CN114756826B - Gas well productivity prediction method and device, electronic equipment and storage medium - Google Patents
Gas well productivity prediction method and device, electronic equipment and storage medium Download PDFInfo
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Abstract
The invention discloses a method and a device for predicting gas well productivity, electronic equipment and a storage medium, wherein the method comprises the following steps: constructing a first mathematical model which is related to the gas well productivity and can reflect the reservoir seepage capacity and the gas content, wherein the first mathematical model can evaluate the production capacity of a reservoir; constructing a second mathematical model comprising reservoir pressure and bottom hole flow pressure of the gas well, wherein the second mathematical model is used for representing the influence of pressure on productivity; determining a third mathematical model for predicting the productivity of the gas well based on the first mathematical model and the second mathematical model; and predicting the productivity of the gas well according to a third mathematical model. According to the scheme, the productivity of the gas well can be quickly and accurately predicted only according to the existing logging and gas testing data, so that a brand-new prediction mode of the productivity of the gas well is provided, and reliable technical support is provided for development of the gas field.
Description
Technical Field
The invention relates to the field of oil and gas reservoir evaluation, in particular to a method and a device for predicting gas well productivity, electronic equipment and a storage medium.
Background
Gas well productivity prediction has been an important research in the field of reservoir evaluation, but productivity calculation is influenced by various factors of reservoirs, such as: the permeability, the reservoir thickness, the skin factor and other influences, especially parameters such as the skin factor and the like which are difficult to predict, so that the calculated productivity result has low precision and is difficult to meet the requirements of practical application.
In the current technical level, the method for calculating the productivity of the gas well mainly comprises a formula calculation method, a numerical simulation method and an empirical model method. The formula calculation method is mainly characterized in that a steady-state or unsteady-state capacity equation is established through a Darcy equation of radial flow, and then reservoir parameters are directly introduced to carry out calculation. The numerical simulation rule solves the linear equation set according to iteration and other mathematical methods by establishing a physical model and a mathematical model so as to obtain the pressure and the capacity, and the history fitting is needed in the later period. In the actual production process, an empirical model method is usually considered preferentially, but the existing empirical model is mostly established on the relationship between reservoir parameters and unobstructed flow, a clear direct calculation model from reservoir comprehensive parameters to productivity is not established, and the original model formula is difficult to calculate more accurate variable productivity along with the change of the production system (flow pressure) of the same well.
Disclosure of Invention
In view of the above problems, the present invention provides a new method, apparatus, electronic device and storage medium for predicting gas well productivity by taking the relationship between productivity and reservoir parameters having important influence on productivity as a bridge, so as to overcome the above problems or at least partially solve the above problems. The method has wide application range and higher precision, avoids the influence of skin factors and the like which are difficult to determine parameters in the gas well productivity calculation, and can effectively solve the problem of low precision of the gas well productivity prediction in the actual production development process.
According to one aspect of the invention, a method for predicting the productivity of a gas well is provided, and the method for predicting the productivity of the gas well comprises the following steps:
constructing a first mathematical model which is related to the gas well productivity and can reflect the reservoir seepage capacity and the gas content, wherein the first mathematical model can evaluate the production capacity of a reservoir;
constructing a second mathematical model comprising reservoir pressure and bottom hole flow pressure of the gas well, the second mathematical model being used to characterize the effect of pressure on productivity;
determining a third mathematical model for predicting production capacity based on the first and second mathematical models;
and predicting the productivity of the gas well according to the third mathematical model.
In an alternative form, the first mathematical model comprises the product of at least two parameters: reservoir permeability, reservoir thickness, reservoir porosity, gas saturation, or reservoir pressure.
In an alternative mode, the third mathematical model further includes at least one empirical constant that characterizes a region of the gas well.
In an alternative mode, the expression of the first mathematical model is:
wherein, lambda is reservoir comprehensive parameters; k is the reservoir permeability; h is the reservoir thickness; phi is the reservoir porosity; s. the g Is the gas saturation; p is a radical of i Is the reservoir pressure.
In an alternative, the expression of the second mathematical model is:
wherein p is D Dimensionless pressure; p is a radical of wf Is the bottom hole flowing pressure.
In an alternative manner, the expression of the third mathematical model is:
wherein A, B is a regional empirical constant; q. q.s g And the capacity of the gas well is increased.
In an alternative form, the method for predicting the productivity of the gas well further comprises:
and verifying the productivity of the gas well by using a DST test, and correcting the empirical constants or parameters in the third mathematical model according to the verification result.
