CN111563609A - Dense sandstone reservoir development and selection method - Google Patents
Dense sandstone reservoir development and selection method Download PDFInfo
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Abstract
The invention discloses a tight sandstone reservoir development and region selection method, which is characterized by comprising the following steps of: obtaining a normalized geological characterization parameter according to the geological characterization parameter of the target oil well in the test area; establishing a productivity prediction model of the target oil well according to the productivity data in the production data of the target oil well and the normalized geological characterization parameters; acquiring the predicted capacity data of the target oil well according to the capacity prediction model of the target oil well; determining a capacity prediction contour map of the target oil well according to the predicted capacity data of the target oil well; and determining the development selection range of the test area according to the capacity prediction contour map of the target oil well and the development selection standard of the test area. The method can improve the method for developing and selecting the area by a single-factor overlapping method, and improve the efficiency of developing and selecting the area and the drilling success rate of a high-yield oil well.
Description
Technical Field
The invention relates to a dense sandstone reservoir development and region selection method, and belongs to the field of petroleum exploration and development.
Background
The tight sandstone reservoir belongs to an unconventional reservoir, the oil-gas enrichment rule is complex, the high-yield main control factor of an oil well is not clear, and the difficulty in developing and selecting zones is high. Development practices show that how to search a relatively enriched oil-gas area in a large-area evaluation area, namely to perform efficient development and selection of compact oil is the basis and key for deploying high-yield development wells and realizing effective development of compact oil.
At present, a dense sandstone oil reservoir generally adopts a single-factor overlapping method suitable for a conventional oil reservoir to develop and select regions, namely, images such as a dominant sedimentary facies diagram, a sand body plane diagram, a reservoir physical property distribution diagram, a fluid distribution diagram, an productivity distribution diagram and the like are overlapped on the basis of single-factor analysis of reservoir deposition, structure, physical properties, fluids, productivity and the like by utilizing a geophysical and geological evaluation means, and the obtained dominant overlapping regions of the single factors are development favorable regions. The method has the defects that the main control factors of the high-yield enrichment of the compact oil gas are complex, the evaluation parameters and drawing graphs of the development selected area are numerous, the situation that the overlapping condition of the single-factor graphs is poor can be caused frequently, the rationality of the result of the selected area is poor, the deployment of the development well position is difficult to guide, and the method cannot make a prejudgment on the capacity situation of the future development well, so the development risk of the compact sandstone reservoir is increased.
In the prior art, an application analytic hierarchy process is adopted to carry out dense oil development and selection in a Jurassic Daanzhai section in the middle of a Sichuan basin, and the method mainly comprises five steps: firstly, determining a target and a scheme according to geological features of a research area, and constructing a target layer and a scheme layer; determining a criterion layer according to factors influencing dense oil enrichment; establishing a pair comparison matrix of each element in the criterion layer, and determining the relative weight of each criterion element; fourthly, establishing judgment matrixes of the criterion elements to different schemes, and determining the weight of the criterion elements in the different schemes; multiplying the weight matrix of each criterion element of different schemes with the relative weight matrix of the criterion element to obtain the hierarchical order of each scheme, and further selecting the best scheme. Although the method has the advantages of simple operation, no need of considering the lower limit value and wide application range, the evaluation results given by different evaluators are possibly very different due to the fact that the scales in the hierarchical analysis are assigned according to the manual experience, the method strongly depends on the experience of people and is high in manual property, and therefore the scientificity of the selection result is to be tested. Moreover, when there are more criteria layers or more scheme layers, a high-order matrix needs to be constructed, which results in a large number of parameters and complex calculation, and does not have the capacity prediction function.
