CN112069444A - Method and computer for calculating reservoir well testing permeability by using well logging data - Google Patents
Method and computer for calculating reservoir well testing permeability by using well logging data Download PDFInfo
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Abstract
The invention relates to a method and a computer for calculating the well testing permeability of a reservoir by utilizing well logging information. The method adopts a reservoir grading method to reflect that reservoirs of different levels in the emergent porous interval have different contributions to productivity, calculates the synthetic permeability of the reservoir of the emergent porous interval by giving weight coefficients of different levels of absolute permeability to the reservoirs of different levels and different sizes, and finally realizes accurate calculation of the well testing permeability by establishing a functional relationship between the synthetic permeability and the well testing interpretation permeability. The method can convert the absolute permeability of the reservoir explained by logging into the permeability explained by logging, so as to realize the purpose of continuously evaluating the natural productivity of the reservoir.
Description
Technical Field
The invention relates to the field of logging evaluation of petroleum geological exploration reservoirs, in particular to a method and a computer for calculating the well testing permeability of a reservoir by using logging information.
Background
In the field of petroleum geology, a reservoir refers to a rock formation with interconnected pores that allow the storage and seepage of hydrocarbons therein, referred to as a reservoir. The quantitative evaluation of the productivity of the reservoir stratum is an important task in the field of petroleum exploration and development, and well testing analysis is the most accurate method for obtaining the productivity for a long time, but due to the limitation of long testing time and high construction cost, the well testing can only be carried out on a main target stratum, and the capacity of each layer of each well cannot be obtained. The research of reservoir productivity prediction by utilizing logging information is always an indispensable means.
According to the seepage theory, the stable productivity of the oil well accords with a plane radial flow yield formula, namely:
in the formula, qoThe daily oil production is m3/d, KoPermeability is explained for well testing in mD; h is the effective output layer thickness of the perforation layer section, BoIs the volume coefficient of crude oil, muoCrude oil viscosity in pa.s; r iseIs the oil supply radius, in m; r iswIs the borehole radius in m; prIs static reservoir pressure in MPa; pwfIs the bottom hole flowing pressure in MPa.
Oil recovery index (I) of ricep) Yield per unit thickness, yield per unit pressure difference, defined as:
in the formula IpIs the meter oil recovery index, and has the unit of m 3/(MP.d.m).
For the oil field actually produced, the crude oil properties are basically the same and are developed by well patternThe supply radius of different oil wells is not greatly different, so that it can be considered that 2 pi/B is applied to the same oil fieldoμoln(re/rw) Is a constant.
As can be seen from the above formula, the magnitude of the reservoir productivity is directly proportional to the permeability of the well test interpretation, so that reservoir productivity prediction research can be carried out according to the permeability of the reservoir well test interpretation.
But the values of the reservoir obtained at the same depth point will vary due to the different probe diameters of the different test patterns. The detection scale of the well logging interpretation permeability is about 0.3 meter, the permeability of the reaction flushing zone stratum can be reflected, and the detection scale of the well testing can reach more than 1000 meters. In addition, for pure oil intervals, the average value of the absolute permeability of the reservoir in the perforation interval is obtained by well logging interpretation, and the oil phase permeability of the effective production layer is obtained by well testing interpretation. Therefore, the permeability of the well logging interpretation is very different from that of the well testing interpretation in both macroscopic characterization scale and absolute value size.
Based on the analysis, in the actual quantitative evaluation of the productivity of the reservoir, the average value of the absolute permeability of the effective reservoir of the perforation interval obtained by utilizing the well logging interpretation cannot accurately reflect the permeability of the effective production layer, and the aim of accurately and quantitatively evaluating the productivity of the reservoir cannot be fulfilled directly according to the permeability of the well logging interpretation.
Disclosure of Invention
The present invention provides a method and a computer for calculating the permeability of a reservoir test well by using well-log data, which aims to solve the above-mentioned drawbacks of the prior art.
