordance with the present invention.
As shown in fig. 1, the method for predicting recoverable reserves of a shale gas well based on early production data provided by the invention comprises the following steps:
step S1: and acquiring yield data from the shale gas production well, and filtering the yield data to remove data points which do not accord with the integral change trend in the yield data.
Before analyzing the yield data, the yield data needs to be filtered to remove data points that do not conform to the overall variation trend.
And S2, identifying the production time of the filtered yield data according to a shale gas flow state identification method in a β parameter and production time double logarithmic graph, wherein the production time comprises a liquid discharge phase, a linear flow phase and a boundary control flow phase.
The step S2 mainly aims to identify each time segment of the production time by the shale gas flow pattern identification method so as to remove the production data of the liquid discharge stage.
The shale gas flow state identification method adopts an β function method, and a β function is defined as:
in the formula (1), β represents a decreasing parameter without dimension, t represents production time in days, abbreviated as d, and q represents yield in 104m3/d。
When the shale gas formation flow shows linear flow or bilinear flow, the disordered production data before the generation time d corresponding to β in the log-log graph of the β parameter and the production time is the production data in the drainage stage.
Step S3: and removing the yield data of the liquid drainage stage, and creating yield data subsets of different production time periods for the yield data of the remaining linear flow stage and the boundary control flow stage, wherein the number of the yield data subsets is at least four, and the starting time of each yield data subset is the starting time of the linear flow.
The number of the divided output data subsets cannot be too small and is at least 4, so that the calculated recoverable reserves can be effectively fitted, the calculated recoverable reserves cannot be too many, the workload can be increased due to the excessive number of the output data subsets, and the number of the output data subsets is preferably 4-7.
Each subset of production data divided is counted from the time of the start of the linear stream.
Step S4: and drawing a log relation curve of daily gas production and time to construct a fitting model, fitting each yield data subset through a power exponential decreasing model, and summing the accumulated yield and the predicted yield of each yield data subset to obtain the upper limit value of the recoverable reserve of the shale gas well in each production time period.
The power exponent decreasing model is:
q(t)＝qiexp(-Ditn) (2)
in the formula (2), DiRepresenting a constant rate of decrease, d-1(ii) a n represents a decreasing index, dimensionless; q. q.siRepresenting the production at the beginning of the decrement in 104m3/d。
And predicting the yield of the shale gas well in each production time period through a power exponential decreasing model, and summing the accumulated yield and the predicted yield in each time period to obtain the upper limit value of the recoverable reserves of the shale gas well in each production time period, as shown in fig. 5, wherein fig. 5 shows the upper limit values of the recoverable reserves of the shale gas production wells predicted for production times of 200 days, 400 days, 600 days and 777 days respectively.
Step S5: drawing a rectangular coordinate relation graph of the accumulated yield and the daily gas production rate, establishing a daily gas production rate linear extrapolation model, and predicting the lower limit value of the recoverable reserve of the shale gas production well in each production time period through the daily gas production rate linear extrapolation model.
The linear extrapolation model of the daily gas production is as follows:
in the formula (3), DiDenotes constant rate of decrease, in d-1(ii) a q (t) represents daily gas production in 10 units4m3/d；qiRepresents the initial daily gas production with the unit of 104m3/d；Gp(t) represents the cumulative gas production in 104m3；
According to the formula (3), when q (t) → 0, Gp(t)→Gp,maxNamely: in q (t) to Gp(t) on the straight line, when q (t) is 0, the recoverable amount is Gp,maxHas a unit of 104m3。
Step S6: drawing the predicted upper limit value and lower limit value of the recoverable reserves and the time variable in the same rectangular coordinate, fitting the recoverable reserves in each production time period by using a depletion decreasing model, calculating until the upper limit value and the lower limit value of the recoverable reserves are not changed any more, and respectively obtaining the predicted upper limit value corresponding to the upper limit value of the recoverable reserves and the predicted lower limit value corresponding to the lower limit value of the recoverable reserves in each production time period.
The decline model is:
y＝Ae-x/B+ C, wherein A, B, C represents undetermined coefficients obtained by nonlinear regression fitting, and has no dimension and no range; y represents the recoverable reserve in units of 104m3(ii) a x represents time in units of d.
Step S7: and obtaining an interval between the upper prediction limit value and the lower prediction limit value of the recoverable reserves according to the upper prediction limit value and the lower prediction limit value of the recoverable reserves.
To facilitate understanding, the present invention is illustrated by a specific example.
Taking a shale gas well in the Sichuan basin as an example, the production time of the well is 777 days, the well is in the early production stage of the shale gas well, and the characteristic of bilinear flow of the well is obvious and is in a quasi-linear flow stage by drawing a log-log curve of β parameters and time, see figure 2. in addition, the early 60 days are main liquid drainage stages.
The current production data of the well is divided into four production time production data subsets, which are 61-200 days, 61-400 days, 61-600 days and 61-777 days respectively.
