CN116976519A - Shale oil reservoir single well recoverable reserve prediction method and system - Google Patents
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Abstract
The invention discloses a shale oil reservoir single well recoverable reserve prediction method and a shale oil reservoir single well recoverable reserve prediction system, and relates to the technical field of shale oil exploitation, wherein the method comprises the following steps: obtaining the type of the single well of the shale oil reservoir to be predicted according to the initial productivity and the progressive rate of the single well of the shale oil reservoir to be predicted after entering the progressive period; the type comprises a high-yield rapid decreasing type, a medium-yield decreasing type, a low-yield rapid decreasing type and a low-yield stable type; obtaining a combination decreasing model corresponding to the single well of the shale oil deposit to be predicted according to the type of the single well of the shale oil deposit to be predicted; the combination decreasing model comprises a SEPD+FDC combination model, a PLE+FDC combination model and a Duong+FDC combination model; and calculating the recoverable reserves of the single well of the shale oil deposit to be predicted by using the combined decreasing model to obtain the recoverable reserves of the single well of the shale oil deposit to be predicted. The invention can realize accurate prediction of the final recoverable reserve of a single well.
Description
Technical Field
The invention relates to the technical field of shale oil exploitation, in particular to a shale oil reservoir single well recoverable reserve prediction method and system.
Background
The research of shale oil reservoirs has become a hot research topic, and the output and recoverable reserve prediction of shale oil and gas wells directly influences the feasibility risk analysis and the final economic evaluation result of oil and gas exploitation. The comprehensive cost of a single well and the final recovery amount of the single well are important indexes for evaluating the economical efficiency of shale oil and gas. Accurately obtaining (predicting) the final recoverable reserves of shale oil gas single wells is the basis of research.
The three methods for evaluating shale oil and gas productivity (comprising yield prediction and the like) are commonly used at present: typical curve method (DCA) based on production dynamic data; simplified analysis method based on seepage mechanism; and (3) a numerical simulation method for considering mechanisms such as reservoir and fluid complexity factors, seepage, desorption and the like.
The simplified analysis method based on the seepage mechanism and the numerical simulation method considering the complex factors of the reservoir and the fluid, the seepage, desorption and other mechanisms are used for realizing yield prediction based on analysis solution, semi-analysis solution or numerical solution of an accurate reservoir model. Reasonable yield predictions can be achieved based on analytical, semi-analytical, or numerical solutions of the accurate reservoir model. However, in order to build such a complex reservoir model, petrophysical experiments need to be performed because a large amount of petrophysical data needs to be collected and analyzed before it is applied to the reservoir model. For example, to obtain the inputs required for a reservoir model (e.g., formation location, depth, resistivity, permeability, fracture properties), a well test needs to be drilled and multiple well logging processes performed. These processes are expensive and time consuming, and some logging techniques are not sensitive enough to measure the multi-scale properties of shale. In contrast, DCA requires only production data and little reservoir information, and this method is efficient with sufficient accuracy to meet industry needs.
By determining the applicability of the decreasing model in shale oil reservoirs, it is necessary to improve the decreasing fitting precision and the prediction accuracy. The calculation of the final recoverable reserves by fully utilizing the production data is an indispensable part of reserve evaluation work, and has important significance for comprehensively evaluating oil and gas fields and establishing the basis of oil and gas development. Therefore, it is very necessary to predict the yield using the production data.
The yield-decreasing prediction (DCA is one of the methods of yield-decreasing prediction) includes a number of methods such as a numerical method (i.e., a numerical simulation method that considers reservoir and fluid complications and mechanisms such as seepage and desorption), an analytical method (i.e., a simplified analytical method based on a seepage mechanism), and an empirical model (i.e., an analytical solution, a semi-analytical solution, or a numerical solution based on an accurate reservoir model to implement yield-decreasing prediction), and the main purpose is to predict well yield and recoverable reserves (final recoverable reserves). The current numerical methods and analytical methods are capable of accurately predicting well production and reserves, however, the two methods are not always applicable due to difficulty in accurately obtaining reservoir parameters, complex reservoir mechanisms and high operation difficulty.
The decreasing curve analysis method (DCA) focuses on the observed production of a single well or a group of wells by mathematical function fitting, and future production is predicted by extrapolating the fitted decreasing curve function. The empirical model method (DCA is predicted by some models) only needs to simply calculate and fit production data, has simple and convenient operation and reliable prediction results, and is still widely used.
However, there is also a difference in the adaptability of the yield-decreasing model for different shale oil production wells due to differences in geologic background and development patterns. Currently, there is still a lack of yield decreasing models (DCA is predicted by different models) for different blocks to match. DCA aims to exploit the interrelationship between data to achieve easy extrapolation predictions, while also being useful for predicting recoverable reserves at a particular production waste.