The Chinese patent application with the application number of CN201710386352.9 discloses a comprehensive evaluation and prediction method for a compact oil enrichment favorable area of a continental lake basin, in particular to a preferred method for the compact oil favorable area, which comprises the following steps: according to the longitudinal superposition relationship of different rocks in the well logging lithology profile, defining the source reservoir configuration relationship and establishing a single well lithofacies mode; forming a cloud-ground ratio contour map and a TOC contour map by using single-well cloud-ground ratio and TOC data, superposing the cloud-ground ratio contour map, the TOC contour map and a source reservoir configuration relation plane distribution map, and determining a lithofacies plane distribution map; on the basis of a lithofacies plane graph, a vitrinite reflectivity contour map is superposed, and meanwhile, a dolomite thickness contour map is referred to, so that comprehensive evaluation and prediction are carried out on the compact oil enrichment favorable area. The method is simple to operate and high in accuracy, and can clearly and comprehensively reflect the plane distribution rules of the high-quality reservoir stratum, the high-quality hydrocarbon source rock and the mutual configuration relation of the reservoir stratum and the high-quality hydrocarbon source rock. However, the method is mainly focused on the dense oil exploration and selection stage, and is still a single-factor overlapping method in nature, the evaluation parameters and drawing pictures of the selection are numerous, which often causes the situation that the overlapping condition of the single-factor pictures is not good, the result of the selection is not reasonable, and the capacity prediction function is not available.
The traditional compact oil district selection method with single-factor overlapping or the probability of the favorable district calculated by mathematical operation has the defects of complex district selection method and poor rationality of district selection results, and the productivity of the selected district can not be predicted. The method for establishing the dense oil selection area based on the geological parameter-productivity prediction model has practical significance for dense oil development.
Disclosure of Invention
In view of the above problems, the present invention aims to provide a method for developing and selecting a compact sandstone reservoir, which can improve the method for developing and selecting a zone by a single-factor overlap method, and improve the efficiency of developing and selecting a zone and the drilling success rate of a high-yield oil well.
In order to achieve the purpose, the invention adopts the following technical scheme: a tight sandstone reservoir development and region selection method comprises the following steps: (1) obtaining a normalized geological characterization parameter according to the geological characterization parameter of the target oil well in the test area; (2) establishing a productivity prediction model of the target oil well according to the productivity data in the production data of the target oil well and the normalized geological characterization parameters; (3) acquiring the predicted capacity data of the target oil well according to the capacity prediction model of the target oil well; (4) determining a capacity prediction contour map of the target oil well according to the predicted capacity data of the target oil well; (5) and determining the development selection range of the test area according to the capacity prediction contour map of the target oil well and the development selection standard of the test area.
In a specific embodiment, in step (1), the geological characterization parameters include matrix reservoir coefficients, fracture strength coefficients, and source rock coefficients.
In one embodiment, in step (1), the matrix reservoir coefficient is determined according to the formula:
S1＝L*H*φ (1)
in the formula, S1Is the matrix reservoir coefficient, L is the length of the target oil well drilling sand, H is the thickness of the target layer sand, and phi is the average porosity.
In one specific embodiment, in the step (1), the fracture strength parameter is determined according to the formula:
S2＝φf*bf+nf(2)
in the formula, S2Is the crack strength coefficient, phifIs the porosity of the crack, bfIs a crackOpening degree, nfIs the zone crack strength.
In one specific embodiment, in step (1), the hydrocarbon source rock coefficient is determined according to the formula:
S3＝TOC*h (3)
in the formula, S3And the TOC is the total organic carbon content of the source rock at the position of the target oil well track, and h is the effective thickness of the source rock at the position of the target oil well track.
In a specific embodiment, in step (1), the normalized geologic characterization parameter is obtained according to the formula:
S′i＝(Si-Si-min)/(Si-max-Si-min) (4)
of formula (II) S'iNormalized geological characterization parameters for the target well, where i is 1, 2 or 3, SiIs a geological characterization parameter of the target well, Si-maxFor the target well and SiMaximum value, S, in geological characterization parameters of the same typei-minFor the target well and SiMinimum value in geological characterization parameters of the same type.