According to another aspect of the present invention, there is provided a gas well productivity prediction apparatus, comprising:
the first mathematical model building module is suitable for building a first mathematical model which is related to the gas well productivity and can reflect the reservoir seepage capacity and the gas content, and the first mathematical model can evaluate the production capacity of a reservoir;
a second mathematical model construction module adapted to construct a second mathematical model comprising reservoir pressure and bottom stream pressure of the well, the second mathematical model characterizing the effect of pressure on productivity;
a third mathematical model determination module adapted to determine a third mathematical model for predicting the capacity based on the first and second mathematical models;
and the productivity prediction module is suitable for predicting the productivity of the gas well according to the third mathematical model.
According to still another aspect of the present invention, there is provided an electronic apparatus including: the system comprises a processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface complete mutual communication through the communication bus;
the memory is used for storing at least one executable instruction, and the executable instruction enables the processor to execute the operation corresponding to the gas well productivity prediction method.
According to yet another aspect of the present invention, a computer storage medium is provided, wherein at least one executable instruction is stored in the storage medium, and the executable instruction causes a processor to execute the operation corresponding to the gas well productivity prediction method.
According to the method for predicting the productivity of the gas well, disclosed by the invention, the oil gas productivity can be rapidly and accurately predicted only according to the existing logging and gas testing data, so that the problem that the prediction precision of the productivity of the gas well is not high in the actual production and development process is solved, the application range is wide, the precision is higher, the influence of skin factors and the like in the calculation of the productivity of the gas well on the difficulty in determining parameters is avoided, and the reliable technical support is provided for the development of an oil gas field.
The foregoing description is only an overview of the technical solutions of the present invention, and the embodiments of the present invention are described below in order to make the technical means of the present invention more clearly understood and to make the above and other objects, features, and advantages of the present invention more clearly understandable.
Drawings
Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention. Also, like reference numerals are used to refer to like parts throughout the drawings. In the drawings:
FIG. 1 is a flow chart of a method for predicting the productivity of a gas well according to an embodiment of the invention;
FIG. 2 is a graph showing the relationship between reservoir synthesis parameters and productivity ratio and dimensionless pressure provided by an embodiment of the present invention;
FIG. 3 is a schematic diagram illustrating the structure of a gas well productivity prediction device provided by an embodiment of the invention;
fig. 4 shows a schematic structural diagram of an electronic device provided in an embodiment of the present invention.
Detailed Description
Exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the invention are shown in the drawings, it should be understood that the invention can be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art.
FIG. 1 shows a flow chart of an embodiment of the gas well productivity prediction method of the present invention, which, as shown in FIG. 1, comprises the steps of:
step 110: and constructing a first mathematical model which is related to the gas well productivity and can reflect the reservoir seepage capacity and the gas content, wherein the first mathematical model can evaluate the production capacity of the reservoir.
The first mathematical model is preferably a comprehensive parameter describing the oil and gas content and the seepage capability of an oil and gas reservoir, and is obtained by multiplying, forming an index or adding a plurality of parameters, wherein the gas well comprises an oil and gas mixing well or a well only producing gas.
Step 120: and constructing a second mathematical model comprising the reservoir pressure and the bottom stream pressure of the gas well, wherein the second mathematical model is used for characterizing the influence of the pressure on the productivity.
Since the reservoir pressure and the gas well bottom stream pressure have a large influence on the productivity, a second mathematical model is also constructed in the embodiment and used for calculating the influence of the pressure on the productivity.
Step 130: a third mathematical model for predicting production capacity is determined based on the first and second mathematical models.
And determining the mathematical expression relation between the third mathematical model for predicting the productivity and the first mathematical model and the second mathematical model by combining the statistical results of the gas testing data of a plurality of blocks of the oil and gas field and the calculation and test of the first mathematical model and the second mathematical model.
Step 140: and predicting the productivity of the gas well according to the third mathematical model.
According to the embodiment, the novel model for predicting the productivity of the gas well is realized by constructing the third mathematical model, the oil gas productivity of the gas well can be accurately predicted, the method is particularly suitable for predicting the productivity of the gas well, the cost is low, the precision is high, and better technical support is provided for oil gas field development.
In a preferred embodiment of the invention, said first mathematical model comprises the product of at least two parameters: reservoir permeability, reservoir thickness, reservoir porosity, gas saturation, or reservoir pressure.
And the parameters are conventional well logging data calibration data or gas testing data, so that the method is convenient to obtain and can ensure the reality and the reliability.
In one embodiment, the third mathematical model further includes at least one empirical constant indicative of an area in which the gas well is located. By introducing the empirical constants of the areas where the oil and gas fields are located, more accurate prediction is guaranteed.