The invention discloses a method for rapidly predicting economic recoverable reserves of a low-permeability dense oil reservoir, which comprises the following steps of:
s1: sequentially arranging oil well production data in Excel according to the production time after well opening, daily oil production, accumulated oil production, oil nozzle caliber and wellhead oil pressure;
s2: independently making a daily oil yield curve graph, a choke caliber curve and a wellhead oil pressure curve graph according to the production time after well opening in a Cartesian coordinate system by using Excel, so that the starting and stopping time of the abscissa of each curve graph are identical, and the lengths of the abscissa are identical;
s3: the three graphs are longitudinally arranged, the starting and stopping time of each graph is guaranteed to be consistent, a data segment which simultaneously meets the conditions that the caliber of a choke is kept unchanged, the oil pressure change of a wellhead is gentle and the oil yield is steadily decreased is selected as a target data segment, the step aims to avoid the influence of the working system change of an oil well and the fracturing interference of a temporary well on the decreasing rule of the target data segment, and the number of days of the target data segment is required to be guaranteed to be greater than 200 days;
s4: recording daily oil production data of the last 100 days in the target data segment screened in the step S3 as prediction result verification data, and recording the rest data in the target data segment as model fitting data;
s5: respectively adopting a power exponent decrementing model, namely a PLE model and an extension exponent decrementing model, namely a SEDM model and a Duong decrementing model, namely a Duong model and a Matthews-Leflcovis decrementing model, namely an ML model, and fitting model fitting data selected in the step S4 by using a total of 4 unconventional oil and gas reservoir experimental yield decrementing models to obtain respective model parameters;
s6: calculating the deviation coefficient beta of the 4 unconventional oil and gas reservoir tested yield decreasing models in the step S5 by combining model fitting data and prediction result verification data, wherein the model corresponding to the minimum deviation coefficient is the optimal decreasing model which is optimized;
s7: calculating the time from the fitting start time to the time when the daily oil yield of the oil well reaches the economic abandoned daily oil yield by adopting the optimal decreasing model selected in the step S6The accumulated oil production Ns, plus the accumulated oil production N before the start of the fitting 0 I.e. Ne=Ns+N, the economically producible reserves of oil wells 0 。
The patent uses four decreasing models (each decreasing model is a decreasing yield model) to fit the well alone, and cannot describe the long "tailing" phenomenon of the shale well later, namely the inaccuracy of the later data fitting. The shale oil well is different in decrementing stage, the early stage and the later stage are different greatly, and a combined decrementing model should be used.
Four decreasing models are needed to fit each well, the models are optimized after the fitting degree is optimized, the calculation steps are more, and the workload is high.
The decreasing model recently proposed by researchers for unconventional reservoirs is mainly: power law index decrementing, SEPD decrementing, and Duong index decrementing models.
The power law exponential decay model (PLE) was proposed by ILK et al to describe the decreasing production at the stages of shale well unstable flows, transitional flows, and boundary flows. The model carries out intensive research on the mathematical change relation between the reduction rate and time, and provides a new mathematical expression of the reduction rate change, which can be fit to any flowing stage of the production well. Compared with a hyperbolic decreasing model, the model has higher calculation reserve accuracy.
The model requires a constant or approximately constant bottom hole pressure. The model adopts a variable decremental index:
D＝D ∞ +D i t -(1-n) (1)
wherein: d is the rate of decrease, D -1 The method comprises the steps of carrying out a first treatment on the surface of the n is a time index; d (D) i For the first time period, corresponding to the rate of decrease, d -1 . As can be seen from the above equation, D can be approximated as a constant D because the power law term does not contribute much after a long production time ∞ . The PLE decremental model has the expression:
(2) The spread index decreasing model (SEPD) was developed by Valko from production data of 7000 wells of Barnrtt shale in north america. The SEPD model introduces a time constant based on the PLE model and comprehensively analyzes some factors related to yield.
Wherein: n is a dimensionless time index; τ is the characteristic relaxation time of the model, d. Daily yield can be expressed as:
wherein: q i For decreasing stage maximum actual daily output, m 3 /d。
(3) Duong proposes a Duong index decreasing model based on the characteristic of linear flow dynamics of the United states shale gas well production state exhibiting cracking for a long period of time. The Duong model is mainly applicable to fracture type shale oil and gas reservoirs.
Based on predictions of empirical parameters, single well production is considered to exhibit a linear flow regime of frailty during the production cycle. Meanwhile, the model shows that the cumulative oil and gas yield and time are in a linear relation under a double-logarithmic coordinate, and the yield of the fractured shale oil and gas reservoir can be predicted with high precision.
Duong proposed:
wherein: m is a power function exponent of decreasing time; a is a decreasing coefficient, d -1 The method comprises the steps of carrying out a first treatment on the surface of the t is a time function of daily output; q i To decrease the initial daily yield, m 3 /d。
(4) In view of the common long tail behavior of both shale well production data and anomalous diffusion phenomena, zuo et al (2016) propose a new score decreasing curve model (FDC), as shown in the equation. With three fitting parameters, a general solution of the fractional diffusion equation is used as a special case of the so-called Mittag-lefler function. They further simplified the FDC as shown by the equation and proposed a four-step scheme to quantify these three parameters based on the asymptotic nature of the Mittag-Leffler function. They validated FDCs according to a numerical reservoir model and successfully applied FDCs to historical fits and production predictions for five actual shale gas wells of feiter shale.
Wherein: λ is the eigenvalue, α is the fitting coefficient, dimensionless, Γ (t) is the gamma function.
All four models have drawbacks. PLE models have multiple solutions in their solution process, and it is difficult to fit cumulative and daily yields simultaneously. The SEPD decremental model is applicable to both unstable and transitional stream production phases. The predicted result of the Duong model is more accurate when the well is in a slow decreasing stage, but the predicted result is larger and is influenced by data fluctuation when the production time is shorter. The FDC model is only suitable for the stage with low taper rate (i.e. the second stage of a well is predicted, and each well is divided into a front stage and a rear stage by two models), and is not suitable for the unstable flow production stage. As a specific technical means adopted in the recoverable reserve prediction method, the model has the defect that the predicted result of the recoverable reserve prediction method is inaccurate and has a large difference from a true value.