In one embodiment, in the step (2), the capacity data of the production data of the target oil well is determined as a dependent variable, the normalized geological characterization parameter of the target oil well is determined as an independent variable, and the capacity prediction model of the target oil well in the test area is established through multiple linear regression.
In one embodiment, in the step (2), the productivity prediction model of the target oil well in the test area is built according to the formula:
wherein Y is the cumulative production capacity data, S ', in the target oil well production data'1To normalized reservoir coefficients, a is the weight of the normalized reservoir coefficients, S'2Is a normalized fracture intensity coefficient, b is a weight of the normalized fracture intensity coefficient, S'3For normalized source rock coefficients, c is normalized hydrocarbonAnd d is a constant, Q is the average daily oil yield of the target oil well, and T is the production days.
In one embodiment, in the step (2), the accumulated capacity data in the production data of the target well is the accumulated capacity of the target well in the same natural time period.
In one embodiment, the cumulative capacity of the target well in the same natural time period is the cumulative oil production of the target well in the natural time period of the previous 90 days, the previous 180 days and the previous 1 year.
In one embodiment, in the step (3), the normalized geological characterization parameters of the target oil well are input into the capacity prediction model of the target oil well, and the predicted capacity data of the target oil well is obtained.
In a particular embodiment, the normalized geologic characterization parameters include normalized reservoir coefficients, normalized fracture intensity coefficients, and normalized source rock coefficients.
In one embodiment, the predicted capacity data for the target well includes predicted cumulative oil production and average daily oil production data.
In one embodiment, in the step (4), the cumulative oil production prediction contour map of the target oil well is determined by an interwell difference method according to the predicted cumulative oil production data of the target oil well, and the average daily oil production prediction contour map of the target oil well is determined by an interwell difference method according to the predicted average daily oil production data of the target oil well.
In one specific embodiment, in the step (5), the development and selection criteria of the test area are set as the single-well technical economic threshold values at different oil prices, the single-well abandonment production limit is used as the cumulative oil production lower limit of the target oil well, and the single-well initial production limit is used as the average daily oil production lower limit of the target oil well.
In one specific embodiment, in the step (5), the development selection range of the test zone includes a region on the cumulative oil production prediction contour of the target well which is larger than the single-well abandoned production limit, or a region on the average daily oil production prediction contour of the target well which is larger than the single-well initial production limit.
In one embodiment, in the step (5), when the development and selection are performed according to the average daily oil yield prediction contour map of the target oil well, the counted production data of the target oil well are all production data in the previous 180 days; and when the development and selection are carried out according to the contour map of the cumulative oil production of the target oil well, the limitation of the production days is avoided.
In one embodiment, the target well is satisfied without being affected by flooding, fracturing anomalies, and well trajectory anomalies, and the cumulative production time of the target well is greater than or equal to 1 year.
Due to the adoption of the technical scheme, the invention has the following advantages: the invention provides a district selection method based on a geological parameter-productivity prediction model, which can improve the method of low efficiency of single-factor overlap method mining district selection, improve the accuracy of developing district selection and the drilling success rate of high-yield oil wells, can predict the productivity condition of oil wells in future development areas, and provide guidance for well position deployment of tight sandstone reservoir development, avoidance of development risk and realization of effective development.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by the practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
Drawings
In order to more clearly illustrate the technical solution in the embodiments of the present invention, the following briefly introduces the drawings required in the description of the embodiments:
figure 1 is a schematic flow diagram of one embodiment of a tight sandstone reservoir development zonal method of the present invention;
FIG. 2 is a schematic representation of geologic characterization parameters for controlling horizontal well productivity in accordance with an embodiment of the present invention;
FIG. 3 is a single well histogram of a horizontal well in the south of Eimen according to an embodiment of the present invention;
FIG. 4 is a graphical representation of the relationship of qualitative characterization parameters to average daily oil production for certain south Eimeria oil fields in accordance with an embodiment of the present invention;
FIG. 5 is a contour plot of the average daily oil production for a certain oil field in Enan, in accordance with an embodiment of the present invention;
FIG. 6 is a schematic illustration of a development vantage point distribution at $ 70 oil price for a certain oil field in the south of Eimeria of an embodiment of the present invention;
figure 7 is a schematic illustration of a development bay at $ 70 oil price for an oil field in south of the jaw of one embodiment of the present invention.