In a preferred embodiment, the expression of the first mathematical model is:
wherein, lambda is reservoir comprehensive parameters, k is reservoir permeability, and the unit is mD; h is the reservoir thickness, preferably m; phi is the porosity of the reservoir and is a decimal less than 1; s g The gas saturation is a decimal less than 1; p is a radical of i Is the reservoir pressure in MPa.
Specifically, each of the reservoir synthesis parameters λ is an important parameter related to the actual gas well productivity. In the formula, kh represents a formation coefficient which reflects the gas supply capacity of the formation, and the larger the value is, the stronger the gas supply capacity of a gas layer is; the porosity phi reflects the reservoir storage capacity; gas saturation S g Reservoir gas bearing is indicated; formation pressure p i Representing reservoir pressure, the larger the value, the stronger the formation energy. Therefore, the reservoir comprehensive parameter lambda reflects the strength of the gas reservoir production capacity to a certain extent.
In a preferred embodiment, the expression of the second mathematical model is:
wherein p is D A dimensionless pressure of less than 1; p is a radical of wf Is the bottom hole flowing pressure in MPa.
Dimensionless pressure p D Representing the change of the bottom flowing pressure of the gas well under different stratums or different production systems of the same stratum.
In a preferred embodiment, the expression of the third mathematical model is:
wherein A, B is a regional empirical constant; q. q.s g And the capacity of the gas well is increased.
Through the statistical result of the gas testing data of a plurality of blocks of a certain offshore oil-gas field, the ratio of the reservoir comprehensive parameter lambda to the gas well productivity is found to be the same as the dimensionless pressure p D There is a universal rule as shown in formula (3), and the empirical constants a and B in the relationship change with the change of the region.
For the established gas well productivity prediction model, all parameters can obtain more accurate values in the prior art. By combining the conventional logging data calibration data and the gas testing data, more accurate information such as permeability, reservoir thickness, porosity, gas saturation, formation pressure and the like can be obtained, and the productivity of the gas well can be calculated by using the productivity model provided by the invention as long as the bottom hole flowing pressure of production is determined, so that more reliable technical support is provided for the development and production of the gas well.
Fig. 2 shows a productivity model constructed from 10 gas wells in a certain block of a gas field a, which shows the relationship between reservoir comprehensive parameters, productivity ratio and dimensionless pressure:
y = 182.48e -5.064x
accuracy of model fitting R 2 The (correlation coefficient) reached 0.9237. It shows that the block has an empirical constant A of 182.48 and an empirical constant B of 5.064.
In one embodiment, the method for predicting the productivity of the gas well further comprises the following steps: and verifying the productivity of the gas well by using a DST (direct sequence test) test, and correcting the empirical constant or the parameter in the third mathematical model according to a verification result.
Among them, the DST (Drill-Stem Testing) test, i.e., the gas well midway test, also called Drill pipe test, refers to a method for obtaining production prediction by interrupting drilling and utilizing a formation Testing instrument to measure pressure, demand production and sample in order to obtain oil and gas evaluation in the normal drilling process of a gas well.
In order to check the accuracy of the calculation result of the model, the capacity of another DST test gas well in the block is calculated and compared with the DST result.
For example, in a test segment DST1, the basic reservoir parameters are measured as follows: the well section length is 3248.3-3254.2, the vertical thickness is 5.9m, the permeability k is 120mD, the porosity phi is 18.9, and the gas saturation S g 52.1 and formation pressure 31.5305 mPa.
According to the productivity calculation of models under different production systems of the gas well, the DST test productivity and error analysis, the calculated error range is within 20%, and most errors are about 10%, so that the purpose of prediction is achieved.
According to the error analysis result, the model calculation gas well productivity is basically consistent with the DST test productivity, and the purpose of quickly and accurately predicting the gas well productivity is achieved.
Fig. 3 shows a schematic structural diagram of an embodiment of the gas well productivity prediction device of the invention. As shown in fig. 3, the gas well productivity prediction apparatus 300 includes:
the first mathematical model building module 310 is adapted to build a first mathematical model positively correlated to productivity, and the first mathematical model can evaluate the production capacity of the reservoir.
A second mathematical model construction module 320 adapted to construct a second mathematical model comprising reservoir pressure and well bottom stream pressure, said second mathematical model characterizing the effect of pressure on productivity.
A third mathematical model determination module 330 adapted to determine a third mathematical model for predicting the capacity based on the first and second mathematical models.
And the productivity predicting module 340 is suitable for predicting the productivity of the gas well according to the third mathematical model.