The different geological background and development modes of shale oil wells lead to different well production characteristics, so the adaptability of the yield-decreasing model is also different. At present, a yield decreasing model matched with well production characteristics is lacking, so that accurate prediction of the final recoverable reserves of a single well cannot be realized.
Disclosure of Invention
The invention aims to provide a method and a system for predicting the single well recoverable reserves of a shale oil reservoir, which can realize accurate prediction of the final recoverable reserves of the single well.
In order to achieve the above object, the present invention provides the following solutions:
a shale reservoir single well recoverable reserve prediction method, the method comprising:
obtaining the type of the single well of the shale oil reservoir to be predicted according to the initial productivity and the progressive rate of the single well of the shale oil reservoir to be predicted after entering the progressive period; the type comprises a high-yield rapid decreasing type, a medium-yield decreasing type, a low-yield rapid decreasing type and a low-yield stable type;
obtaining a combination decreasing model corresponding to the single well of the shale oil deposit to be predicted according to the type of the single well of the shale oil deposit to be predicted; the combination decreasing model comprises a SEPD+FDC combination model, a PLE+FDC combination model and a Duong+FDC combination model;
and calculating the recoverable reserves of the single well of the shale oil deposit to be predicted by using the combined decreasing model to obtain the recoverable reserves of the single well of the shale oil deposit to be predicted.
Optionally, obtaining the type of the single well of the shale oil reservoir to be predicted according to the initial productivity and the progressive rate after the single well of the shale oil reservoir to be predicted enters the progressive period, which specifically comprises the following steps:
when the initial productivity of the shale oil reservoir single well to be predicted after entering the decreasing period is more than 15 tons/day, the decreasing rate is more than 0.20 month -1 When the type of the shale oil reservoir single well to be predicted is high-yield rapid decreasing type;
when the initial productivity of the shale oil reservoir single well to be predicted after entering the decreasing period is 10-20 tons/day, the decreasing rate is 0.10-0.20 month -1 When the type of the shale oil reservoir single well to be predicted is a medium-yield decreasing type;
when the initial productivity of the single well of the shale oil reservoir to be predicted enters the decreasing period is less than 15 tons/day, and the decreasing rate is more than 0.20 month -1 When the type of the shale oil reservoir single well to be predicted is low-yield rapid decreasing type;
when the initial productivity of the single well of the shale oil reservoir to be predicted enters the decreasing period is more than 15 tons/day,The taper rate is less than 0.10 month -1 When the shale oil reservoir single well type to be predicted is low-yield stable-yield type.
Optionally, according to the type of the single well of the shale oil deposit to be predicted, obtaining a corresponding combination decreasing model of the single well of the shale oil deposit to be predicted specifically includes:
when the type of the shale oil reservoir single well to be predicted is a high-yield rapid decreasing type or a low-yield rapid decreasing type, the corresponding combination decreasing model of the shale oil reservoir single well to be predicted is a PLE+FDC combination model;
when the type of the single well of the shale oil reservoir to be predicted is a middle-yield decreasing type, the corresponding combination decreasing model of the single well of the shale oil reservoir to be predicted is an SEPD+FDC combination model;
when the type of the single well of the shale oil deposit to be predicted is low-yield stable-yield type, the corresponding combination decreasing model of the single well of the shale oil deposit to be predicted is a Duong+FDC combination model.
Optionally, calculating the recoverable reserves of the single well of the shale oil reservoir to be predicted by using the combined decreasing model to obtain the recoverable reserves of the single well of the shale oil reservoir to be predicted, which specifically comprises the following steps:
when the PLE+FDC combined model is used for carrying out the recoverable reserve calculation on the single well of the shale oil deposit to be predicted, the single well of the shale oil deposit to be predicted is formed into a combined decreasing model through the PLE model in one stage and the FDC model in the second stage of the shale oil deposit to be predicted Shan Jingdi, so that the recoverable reserve of the single well of the shale oil deposit to be predicted is obtained;
when the SEPD+FDC combined model is used for carrying out the recoverable reserve calculation on the single well of the shale oil deposit to be predicted, the single well of the shale oil deposit to be predicted is formed into a combined decreasing model through the SEPD model in one stage and the FDC model in the second stage of the shale oil deposit Shan Jingdi to be predicted, and the recoverable reserve of the single well of the shale oil deposit to be predicted is obtained;
when the Duong+FDC combined model is used for carrying out the recoverable reserve calculation on the single well of the shale oil deposit to be predicted, the recoverable reserve calculation is carried out on the single well of the shale oil deposit to be predicted by the Duong model in one stage and the FDC model in the second stage to form a combined decreasing model, so that the recoverable reserve of the single well of the shale oil deposit to be predicted is obtained.
Optionally, the calculating the recoverable reserves of the single well of the shale oil reservoir to be predicted by using the PLE+FDC combined model specifically comprises the following steps:
calculating the daily output of the first stage of the model by using the PLE model;
calculating a model first-stage cumulative yield according to the model first-stage daily yield;
calculating the daily output of the second stage of the model by using the FDC model;
and adding the daily output of the first stage of the model and the daily output of the second stage of the model to obtain the recoverable reserve of the single well of the shale oil reservoir to be predicted.
Optionally, the calculating the recoverable reserves of the single well of the shale oil reservoir to be predicted by using the SEPD+FDC combined model specifically comprises the following steps:
calculating the daily output of the first stage of the model by using the SEPD model;
calculating a model first-stage cumulative yield according to the model first-stage daily yield;
calculating the daily output of the second stage of the model by using the FDC model;
and adding the daily output of the first stage of the model and the daily output of the second stage of the model to obtain the recoverable reserve of the single well of the shale oil reservoir to be predicted.