Detailed Description
The following detailed description of the embodiments of the present invention will be provided with reference to the drawings and examples, so that how to apply the technical means to solve the technical problems and achieve the technical effects can be fully understood and implemented. It should be noted that, as long as there is no conflict, the embodiments and the features of the embodiments of the present invention may be combined with each other, and the technical solutions formed are within the scope of the present invention.
As shown in fig. 1, the method for developing and selecting tight sandstone oil reservoir provided by the invention comprises the following steps:
(1) obtaining a normalized geological characterization parameter according to the geological characterization parameter of the target oil well in the test area;
(2) establishing a productivity prediction model of the target oil well according to the productivity data in the production data of the target oil well and the normalized geological characterization parameters;
(3) acquiring the predicted capacity data of the target oil well according to the capacity prediction model of the target oil well;
(4) determining a capacity prediction contour map of the target oil well according to the predicted capacity data of the target oil well;
(5) and determining the development selection range of the test area according to the capacity prediction contour map of the target oil well and the development selection standard of the test area.
Specifically, in step (1), the geological characterization parameters comprise matrix reservoir coefficients for characterizing the matrix reservoir, fracture strength coefficients for characterizing the fractures, and source rock coefficients for characterizing the oil content of the reservoir.
In step (1), the matrix reservoir coefficients are determined according to the formula:
S1＝L*H*φ (1)
in the formula, S1Is the matrix reservoir coefficient, L is the length of the target oil well drilling sand, H is the thickness of the target layer sand, and phi is the average porosity.
In step (1), the crack strength parameter is determined according to the formula:
S2＝φf*bi+nf(2)
in the formula, S2Is the crack strength coefficient, phifIs the porosity of the crack, bfOpening of crack, nfIs the zone fracture strength, which is obtained by seismic or geostress simulation.
In step (1), the formula according to which the hydrocarbon source rock coefficient is determined is as follows:
S3＝TOC*h (3)
in the formula, S3And the TOC is the total organic carbon content of the high-quality source rock at the position of the target oil well track, and the h is the effective thickness of the high-quality source rock at the position of the target oil well track.
In step (1), the formula according to which the normalized geologic characterization parameters are obtained is:
S′i＝(Si-Si-min)/(Si-max-Si-min) (4)
of formula (II) S'iNormalized geological characterization parameters for the target well, where i is 1, 2 or 3, SiIs a geological characterization parameter of the target well, Si-maxFor the target well and SiMaximum value, S, in geological characterization parameters of the same typei-minFor the target well and SiMinimum value in geological characterization parameters of the same type.
Specifically, in the step (2), the capacity data of the production data of the target oil well is determined to be a dependent variable, the normalized geological characterization parameter of the target oil well is determined to be an independent variable, and a capacity prediction model of the target oil well in the test area is established through multiple linear regression.
In the step (2), the formula according to which the productivity prediction model of the target oil well in the test area is established is as follows:
wherein Y is the cumulative production capacity data, S ', in the target oil well production data'1To normalized reservoir coefficients, a is the weight of the normalized reservoir coefficients, S'2Is a normalized fracture intensity coefficient, b is a weight of the normalized fracture intensity coefficient, S'3The normalized source rock coefficient is shown as c, the weight of the normalized source rock coefficient is shown as d, d is a constant, Q is the average daily oil yield of the target oil well, and T is the production days.
In the step (2), the accumulated capacity data in the production data of the target oil well is the accumulated capacity of the target oil well in the same natural time period.