The technical scheme adopted by the invention for solving the technical problems is as follows: a method for calculating reservoir well testing permeability using well logging data is constructed, comprising:
s1, establishing a logging interpretation model of the absolute permeability of the reservoir layer: calculating the absolute permeability of the reservoir by utilizing the porosity, permeability, rock granularity, cast body slices, mercury intrusion and X diffraction data obtained by analyzing a rock core experiment and combining the regional geological rule and the well logging curve characteristics;
s2, establishing a reservoir grading standard: on the basis of referring to the classification standard of the clastic rock reservoir, giving M-1 porosity and permeability values according to the porosity, permeability and capacity data of core analysis in a research area, and dividing the reservoir into M levels;
s3, calculating the permeability of the reservoir layer with different levels: grading the reservoir of the perforated interval by using porosity and permeability curves, counting the average value Ki of the permeability of each level of reservoir, and sequencing the permeability of each level of reservoir from large to small, wherein the permeability is respectively marked as K1, K2 and K3 … … KM;
ki is the average value of the permeability of the ith reservoir, the unit is mD, i is more than or equal to 1 and less than or equal to M; n is the number of sampling points of the ith-level reservoir, and is a positive integer;
s4, calculating the synthetic permeability: calculating the synthetic permeability by giving different weight coefficients to different levels of reservoirs in the perforated interval and constraining the size of the weight coefficients;
in the formula KCombination of Chinese herbsIs the synthetic permeability of the perforation interval, in mD; a isjIs a weight coefficient, and 0<aj<aj-1<1; j is an integer, and j is more than or equal to 1 and less than or equal to M;
recording the ratio of the average value of the permeability of the first-level reservoir to the average value of the permeability of the reservoir of each later level as K1/Ki, when K1/Ki >10, the reservoir of the level does not contribute to the energy production, and setting the weight coefficient of the permeability of the reservoir arranged behind the level as 0;
s5, establishing a functional relation between the synthetic permeability and the well testing interpretation permeability of the reservoir layers of different levels of the perforation intervals, and calculating the well testing permeability of the perforation intervals from the permeability data of the actual well logging interpretation by using the functional relation.
Further, in the method for calculating the permeability of the reservoir test well by using the well logging data of the present invention, the functional relationship between the synthetic permeability and the well test interpretation permeability of the reservoir related to different levels in the step S5 is as follows:
in the formula
The permeability of the well testing explanation of the ith perforation interval is expressed in mD; the value of i is determined by the number of perforation layers in the research area;
represents the average of the absolute permeability explained by each level of reservoir logging after the sequencing of the perforation log segments,
the weight coefficient is the weight coefficient of the synthetic permeability, and the numerical value is obtained by calibrating the permeability explained by the well testing of the perforation layer; d and c are undetermined constants, and the numerical values of the undetermined constants are obtained by calibrating the well testing interpretation permeability of the perforation layer.
Further, in the method for calculating permeability of a reservoir test well by using well logging data of the present invention, the permeability calculation method in step S1 includes one or more of a permeability and porosity regression model, Herron model, petrophysical facies classification, flow cell classification, nuclear magnetic SDR and Coates model.
In addition, the invention also provides a computer, which comprises a memory and a processor;
the memory is used for storing a computer program;
the processor is configured to execute a computer program in the memory to implement a method of calculating a reservoir test permeability using well logs as described above.
The method and the computer for calculating the well testing permeability of the reservoir by utilizing the logging information have the following beneficial effects: the method adopts a reservoir grading method to reflect that reservoirs of different levels in the emergent porous interval have different contributions to productivity, calculates the synthetic permeability of the reservoir of the emergent porous interval by giving weight coefficients of different levels of absolute permeability to the reservoirs of different levels and different sizes, and finally realizes accurate calculation of the well testing permeability by establishing a functional relationship between the synthetic permeability and the well testing interpretation permeability. The method can convert the absolute permeability of the reservoir explained by logging into the permeability explained by logging, so as to realize the purpose of continuously evaluating the natural productivity of the reservoir.