The gas well productivity prediction device 300 disclosed in this embodiment can accurately predict the oil gas productivity of the gas well by constructing the third mathematical model, is particularly suitable for predicting the productivity of the gas well, has low cost and high precision, and provides better technical support for oil gas field development.
In one embodiment, the first mathematical model comprises a product of at least two parameters: reservoir permeability, reservoir thickness, reservoir porosity, gas saturation, or reservoir pressure.
In one embodiment, the third mathematical model further includes at least one empirical constant indicative of an area in which the gas well is located.
In one embodiment, the expression of the first mathematical model is:
wherein, lambda is reservoir comprehensive parameters; k is reservoir permeability; h is the reservoir thickness; phi is the reservoir porosity; s g Is the gas saturation; p is a radical of i Is the reservoir pressure.
In one embodiment, the expression of the second mathematical model is:
wherein p is D Dimensionless pressure; p is a radical of formula wf Is the bottom hole flowing pressure.
In one embodiment, the expression of the third mathematical model is:
wherein A, B is a regional empirical constant; q. q of g And the capacity of the gas well is increased.
In one embodiment, the gas well productivity prediction device 300 is further adapted to: and verifying the productivity of the gas well by using a DST test, and correcting the empirical constants or parameters in the third mathematical model according to the verification result.
According to the method and the device for predicting the gas well productivity, disclosed by the invention, the oil gas productivity can be rapidly and accurately predicted only according to the existing well logging and gas testing data, so that the problem that the prediction precision of the gas well productivity is not high in the actual production and development process is solved, the application range is wide, the precision is higher, the influence of skin factors and the like which are difficult to determine parameters in the gas well productivity calculation is avoided, and better technical support is provided for the development of an oil gas field.
The embodiment of the invention provides a nonvolatile computer storage medium, wherein the computer storage medium stores at least one executable instruction, and the computer executable instruction can execute the gas well productivity prediction method in any method embodiment.
Fig. 4 is a schematic structural diagram of an embodiment of the electronic device according to the present invention, and the specific embodiment of the present invention does not limit the specific implementation of the electronic device.
As shown in fig. 4, the electronic device may include: a processor (processor)402, a Communications Interface 404, a memory 406, and a Communications bus 408.
Wherein: the processor 402, communication interface 404, and memory 406 communicate with each other via a communication bus 408. A communication interface 404 for communicating with network elements of other devices, such as clients or other servers. The processor 402 is used to execute the program 410, and may specifically execute the relevant steps in the above-described embodiment of the method for predicting gas well productivity for an electronic device.
In particular, program 410 may include program code comprising computer operating instructions.
The processor 402 may be a central processing unit CPU or an application Specific Integrated circuit asic or one or more Integrated circuits configured to implement embodiments of the present invention. The electronic device comprises one or more processors, which can be the same type of processor, such as one or more CPUs; or may be different types of processors such as one or more CPUs and one or more ASICs.
And a memory 406 for storing a program 410. Memory 406 may comprise high-speed RAM memory, and may also include non-volatile memory (non-volatile memory), such as at least one disk memory.
The program 410 can be specifically configured to cause the processor 402 to perform the operations corresponding to the gas well productivity prediction method in any of the embodiments described above.
The algorithms or displays presented herein are not inherently related to any particular computer, virtual machine, or other apparatus. Various general purpose systems may also be used with the teachings herein. The required structure for constructing such a system is apparent from the description above. In addition, embodiments of the present invention are not directed to any particular programming language. It is appreciated that a variety of programming languages may be used to implement the teachings of the present invention as described herein, and any descriptions of specific languages are provided above to disclose the best mode of the invention.
In the description provided herein, numerous specific details are set forth. It is understood, however, that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures and techniques have not been shown in detail in order not to obscure an understanding of this description.
Similarly, it should be appreciated that in the foregoing description of exemplary embodiments of the invention, various features of the embodiments of the invention are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the invention and aiding in the understanding of one or more of the various inventive aspects. However, the disclosed method should not be interpreted as reflecting an intention that: that the invention as claimed requires more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive aspects lie in less than all features of a single foregoing disclosed embodiment. Thus, the claims following the detailed description are hereby expressly incorporated into this detailed description, with each claim standing on its own as a separate embodiment of this invention.
Those skilled in the art will appreciate that the modules in the device in an embodiment may be adaptively changed and disposed in one or more devices different from the embodiment. The modules or units or components of the embodiments may be combined into one module or unit or component, and furthermore they may be divided into a plurality of sub-modules or sub-units or sub-components. All of the features disclosed in this specification (including any accompanying claims, abstract and drawings), and all of the processes or elements of any method or apparatus so disclosed, may be combined in any combination, except combinations where at least some of such features and/or processes or elements are mutually exclusive. Each feature disclosed in this specification (including any accompanying claims, abstract and drawings) may be replaced by alternative features serving the same, equivalent or similar purpose, unless expressly stated otherwise.