And the accumulated capacity of the target oil well in the same natural time period is the accumulated oil production of the target oil well in the natural time periods of 90 days, 180 days and 1 year.
Specifically, in the step (3), the normalized geological characterization parameters of the target oil well, including the normalized reservoir coefficient, the normalized fracture intensity coefficient and the normalized hydrocarbon source rock coefficient, are input into the capacity prediction model of the target oil well, so as to obtain the predicted capacity data of the target oil well. The predicted capacity data for the target well includes predicted cumulative oil production and average daily oil production data for the target well.
Specifically, in the step (4), according to the predicted accumulated oil production data of the target oil well, the accumulated oil production prediction contour map of the target oil well is determined through an interwell difference method, and according to the predicted average daily oil production data of the target oil well, the average daily oil production prediction contour map of the target oil well is determined through the interwell difference method.
Specifically, in the step (5), the development and selection area standard of the test area is set as a single-well technical-economic threshold value under different oil prices, a single-well abandonment yield threshold is used as the accumulated oil yield lower limit of the target oil well, and a single-well initial yield threshold is used as the average daily oil yield lower limit of the target oil well.
In the step (5), the development selection range of the test area comprises a region on the cumulative oil yield prediction contour map of the target oil well, which is larger than the single-well abandoned production limit, or a region on the average daily oil yield prediction contour map of the target oil well, which is larger than the single-well initial production limit.
In the step (5), when the development and selection are carried out according to the average daily oil yield prediction contour map of the target oil well, the capacity data in the statistical production data of the target oil well are all the production data in the previous 180 days; and when the development and selection are carried out according to the contour map of the cumulative oil production of the target oil well, the limitation of the production days is avoided.
Specifically, the target oil well is not affected by flooding, fracturing abnormity and well track abnormity, and the accumulated production time of the target oil well is more than or equal to 1 year.
One specific example is listed below:
in the embodiment, the key geological parameters of the tight sandstone oil reservoir are optimized, the quantitative relation between the geological characterization parameters and the target oil well productivity is constructed, the target oil well productivity distribution condition of the test area is predicted, the tight oil development selection area range is determined by combining the development selection area standard, and the technical support is provided for improving the drilling success rate of the tight oil high-yield oil well and realizing the effective development of the tight oil high-yield oil well.
(1) Establishing geological characterization parameters of a target oil well (horizontal well) in a test area, wherein the geological characterization parameters comprise matrix reservoir coefficients for characterizing a matrix reservoir, fracture strength coefficients for characterizing fractures and hydrocarbon source rock coefficients for characterizing reservoir oiliness
At present, a tight sandstone reservoir is mainly developed by drilling a horizontal well, and numerous geological factors influencing the productivity of the horizontal well are provided (as shown in fig. 2, A is the starting point of the horizontal section of the horizontal well, B is the end point of the horizontal section of the horizontal well, the distance between the points A and B is the length L (the length of a sand body drilled by a target oil well) of the horizontal section of the horizontal well, H is the thickness of a hydrocarbon source rock, and H is the thickness of a sand body of a target stratum), wherein geological parameters related to a matrix reservoir comprise the thickness of the sand body, the length and the average porosity of the sand body drilled by the horizontal well, and geological parameters related to fractures comprise the porosity of the fractures and the; because the interpretation error of oil-bearing logging of tight sandstone oil reservoirs is large, the oil-bearing performance of the reservoir is represented by using the hydrocarbon source rock parameters, and the related geological parameters comprise the thickness of the hydrocarbon source rock and the content of Total Organic Carbon (TOC for short).
First, the matrix reservoir coefficient is calculated by the following formula:
S1＝L*H*φ (1)
in the formula, S1Is the matrix reservoir coefficient, L is the length of the target oil well drilling sand, H is the thickness of the target layer sand, and phi is the average porosity.