Optionally, the calculating the recoverable reserves of the single well of the shale oil reservoir to be predicted by using the Duong+FDC combination model specifically comprises the following steps:
calculating the daily output of the model in the first stage by using the Duong model;
calculating a model first-stage cumulative yield according to the model first-stage daily yield;
calculating the daily output of the second stage of the model by using the FDC model;
and adding the daily output of the first stage of the model and the daily output of the second stage of the model to obtain the recoverable reserve of the single well of the shale oil reservoir to be predicted.
Optionally, obtaining the type of the single well of the shale oil reservoir to be predicted according to the initial productivity and the progressive rate after the single well of the shale oil reservoir to be predicted enters the progressive period, and further including:
acquiring abnormal points which do not accord with a decreasing rule in the production process and points with zero gas production;
and deleting abnormal points which do not accord with the decreasing rule and points with zero gas production in the production process, reducing corresponding production days, and acquiring initial capacity and decreasing rate of the shale oil reservoir single well to be predicted after the shale oil reservoir single well to be predicted enters the decreasing period.
The invention also provides the following scheme:
a shale reservoir single well recoverable reserves prediction system, the system comprising:
the shale oil reservoir single well type determining module is used for obtaining the type of the shale oil reservoir single well to be predicted according to the initial productivity and the progressive rate of the shale oil reservoir single well to be predicted after entering the progressive period; the type comprises a high-yield rapid decreasing type, a medium-yield decreasing type, a low-yield rapid decreasing type and a low-yield stable type;
the combination decreasing model determining module is used for obtaining a combination decreasing model corresponding to the single well of the shale oil deposit to be predicted according to the type of the single well of the shale oil deposit to be predicted; the combination decreasing model comprises a SEPD+FDC combination model, a PLE+FDC combination model and a Duong+FDC combination model;
and the recoverable reserves calculating module is used for calculating recoverable reserves of the single shale oil reservoir well to be predicted by utilizing the combined decreasing model to obtain recoverable reserves of the single shale oil reservoir well to be predicted.
Optionally, the system further comprises:
the abnormal point and gas production amount zero point acquisition module is used for acquiring abnormal points which do not accord with a decreasing rule in the production process and points with gas production amount zero;
the initial productivity and progressive rate obtaining module is used for deleting abnormal points which do not accord with the progressive rule in the production process and points with zero gas production, reducing corresponding production days, and obtaining the initial productivity and progressive rate of the shale oil reservoir single well to be predicted after the shale oil reservoir single well to be predicted enters the progressive period.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects:
according to the method and the system for predicting the recoverable reserves of the single shale oil deposit well, the type of the single shale oil deposit well is obtained according to the initial productivity and the progressive reduction rate of the single shale oil deposit well after entering the progressive reduction period, and according to the type of the single shale oil deposit well, the recoverable reserves of the single shale oil deposit well is calculated by using the SEPD+FDC combined model, the PLE+FDC combined model and the Duong+FDC combined model, wherein the recoverable reserves of the single shale oil deposit well are calculated by using the progressive reduction model, the recoverable reserves are predicted by adopting the DCA method, the FDC model is introduced for common tailing phenomena of a horizontal well, the progressive reduction later stage of the shale oil well can be fitted better, and the method is based on the three proposed combined progressive reduction models: the method comprises the steps of classifying shale oil wells according to descending conditions, calculating single-well recoverable reserves by using proper descending models of different types of shale oil wells, calculating the recoverable reserves of the single well, wherein the calculation steps are simple and the required parameters are fewer, and the effect of matching and adapting the combined descending models according to the induced production characteristics to the reservoir production characteristics can be achieved, so that the descending fitting precision and the prediction accuracy are improved, and the effect of predicting the recoverable reserves of the single well in a simple and accurate manner is achieved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are needed in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a first embodiment of a shale reservoir single well recoverable reserve prediction method of the present invention;
FIG. 2 is a block diagram of a second embodiment of a shale reservoir single well recoverable reservoir prediction system of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The invention aims to provide a method and a system for predicting the single well recoverable reserves of a shale oil reservoir, which can realize accurate prediction of the final recoverable reserves of the single well.
In order that the above-recited objects, features and advantages of the present invention will become more readily apparent, a more particular description of the invention will be rendered by reference to the appended drawings and appended detailed description.
First, some terms of art related to the present invention will be specifically described:
DCA: decline curve analysis, a decreasing curve analysis method, which is an empirical method of production data matching and prediction, involves fitting a decreasing trend of the curve.
PLE: power law exponential, the power law index decreases.
SEPD: stretched Exponential Production Decline, the extensibility index decreases.
FDC: fractional decline curve, score decreasing curve.
Example 1
FIG. 1 is a flow chart of a first embodiment of a shale reservoir single well recoverable reserve prediction method of the present invention. As shown in FIG. 1, the invention provides a shale oil reservoir single well recoverable reserve prediction method, which comprises the following steps:
step S1: obtaining the type of the single well of the shale oil reservoir to be predicted according to the initial productivity and the progressive rate of the single well of the shale oil reservoir to be predicted after entering the progressive period; the types include high-yield rapid decrease type, medium-yield decrease type, low-yield rapid decrease type and low-yield stable type.
The step S1 specifically includes:
when the initial productivity of the shale oil reservoir single well to be predicted after entering the decreasing period is more than 15 tons/day, the decreasing rate is more than 0.20 month -1 When the type of the shale oil reservoir single well to be predicted is high-yield rapid decreasing type.