Furthermore, those skilled in the art will appreciate that while some embodiments herein include some features included in other embodiments, rather than other features, combinations of features of different embodiments are meant to be within the scope of the invention and form different embodiments. For example, in the following claims, any of the claimed embodiments may be used in any combination.
The various component embodiments of the invention may be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. Those skilled in the art will appreciate that a microprocessor or Digital Signal Processor (DSP) may be used in practice to implement some or all of the functionality of some or all of the components according to embodiments of the present invention. The present invention may also be embodied as apparatus or device programs (e.g., computer programs and computer program products) for performing a portion or all of the methods described herein. Such programs implementing the present invention may be stored on computer-readable media or may be in the form of one or more signals. Such a signal may be downloaded from an internet website or provided on a carrier signal or in any other form.
It should be noted that the above-mentioned embodiments illustrate rather than limit the invention, and that those skilled in the art will be able to design alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps not listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention may be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by one and the same item of hardware. The usage of the words first, second and third, etcetera do not indicate any ordering. These words may be interpreted as names. The steps in the above embodiments should not be construed as limiting the order of execution unless specified otherwise.
Claims (5)
1. A gas well productivity prediction method is characterized by comprising the following steps:
constructing a first mathematical model which is related to the gas well productivity and can reflect the reservoir seepage capacity and the gas content, wherein the first mathematical model can evaluate the production capacity of a reservoir;
constructing a second mathematical model comprising reservoir pressure and bottom hole flow pressure of the gas well, the second mathematical model being used to characterize the effect of pressure on productivity;
determining a third mathematical model for predicting production capacity based on the first and second mathematical models;
predicting the productivity of the gas well according to the third mathematical model;
the first mathematical model is a reservoir comprehensive parameter model for describing the oil and gas content and the seepage capacity of an oil and gas reservoir:
wherein, lambda is reservoir comprehensive parameters; k is reservoir permeability; h is the reservoir thickness; phi is the reservoir porosity; s g Is the gas saturation; p is a radical of i Is the reservoir pressure;
the second mathematical model is a dimensionless pressure model characterizing the impact of pressure on capacity:
wherein p is D Dimensionless pressure; p is a radical of wf Is bottom hole flowing pressure;
the third mathematical model is a gas well productivity prediction index model:
wherein A, B is a regional empirical constant; q. q of g The gas well capacity is obtained.
2. The method for predicting the productivity of a gas well according to claim 1, further comprising:
and verifying the productivity of the gas well by using a DST test, and correcting the empirical constants or parameters in the third mathematical model according to the verification result.
3. A gas well productivity prediction device, comprising:
the first mathematical model building module is suitable for building a first mathematical model which is related to the gas well productivity and can reflect the seepage capability and the gas content of a reservoir, and the first mathematical model can evaluate the production capability of the reservoir;
a second mathematical model construction module adapted to construct a second mathematical model comprising reservoir pressure and bottom stream pressure of the well, the second mathematical model characterizing the effect of pressure on productivity;
a third mathematical model determination module adapted to determine a third mathematical model for predicting the capacity based on the first and second mathematical models;
the productivity prediction module is suitable for predicting the productivity of the gas well according to the third mathematical model;
the first mathematical model is a reservoir comprehensive parameter model for describing the oil and gas content and the seepage capacity of an oil and gas reservoir:
wherein, lambda is reservoir comprehensive parameters; k is reservoir permeability; h is the reservoir thickness; phi is the reservoir porosity; s g Is the gas saturation; p is a radical of formula i Is the reservoir pressure;
the second mathematical model is a dimensionless pressure model characterizing the impact of pressure on capacity:
wherein p is D Dimensionless pressure; p is a radical of formula wf Is bottom hole flowing pressure;
the third mathematical model is a gas well productivity prediction index model:
wherein A, B is a regional empirical constant; q. q.s g And the capacity of the gas well is increased.
4. An electronic device, comprising: the system comprises a processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface complete mutual communication through the communication bus;
the memory is used for storing at least one executable instruction which causes the processor to execute the operation corresponding to the gas well productivity prediction method of any one of claims 1-2.
5. A computer storage medium having stored therein at least one executable instruction for causing a processor to perform operations corresponding to the method for predicting productivity of a gas well as set forth in any one of claims 1-2.
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