Drawings
The invention will be further described with reference to the accompanying drawings and examples, in which:
FIG. 1 is a plot of mean absolute permeability from well log interpretation versus permeability from well test interpretation;
FIG. 2 is a flow chart of a method for calculating permeability of a reservoir test using well logs provided by an embodiment;
FIG. 3 is a graph of different types of reservoir core analysis porosity and permeability;
FIG. 4 is a conventional well log identification chart for flat-concave different reservoir types;
FIG. 5 is a conversion model of synthetic permeability and well testing interpretation permeability;
FIG. 6 is a log plot illustrating the final shut-in well testing of the HJ530 zone of the B well;
FIG. 7 is a graph of the permeability results of a B well HJ530 layer synthetic permeability calculation test well.
Detailed Description
For a more clear understanding of the technical features, objects and effects of the present invention, embodiments of the present invention will now be described in detail with reference to the accompanying drawings.
The method aims to solve the problems that the correlation between the average value of the absolute permeability of the effective reservoir of the perforation interval and a well testing interpretation permeability model which is directly established by a statistical regression method is poor (figure 1) and the precision cannot meet the productivity prediction requirement. The embodiment provides a method for calculating the well testing permeability of a reservoir by using well logging information, which can convert the absolute permeability of the reservoir explained by well logging into the well testing explained permeability so as to realize the purpose of continuously evaluating the natural productivity of the reservoir.
The present embodiment is explained with reference to fig. 2 to 7. In this embodiment, the layer well testing explanation permeability calculation process of the well B is selected to explain by taking the oil field a of the basin at the pearl estuary as an example.
S1, analyzing porosity, permeability, X-ray diffraction and slice granularity data by using the core of the oil field A in the Yangtze river basin, dividing the reservoir into 3 types of flow units according to the flow unit theory, and obtaining a permeability calculation model corresponding to the 3 types of flow units in the graph 3. Analyzing the response characteristics of different flow units on a conventional logging curve, and extracting two parameters sensitive to the type of the flow units from the response characteristics, namely the difference between the natural gamma and neutron porosity and the density under a certain scale condition, namely:
NDS＝(RHOB-1.95)/0.1-(0.45-TNPH)/0.06
in the formula: NDS is the difference value of neutron porosity and density logging value under a certain scale condition, V/V; RHOB is the density log in g/cm3(ii) a TNPH is neutron porosity in V/V.
FIG. 4 is a graphical representation of the identification of three types of flow elements created using natural gamma and NDS curves, from which it can be seen that there are distinct boundaries between the various types of flow elements in the reservoir, from which the division of the type of flow elements in the A field of the Zhujiang estuary basin can be made according to conventional well logs.
S2, establishing a reservoir grading standard: according to the classification standard of the clastic rock reservoir and the porosity, permeability and actual capacity data of core analysis of the oil field A, giving 7 porosities and permeability values, wherein the corresponding permeabilities are respectively 2mD, 5mD, 20mD, 50mD, 200mD, 500mD and 2000 mD; the porosity was 8%, 12%, 15%, 17.5%, 20%, 25%, 30%, respectively, dividing the reservoir into 8 grades.
S3, calculating the permeability of the reservoirs of different levels of the perforated intervals: grading the reservoir stratum of the perforated interval by utilizing a porosity and permeability curve, counting the average value Ki of the permeability of each level of reservoir stratum, and sequencing the permeability of each level of reservoir stratum from large to small, wherein the permeability of each level of reservoir stratum is respectively marked as K1, K2 and K3 … … KM;
in the formula: ki is the average value of the i-th reservoir permeability and is expressed in mD; n is the number of ith reservoir sampling points.
S4, calculating the synthetic permeability: the synthetic permeability is calculated by giving different weighting factors to different levels of the reservoir in the perforated interval and constraining the magnitude of the weighting factors, i.e.
In the formula KCombination of Chinese herbsThe synthetic permeability of the perforation interval is given in mD; a isjIs a weight coefficient, 0<aj<aj-1<1; j is an integer, and j is more than or equal to 1 and less than or equal to M.