When shale reservoir Shan Jingjin is to be predictedThe initial productivity after the decreasing period is 10-20 tons/day, and the decreasing rate is 0.10-0.20 month -1 And when the type of the shale oil reservoir single well to be predicted is a medium-yield decreasing type.
When the initial productivity of the single well of the shale oil reservoir to be predicted enters the decreasing period is less than 15 tons/day, and the decreasing rate is more than 0.20 month -1 When the type of the shale oil reservoir single well to be predicted is low-yield rapid decreasing type.
When the initial productivity of the shale oil reservoir single well to be predicted after entering the decreasing period is more than 15 tons/day, and the decreasing rate is less than 0.10 month -1 When the shale oil reservoir single well type to be predicted is low-yield stable-yield type.
This step 101 is preceded by:
and acquiring abnormal points which do not accord with the decreasing rule in the production process and points with zero gas production.
And deleting abnormal points which do not accord with the decreasing rule and points with zero gas production in the production process, reducing corresponding production days, and acquiring initial capacity and decreasing rate of the shale oil reservoir single well to be predicted after the shale oil reservoir single well to be predicted enters the decreasing period.
Step S2: obtaining a combination decreasing model corresponding to the single well of the shale oil deposit to be predicted according to the type of the single well of the shale oil deposit to be predicted; the combination decreasing model includes a SEPD+FDC combination model, a PLE+FDC combination model, and a Duong+FDC combination model.
The step S2 specifically includes:
when the type of the shale oil reservoir single well to be predicted is high-yield rapid decrease type or low-yield rapid decrease type, the corresponding combination decrease model of the shale oil reservoir single well to be predicted is PLE+FDC combination model.
When the type of the single well of the shale oil reservoir to be predicted is the middle-yield decreasing type, the corresponding combination decreasing model of the single well of the shale oil reservoir to be predicted is an SEPD+FDC combination model.
When the type of the single well of the shale oil deposit to be predicted is low-yield stable-yield type, the corresponding combination decreasing model of the single well of the shale oil deposit to be predicted is a Duong+FDC combination model.
Step S3: and calculating the recoverable reserves of the single well of the shale oil reservoir to be predicted by using the combined decreasing model to obtain the recoverable reserves of the single well of the shale oil reservoir to be predicted.
The step S3 specifically includes:
when the PLE+FDC combined model is used for carrying out the recoverable reserve calculation on the single well of the shale oil deposit to be predicted, the recoverable reserve calculation is carried out on the single well of the shale oil deposit to be predicted by a combined decreasing model formed by the PLE model in one stage and the FDC model in the second stage of the shale oil deposit Shan Jingdi to be predicted, and the recoverable reserve of the single well of the shale oil deposit to be predicted is obtained.
When the SEPD+FDC combined model is used for carrying out the recoverable reserve calculation on the single well of the shale oil deposit to be predicted, the recoverable reserve calculation on the single well of the shale oil deposit to be predicted is carried out by forming a combined decreasing model through the SEPD model in one stage and the FDC model in the second stage of the shale oil deposit Shan Jingdi to be predicted, and the recoverable reserve of the single well of the shale oil deposit to be predicted is obtained.
When the Duong+FDC combined model is used for carrying out the recoverable reserve calculation on the single well of the shale oil deposit to be predicted, the recoverable reserve calculation is carried out on the single well of the shale oil deposit to be predicted by the Duong model in one stage and the FDC model in the second stage to form a combined decreasing model, so that the recoverable reserve of the single well of the shale oil deposit to be predicted is obtained.
The method for calculating the recoverable reserves of the single well of the shale oil reservoir to be predicted by using the PLE+FDC combined model specifically comprises the following steps:
the PLE model was used to calculate the model first stage daily yield.
And calculating the first-stage accumulated yield of the model according to the first-stage daily yield of the model.
The FDC model is used to calculate the daily output of the second stage of the model.
And adding the daily output of the first stage of the model and the daily output of the second stage of the model to obtain the recoverable reserve of the single well of the shale oil reservoir to be predicted.
Calculating the recoverable reserves of a single well of the shale oil reservoir to be predicted by using the SEPD+FDC combined model, wherein the method specifically comprises the following steps of:
the SEPD model was used to calculate the model first stage daily yield.
And calculating the first-stage accumulated yield of the model according to the first-stage daily yield of the model.
The FDC model is used to calculate the daily output of the second stage of the model.
And adding the daily output of the first stage of the model and the daily output of the second stage of the model to obtain the recoverable reserve of the single well of the shale oil reservoir to be predicted.
The method for calculating the recoverable reserves of the single well of the shale oil reservoir to be predicted by using the Duong+FDC combined model specifically comprises the following steps:
the first stage daily yield of the model was calculated using the Duong model.
And calculating the first-stage accumulated yield of the model according to the first-stage daily yield of the model.
The FDC model is used to calculate the daily output of the second stage of the model.
And adding the daily output of the first stage of the model and the daily output of the second stage of the model to obtain the recoverable reserve of the single well of the shale oil reservoir to be predicted.
The technical scheme of the invention is described in the following by a specific embodiment:
the invention provides an optimization process of a single-well recoverable reserve prediction method of a shale oil reservoir, which comprises the following steps: the wells (shale oil wells) are divided into A, B, C according to the initial productivity and the reduction rate change of the shale oil single well (shale oil reservoir single well) 1 And C 2 The high-yield rapid decrease type, the medium-yield decrease type, the low-yield rapid decrease type and the low-yield stable type. And (3) formulating a single well recoverable reserve calculation flow for four types of wells. The first phase consisted of a combined model (combined decreasing model) with the SEPD, duong and PLE models and the second phase consisted of an FDC model, fitting a production curve to a single well and calculating recoverable reserves. The method for predicting the single well recoverable reserves of the shale oil reservoir specifically comprises the following steps:
step 101: in combination with actual shale oil production data, the wells are divided into A, B, C according to table 1 according to the initial capacity and the rate of decline after the well enters the decline period 1 And C 2 The categories are high-yield rapid decrease type, medium-yield decrease type, low-yield rapid decrease type and low-yield stable type.