The upper limit values of the recoverable reserves of the four yield data subsets predicted by the power exponent decreasing model are respectively 2.17, 1.87, 1.85 and 1.83 multiplied by 108m3See fig. 3.
The lower limit values of the recoverable reserves of the four yield data subsets obtained by utilizing the daily yield linear extrapolation model are respectively 0.31, 0.76, 1.01 and 1.18 multiplied by 108m3See fig. 4.
Drawing the upper limit values of the recoverable reserves of the four yield data subsets obtained by the power exponential decrement model prediction and the lower limit values of the recoverable reserves of the four yield data subsets obtained by the daily gas production linear extrapolation model prediction in a relation graph of time and the recoverable reserves, referring to FIG. 5, respectively fitting two groups of data by using a depletion decrement model to ensure that the two groups of data are respectively converged to a stable recoverable reserve value,
in fig. 5, the box represents the upper limit of the recoverable amount of the sub-set of the yield data predicted by the power exponential decreasing model, and the circle represents the lower limit of the recoverable amount of the sub-set of the yield data predicted by the linear extrapolation model for the daily yield.
From fig. 5, it can be determined that the upper limit of the recoverable reserves of the well is 1.82 × 108m3Lower limit of 1.52X 108m3。
The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and all the changes or substitutions should be covered within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (5)
1. A method of predicting recoverable reserves of a shale gas well based on early production data, comprising:
step 1: obtaining yield data from the shale gas production well, filtering the yield data, and removing data points which do not accord with the overall change trend in the yield data;
step 2, identifying the production time of the filtered yield data according to a β function method in a β parameter and production time double logarithm diagram, wherein the production time comprises a liquid discharge stage, a linear flow stage and a boundary control flow stage;
and step 3: removing the yield data of the liquid drainage stage, and creating yield data subsets of different production time periods for the yield data of the remaining linear flow stage and the boundary control flow stage, wherein the number of the yield data subsets is at least four, and the starting time of each yield data subset is the starting time of the linear flow;
and 4, step 4: drawing a log-log relation curve of daily gas production and time to construct a fitting model, fitting each yield data subset through a power exponential decreasing curve, predicting the yield of the shale gas well in each production time period, and summing the accumulated yield and the predicted yield of each yield data subset to obtain an upper limit value of the recoverable reserves;
and 5: drawing a rectangular coordinate relation graph of the accumulated yield and the daily gas production rate, establishing a daily gas production rate linear extrapolation model, and predicting a lower limit value of the recoverable reserve of the shale gas well in each production time period through the daily gas production rate linear extrapolation model;
step 6: drawing the predicted upper limit value of the recoverable reserves, the predicted lower limit value of the recoverable reserves and the time variable in the same rectangular coordinate, fitting the recoverable reserves of each production time period by using a depletion decreasing model, calculating until the upper limit value and the lower limit value of the recoverable reserves are not changed any more, and respectively obtaining a predicted upper limit value corresponding to the upper limit value of the recoverable reserves and a predicted lower limit value corresponding to the lower limit value of the recoverable reserves in each production time period;
and 7: and obtaining the interval between the upper prediction limit value and the lower prediction limit value of the recoverable reserves according to the upper prediction limit value and the lower prediction limit value of the recoverable reserves.
2. The method for predicting recoverable reserves of shale gas wells based on early production data as claimed in claim 1, wherein the β function in the β function is defined as:
in the formula (1), β represents a decreasing parameter without dimension, T represents production time in days, abbreviated as T, and q represents yield in 104m3/T；
When the shale gas formation flow shows linear flow or bilinear flow, the disordered production data before the production time T corresponding to β in the double-logarithm diagram of the β parameter and the production time is the production data in the drainage stage.
3. The method of predicting recoverable reserves of shale gas wells based on early production data as claimed in claim 1 wherein the power exponential decay model is:
q(t)＝qiexp(-Ditn) (2)
in the formula (2), q (t) represents daily gas production, t represents production time in days, DiRepresenting a constant rate of decrease, T-1(ii) a n represents a decreasing index, dimensionless; q. q.siRepresenting the production at the beginning of the decrement in 104m3/T。
4. The method for predicting recoverable reserves of shale gas wells based on early production data as claimed in claim 1 wherein the linear extrapolation model for daily gas production is:
in the formula (3), DiRepresents a constant rate of decrease in units of T-1(ii) a q (t) represents daily gas production in 10 units4m3/T；qiRepresents the initial daily gas production with the unit of 104m3/T；Gp(t) represents the cumulative gas production in 104m3(ii) a T represents the production time in days.
5. The method of predicting recoverable reserves of shale gas wells based on early production data as claimed in claim 1 wherein the depletion diminishing model is:
y＝Ae-x/B+ C, wherein A, B, C each represents a pending coefficient obtained by nonlinear regression fitting; y represents the recoverable reserve in units of 104m3(ii) a x represents time in days.
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