And recording the ratio of the average permeability of the reservoir at the first stage to the average permeability of the reservoir at the later stage as K1/Ki, wherein when K1/Ki is greater than 10, the reservoir at the first stage does not contribute to the productivity, and the weight coefficient of the permeability of the reservoir arranged at the later stage of the stage is set to be 0. By ranking the reservoirs of the perforation intervals according to the ranking criteria of the Enping-cave reservoir in the step S2, when the reservoir rank exceeds 3, K1/Ki >10, that is, only the reservoir with the perforation interval ranked in the first three levels contributes to the productivity.
S5, establishing a functional relation between the synthetic permeability and the well testing interpretation permeability of the reservoir layers of different levels of the perforation intervals, and calculating the well testing permeability of the perforation intervals from the permeability data of the actual well logging interpretation by using the functional relation.
The functional relationship between the synthetic permeability and the well testing interpretation permeability of the reservoir of different grades related to the A oil field of the Zhujiang river basin in the step S5 is as follows:
in the formula
The permeability of the well testing explanation of the ith perforation interval is expressed in mD; the value of i is determined by the number of perforation layers in the research area;
represents the average of the absolute permeability of the front three reservoir well log interpretations after the perforation log sequencing,
the weight coefficient is the weight coefficient of the synthetic permeability, and the numerical value is obtained by calibrating the permeability explained by the well testing of the perforation layer; d and c are undetermined constants, and the numerical values of the undetermined constants are obtained by calibrating the well testing interpretation permeability of the perforation layer.
In order to illustrate the reliability of the method, the permeability of the reservoir well testing explanation of the selected perforated interval is wide in distribution range, the distribution range is 0.1-20000 mD, and all reservoirs encountered in daily production are basically covered. From fig. 4, it can be seen that the complex correlation coefficient between the synthetic permeability of the perforation interval reservoir logging and the well test interpretation permeability is 0.9324, which is improved by 0.2231 compared with the complex correlation coefficient 0.7093 between the average permeability of the logging and the well test interpretation, and this indicates that the method has a good practical effect.
FIG. 7 is a well testing explanatory permeability achievement diagram obtained by processing actual well data by a computer program programmed according to the method of the present embodiment, wherein the whole diagram is composed of ten paths in total.
The first pass is a geological stratification pass.
The second track is a depth track.
The third path is a lithologic path, which comprises a natural gamma curve (GR), a borehole diameter Curve (CAL) and a BIT diameter curve (BIT).
The fourth trace is an array lateral resistivity curve trace, the detection depths are MLR1C, MLR2C, MLR3C and MLR4C from shallow to deep once, and RTM is the apparent resistivity of the stratum obtained by resistivity inversion.
The fifth trace is a physical property trace including a density curve (RHOB), a neutron porosity curve (CNCF), a photoelectric absorption cross-section curve (PE), and a density correction amount curve (ZCOR).
The sixth trace is a permeability trace comprising the CORE analysis permeability point data (K _ CORE) and the well log interpretation permeability (KINT).
The seventh trace is a porosity trace comprising CORE analysis porosity point data (POR _ CORE) and a well log interpretation porosity curve (PHIE).
The eighth trace is a well log interpretation water saturation trace comprising well log interpretation water saturation (Swe).
The ninth lane is a flow cell sorting lane.
The tenth trace is a reservoir stratifying trace.
From the ninth path, it can be seen that the HJ530 layer of the B well develops three types of flow units, and the permeability of the well logging interpretation after the flow unit classification and the permeability of the core analysis are matched well by mainly using the two types and three types of flow units. The perforated interval of the well is 1690-1710 m, the effective thickness of the well interpretation is 10 m, and the tenth shows that the reservoirs of 2 to 7 grades of perforated intervals of the HJ530 layer are developed, but the reservoirs of 2, 3 and 4 grades contributing to the actual productivity are provided, and the thickness of the effective output layer is 3.2 m, 6.8 m smaller than the effective thickness and only occupies 32% of the thickness of the effective reservoir. The permeability of the 2-class reservoir is 650.7mD, the permeability of the 3-class reservoir is 300mD, the permeability of the 4-class reservoir is 60.1mD, the synthetic permeability is 122.7mD, the permeability of the test well of the layer is 839mD according to the calculation of figure 5, and figure 6 is a derivative test well interpretation chart of the perforation layer, and the permeability of the test well interpretation obtained from the derivative test well interpretation chart is 775mD, which are very close to each other. The well testing permeability obtained by the method can effectively represent the permeability of an actual production layer of the perforation interval on the well testing scale.