TABLE 1 Classification criteria
Step 102: during the production process, external factors such as fracturing, water injection and the like may cause abnormal points which do not conform to the decreasing rule. Furthermore, there may be some points in the production process where the gas production is zero due to shut-in or other reasons. To ensure the quality of the production data and to increase the accuracy of the prediction of the decreasing model, it is necessary to exclude these outliers (the points with value 0 are deleted and the corresponding production days are reduced). The calculation is performed after the shale well (shale reservoir individual well) enters the decrement period.
Step 103: after the abnormal points are removed, judgment and classification are performed according to the step 101.
If the well type is A or C 1 Class, then we shall use ple+fdc combined decreasing model (ple+fdc combined model):
first, ln (q/q) is plotted by well data (including date, daily oil production, initial daily oil production) i ) A hyperbolic curve with time (time function corresponding to daily output) t, i.e. a curve with intercept a and slope n; then D i ＝e A N; the time is cut off to the time of the combination point (the time point of the combination, namely the time point of the production curve entering the long tail, the long tail stage can be defined as the stage of decreasing the decreasing rate to below 5%), and the daily output of the first stage of the model can be calculated by the formula (9).
In the formula (9) and the formula (10): q is the daily output of the model in the first stage, and the unit is m 3 /d，q i To decrease the initial daily yield in m 3 /d；q j For daily output corresponding to the jth time point of the first stage, unit m 3 /d; n is time fingerA number (the value of n is obtained by the slope), e is a natural constant; n (N) p1 For the first stage cumulative yield (model first stage cumulative yield), unit m 3 The method comprises the steps of carrying out a first treatment on the surface of the z is the combined point time, unit d; j is a positive integer; d (D) ∞ Taking 0 for infinite reduction rate, unit d -1 ；D i For initial rate of decrease, unit d -1 。
If the well type is class B, a sepd+fdc combination decreasing model (sepd+fdc combination model) should be used:
first, ln (q/q i ) A double logarithmic curve with time t, namely a curve with an intercept of A and a slope of n; thenThe time is cut off to the time of the combination point, and the daily output q of the first stage of the model can be calculated by the formula (11). The accumulated yield N of the first stage of the model can be calculated by the formula (10) p1 。
In formula (11): q i To decrease the initial daily yield in m 3 /d; n is a dimensionless time index (the value of n is derived by slope); τ is the characteristic relaxation time of the model, unit d; t is a time function of daily output.
If the well type is C 2 Class, then the Duong+FDC model (Duong+FDC combined model) should be utilized:
first, ln (q/G) p ) A) curve of =a-m· lnt (curve intercept a, slope n). A=e A And is also provided withDrawing rectangular coordinate curves of q and t (a, m) to obtain q i . The time is cut off to the time of the combination point, and the daily output q of the first stage of the model can be calculated by the formula (12). The accumulated yield N of the first stage of the model can be calculated by the formula (10) p1 。
In formula (12): q i To decrease the initial daily yield in m 3 /d; m is a power function exponent of decreasing time; a is a decreasing coefficient, unit d -1 The method comprises the steps of carrying out a first treatment on the surface of the t is a time function of daily output; g p Representing the cumulative yield.
Step 104: the cumulative yield of the first stage (model first stage cumulative yield) and the yield q of the combined time point model can be calculated by step 103 i (i.e., using the last day yield of the first stage as the initial yield of the model after the combining point), log (q i /q) and log (t), q i The hyperbolic curve of/q and t is a straight line, the slope is α, the intercept is a, a=log (λ·Γ (1- α)), and λ can be obtained from the slope and the intercept. The daily output q of the second stage of the model can be calculated by the formula (13), and the time is cut off from the output to the lowest limit daily oil production of a single well. The second-stage cumulative yield (model second-stage cumulative yield) calculated from equation (14) is N p2 。
In the formulas (13) and (14): q i To decrease the initial daily yield in m 3 /d; j is a positive integer; q j Daily output corresponding to the j-th time point of the second stage; t is a time function of daily output; λ is the eigenvalue, α is the fitting coefficient, dimensionless, and f (t) is the gamma function. N (N) p2 For the second stage cumulative yield, unit m 3 The method comprises the steps of carrying out a first treatment on the surface of the z is the combined point time; z 1 The end time of the decrementing period, i.e., the daily yield, is the discard yield time point, unit d.
Equation (13) is the FDC model. After each well classification, the early stage (first stage) was combined with one of the SEPD, PLE and dunng models, and the later stage (second stage) was combined with the FDC model.
Step 105: the final recoverable reserve of the well (recoverable reserve of a shale oil reservoir single well) is the sum of the results of equation (10) and equation (14), namely N p1 +N p2 。
Aiming at the common tailing phenomenon of a horizontal well, the invention introduces an FDC model, can better fit the descending later stage of a shale oil well (a shale oil reservoir single well), is based on the current DCA method for the shale oil reservoir with less research, and provides three combined descending models which are more suitable for the shale oil well through the fit comparison of at least 100 shale oil wells: the SEPD+FDC combined model, the PLE+FDC combined model and the Duong+FDC combined model are used for classifying the wells according to the descending conditions, and the suitable descending models of different types of wells are used for calculating the single-well recoverable reserves, so that the calculation steps are simple and the required parameters are fewer.