The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. The device disclosed by the embodiment corresponds to the method disclosed by the embodiment, so that the description is simple, and the relevant points can be referred to the method part for description.
Those of skill would further appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the various illustrative components and steps have been described above generally in terms of their functionality in order to clearly illustrate this interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module may reside in Random Access Memory (RAM), memory, Read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.
The above embodiments are merely illustrative of the technical ideas and features of the present invention, and are intended to enable those skilled in the art to understand the contents of the present invention and implement the present invention, and not to limit the scope of the present invention. All equivalent changes and modifications made within the scope of the claims of the present invention should be covered by the claims of the present invention.
Claims (4)
1. A method for calculating a reservoir well test permeability using well log data, comprising:
s1, establishing a logging interpretation model of the absolute permeability of the reservoir layer: calculating the absolute permeability of the reservoir by utilizing the porosity, permeability, rock granularity, cast body slices, mercury intrusion and X diffraction data obtained by analyzing a rock core experiment and combining the regional geological rule and the well logging curve characteristics;
s2, establishing a reservoir grading standard: on the basis of referring to the classification standard of the clastic rock reservoir, giving M-1 porosity and permeability values according to the porosity, permeability and capacity data of core analysis in a research area, and dividing the reservoir into M levels;
s3, calculating the permeability of the reservoir layer with different levels: grading the reservoir of the perforated interval by using porosity and permeability curves, counting the average value Ki of the permeability of each level of reservoir, and sequencing the permeability of each level of reservoir from large to small, wherein the permeability is respectively marked as K1, K2 and K3 … … KM;
ki is the average value of the permeability of the ith reservoir, the unit is mD, i is more than or equal to 1 and less than or equal to M; n is the number of sampling points of the ith-level reservoir, and is a positive integer;
s4, calculating the synthetic permeability: calculating the synthetic permeability by giving different weight coefficients to different levels of reservoirs in the perforated interval and constraining the size of the weight coefficients;
in the formula KCombination of Chinese herbsIs the synthetic permeability of the perforation interval, in mD; a isjIs a weight coefficient, and 0<aj<aj-1<1; j is an integer, and j is more than or equal to 1 and less than or equal to M;
recording the ratio of the average value of the permeability of the first-level reservoir to the average value of the permeability of the reservoir of each later level as K1/Ki, when K1/Ki >10, the reservoir of the level does not contribute to the energy production, and setting the weight coefficient of the permeability of the reservoir arranged behind the level as 0;
s5, establishing a functional relation between the synthetic permeability and the well testing interpretation permeability of the reservoir layers of different levels of the perforation intervals, and calculating the well testing permeability of the perforation intervals from the permeability data of the actual well logging interpretation by using the functional relation.
2. The method for calculating the permeability of a reservoir test well using well logs as claimed in claim 1, wherein the functional relationship between the synthetic permeability and the well test interpretation permeability of the reservoir related to different levels in the step S5 is as follows:
in the formula
The permeability of the well testing explanation of the ith perforation interval is expressed in mD; the value of i is determined by the number of perforation layers in the research area;
represents the average of the absolute permeability explained by each level of reservoir logging after the sequencing of the perforation log segments,
the weight coefficient is the weight coefficient of the synthetic permeability, and the numerical value is obtained by calibrating the permeability explained by the well testing of the perforation layer; d and c are undetermined constants, and the numerical values of the undetermined constants are obtained by calibrating the well testing interpretation permeability of the perforation layer.
3. The method of claim 1, wherein the permeability calculation in step S1 includes one or more of a permeability and porosity regression model, Herron model, petrophysical facies classification, flow cell classification, nuclear magnetic SDR and Coates model.
4. A computer comprising a memory and a processor;
the memory is used for storing a computer program;
the processor is configured to execute a computer program in the memory to implement the method of calculating reservoir test permeability using well logs as defined in any one of claims 1 to 3.
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