Compared with the prior art, the invention has the advantages that:
1. dividing the wells into A, B, C according to the initial productivity and the decline rate of the shale oil single well 1 And C 2 The high-yield rapid decrease type, the medium-yield decrease type, the low-yield rapid decrease type and the low-yield stable type.
2. And (3) establishing a single well recoverable reserve calculation flow for four types of wells, wherein the first stage of each type of well is formed into a combined model through SEPD, duong and PLE models, and the second stage of each type of well is formed into a combined model through FDC models, namely one model of the FDC models and SEPD, PLE, duong is combined, and the recoverable reserve calculation is carried out on the single well.
Example two
In order to execute the corresponding method of the embodiment to realize the corresponding functions and technical effects, the invention also provides a shale oil reservoir single well recoverable reserve prediction system, as shown in fig. 2, which comprises the following modules:
the shale oil reservoir single well type determining module 201 is configured to obtain a type of a shale oil reservoir single well to be predicted according to an initial productivity and a progressive rate of the shale oil reservoir single well to be predicted after entering a progressive period; the types include high-yield rapid decrease type, medium-yield decrease type, low-yield rapid decrease type and low-yield stable type.
The combination decreasing model determining module 202 is configured to obtain a combination decreasing model corresponding to the single well of the shale oil reservoir to be predicted according to the type of the single well of the shale oil reservoir to be predicted; the combination decreasing model includes a SEPD+FDC combination model, a PLE+FDC combination model, and a Duong+FDC combination model.
And the recoverable reserves calculating module 203 is configured to calculate recoverable reserves of the single shale oil reservoir well to be predicted by using the combined decreasing model, so as to obtain recoverable reserves of the single shale oil reservoir well to be predicted.
Specifically, the system further comprises:
the abnormal point and the point acquisition module with zero gas production are used for acquiring abnormal points which do not accord with the decreasing rule in the production process and points with zero gas production.
The initial productivity and progressive rate obtaining module is used for deleting abnormal points which do not accord with the progressive rule in the production process and points with zero gas production, reducing corresponding production days, and obtaining the initial productivity and progressive rate of the shale oil reservoir single well to be predicted after the shale oil reservoir single well to be predicted enters the progressive period.
In the present specification, each embodiment is described in a progressive manner, and each embodiment is mainly described in a different point from other embodiments, and identical and similar parts between the embodiments are all enough to refer to each other. For the system disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant points refer to the description of the method section.
The principles and embodiments of the present invention have been described herein with reference to specific examples, the description of which is intended only to assist in understanding the methods of the present invention and the core ideas thereof; also, it is within the scope of the present invention to be modified by those of ordinary skill in the art in light of the present teachings. In view of the foregoing, this description should not be construed as limiting the invention.
Claims (10)
1. A shale reservoir single well recoverable reserve prediction method, the method comprising:
obtaining the type of the single well of the shale oil reservoir to be predicted according to the initial productivity and the progressive rate of the single well of the shale oil reservoir to be predicted after entering the progressive period; the type comprises a high-yield rapid decreasing type, a medium-yield decreasing type, a low-yield rapid decreasing type and a low-yield stable type;
obtaining a combination decreasing model corresponding to the single well of the shale oil deposit to be predicted according to the type of the single well of the shale oil deposit to be predicted; the combination decreasing model comprises a SEPD+FDC combination model, a PLE+FDC combination model and a Duong+FDC combination model;
and calculating the recoverable reserves of the single well of the shale oil deposit to be predicted by using the combined decreasing model to obtain the recoverable reserves of the single well of the shale oil deposit to be predicted.
2. The method for predicting the recoverable reserves of the single shale oil deposit well according to claim 1, wherein the obtaining the type of the single shale oil deposit well to be predicted according to the initial productivity and the decreasing rate after the single shale oil deposit well to be predicted enters the decreasing period specifically comprises the following steps:
when the initial productivity of the shale oil reservoir single well to be predicted after entering the decreasing period is more than 15 tons/day, the decreasing rate is more than 0.20 month -1 When the type of the shale oil reservoir single well to be predicted is high-yield rapid decreasing type;
when the initial productivity of the shale oil reservoir single well to be predicted after entering the decreasing period is 10-20 tons/day, the decreasing rate is 0.10-0.20 month -1 When the type of the shale oil reservoir single well to be predicted is a medium-yield decreasing type;
when the initial productivity of the single well of the shale oil reservoir to be predicted enters the decreasing period is less than 15 tons/day, and the decreasing rate is more than 0.20 month -1 When the type of the shale oil reservoir single well to be predicted is low-yield rapid decreasing type;
when the initial productivity of the shale oil reservoir single well to be predicted after entering the decreasing period is more than 15 tons/day, and the decreasing rate is less than 0.10 month -1 When the shale oil reservoir single well type to be predicted is low-yield stable-yield type.
3. The method for predicting the recoverable reserves of the single shale oil deposit well according to claim 1, wherein the obtaining a corresponding combination decreasing model of the single shale oil deposit well to be predicted according to the type of the single shale oil deposit well to be predicted specifically comprises:
when the type of the shale oil reservoir single well to be predicted is a high-yield rapid decreasing type or a low-yield rapid decreasing type, the corresponding combination decreasing model of the shale oil reservoir single well to be predicted is a PLE+FDC combination model;
when the type of the single well of the shale oil reservoir to be predicted is a middle-yield decreasing type, the corresponding combination decreasing model of the single well of the shale oil reservoir to be predicted is an SEPD+FDC combination model;
when the type of the single well of the shale oil deposit to be predicted is low-yield stable-yield type, the corresponding combination decreasing model of the single well of the shale oil deposit to be predicted is a Duong+FDC combination model.
4. The method for predicting the recoverable reserves of the single shale oil deposit well according to claim 1, wherein the method for calculating the recoverable reserves of the single shale oil deposit well to be predicted by utilizing the combined decreasing model comprises the following steps:
when the PLE+FDC combined model is used for carrying out the recoverable reserve calculation on the single well of the shale oil deposit to be predicted, the single well of the shale oil deposit to be predicted is formed into a combined decreasing model through the PLE model in one stage and the FDC model in the second stage of the shale oil deposit to be predicted Shan Jingdi, so that the recoverable reserve of the single well of the shale oil deposit to be predicted is obtained;
when the SEPD+FDC combined model is used for carrying out the recoverable reserve calculation on the single well of the shale oil deposit to be predicted, the single well of the shale oil deposit to be predicted is formed into a combined decreasing model through the SEPD model in one stage and the FDC model in the second stage of the shale oil deposit Shan Jingdi to be predicted, and the recoverable reserve of the single well of the shale oil deposit to be predicted is obtained;
when the Duong+FDC combined model is used for carrying out the recoverable reserve calculation on the single well of the shale oil deposit to be predicted, the recoverable reserve calculation is carried out on the single well of the shale oil deposit to be predicted by the Duong model in one stage and the FDC model in the second stage to form a combined decreasing model, so that the recoverable reserve of the single well of the shale oil deposit to be predicted is obtained.
5. The method for predicting the recoverable reserves of the single well of the shale oil deposit according to claim 4, wherein the method for calculating the recoverable reserves of the single well of the shale oil deposit to be predicted by using the PLE+FDC combination model specifically comprises the following steps:
calculating the daily output of the first stage of the model by using the PLE model;
calculating a model first-stage cumulative yield according to the model first-stage daily yield;
calculating the daily output of the second stage of the model by using the FDC model;
and adding the daily output of the first stage of the model and the daily output of the second stage of the model to obtain the recoverable reserve of the single well of the shale oil reservoir to be predicted.
6. The method for predicting the recoverable reserves of the single shale oil deposit well according to claim 4, wherein the method for calculating the recoverable reserves of the single shale oil deposit well to be predicted by using the SEPD+FDC combined model specifically comprises the following steps:
calculating the daily output of the first stage of the model by using the SEPD model;
calculating a model first-stage cumulative yield according to the model first-stage daily yield;
calculating the daily output of the second stage of the model by using the FDC model;
and adding the daily output of the first stage of the model and the daily output of the second stage of the model to obtain the recoverable reserve of the single well of the shale oil reservoir to be predicted.
7. The method for predicting the recoverable reserves of a single shale oil deposit well according to claim 4, wherein the method for calculating the recoverable reserves of the single shale oil deposit well to be predicted by using the Duong+FDC combination model specifically comprises the following steps:
calculating the daily output of the model in the first stage by using the Duong model;
calculating a model first-stage cumulative yield according to the model first-stage daily yield;
calculating the daily output of the second stage of the model by using the FDC model;
and adding the daily output of the first stage of the model and the daily output of the second stage of the model to obtain the recoverable reserve of the single well of the shale oil reservoir to be predicted.
8. The method for predicting the recoverable reserves of a single shale oil deposit well according to claim 1, wherein the obtaining the type of the single shale oil deposit well to be predicted according to the initial productivity and the rate of decline after the single shale oil deposit well to be predicted enters the decreasing period further comprises:
acquiring abnormal points which do not accord with a decreasing rule in the production process and points with zero gas production;
and deleting abnormal points which do not accord with the decreasing rule and points with zero gas production in the production process, reducing corresponding production days, and acquiring initial capacity and decreasing rate of the shale oil reservoir single well to be predicted after the shale oil reservoir single well to be predicted enters the decreasing period.
9. A shale reservoir single well recoverable reserves prediction system, the system comprising:
the shale oil reservoir single well type determining module is used for obtaining the type of the shale oil reservoir single well to be predicted according to the initial productivity and the progressive rate of the shale oil reservoir single well to be predicted after entering the progressive period; the type comprises a high-yield rapid decreasing type, a medium-yield decreasing type, a low-yield rapid decreasing type and a low-yield stable type;
the combination decreasing model determining module is used for obtaining a combination decreasing model corresponding to the single well of the shale oil deposit to be predicted according to the type of the single well of the shale oil deposit to be predicted; the combination decreasing model comprises a SEPD+FDC combination model, a PLE+FDC combination model and a Duong+FDC combination model;
and the recoverable reserves calculating module is used for calculating recoverable reserves of the single shale oil reservoir well to be predicted by utilizing the combined decreasing model to obtain recoverable reserves of the single shale oil reservoir well to be predicted.
10. The shale reservoir single well recoverable reserves prediction system of claim 9, wherein the system further comprises:
the abnormal point and gas production amount zero point acquisition module is used for acquiring abnormal points which do not accord with a decreasing rule in the production process and points with gas production amount zero;
the initial productivity and progressive rate obtaining module is used for deleting abnormal points which do not accord with the progressive rule in the production process and points with zero gas production, reducing corresponding production days, and obtaining the initial productivity and progressive rate of the shale oil reservoir single well to be predicted after the shale oil reservoir single well to be predicted enters the progressive period.
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