Specifically, the quality of the matrix reservoir of the horizontal well mainly comprises average porosity and sand thickness, wherein the sand thickness is divided into vertical sand thickness (target stratum sand thickness) and length of sand encountered by the horizontal well (target oil well sand length), and the average porosity and the sand thickness have positive correlation with the productivity of the horizontal well. In the embodiment, the volume of the reservoir controlled along the well trajectory and the properties of the reservoir are integrated by using the concept of well control reservoir volume, so that the matrix reservoir coefficient is established.
Secondly, the formula according to which the fracture strength parameters are determined is as follows:
S2＝φf*bf+nf(2)
wherein S is2Is the crack strength coefficient, phifIs the porosity of the crack, bfOpening of crack, nfIs the zone fracture strength, which is obtained by seismic or geostress simulation.
Specifically, the fracture strength parameters are primarily for natural fractures, without regard to artificial fractures. The horizontal well logging interpretation can obtain the fractures encountered by the horizontal well, and the fracture development degree is represented by the fracture opening and the fracture porosity of the logging interpretation. The horizontal well is fractured, the fractures can communicate with natural fractures around the horizontal well, and the fractures cannot be obtained from well logging explanation because the horizontal well is not drilled, but the fractures also influence the production condition of the horizontal well. Therefore, in the present embodiment, the crack strength n of the lead-in region is established when the crack strength is establishedf。nfThe method is used for expressing the rock failure proximity degree, and the value is a magnitude value obtained based on rock strength theory and is a comprehensive embodiment of the stress deformation of the rock body. The geological significance of the method is to indicate the relative development degree of rock mass fracture, and the larger the value of the method is, the more the crack develops. When n isfWhen the frequency is less than 1, the rock mass is stable, and the rock mass cannot be damaged and the instability cannot be damaged; when n isfWhen the value is more than or equal to 1, the rock body is unstable and obvious fracture is generated. In this example, n is usedfThe fracture development characteristics are approximately expressed as regional fracture development characteristics and can be obtained through earthquake or ground stress simulation.
Finally, the formula according to which the hydrocarbon source rock coefficient is determined is:
S3＝TOC*h (3)
in the formula, S3And the TOC is the total organic carbon content of the source rock at the position of the target oil well track, and h is the effective thickness of the source rock at the position of the target oil well track.
Specifically, the oil-water content of the tight sandstone reservoir is small in water-oil difference and strong in oil-containing heterogeneity, and the oil-containing saturation of the reservoir cannot be accurately calculated by means of well logging or earthquakes and the like at present. However, as the dense oil is near the source reservoir, the quality of the source rock near the reservoir directly determines the oil saturation of the reservoir, so the quality coefficient of the source rock is used to indirectly evaluate the oil saturation of the horizontal well, and the parameters determining the quality coefficient of the source rock include the total organic carbon content and the thickness of the high-quality source rock at the position of the horizontal well trajectory.
Specifically, taking a certain compact oil reservoir horizontal well a in an oil field in the south of the jaw as an example (as shown in fig. 3, GR is natural gamma, unit is gapi, DEPTH is DEPTH, LL8 is eight-lateral well logging, Ω · M is ILD for deep detection induction well logging, ILM is middle detection induction well logging, AC is acoustic moveout, unit is microsecond/meter, POR is porosity, SH is shale content, and SAND content is SAND content), length of a horizontal well drilling encountering SAND is 416M, length of an oil-containing effective reservoir is 102M, average porosity of an effective thickness section of the well is 8%, thickness of vertical SAND at the horizontal well a can be read from a region SAND thickness distribution diagram (as shown in fig. 4), thickness of a target layer SAND is 15M, and after calculation by using formula (1), a is aMatrix reservoir coefficient of horizontal well S1Is 122.28.
On the other hand, the change trend of the size of the fracture on the shaft and the thickness of the fracture section can be solved through conventional logging, namely the fracture strength of the logging interpretation is a function of the porosity of the fracture and the thickness of the fracture section, and the logging interpretation fracture strength of the horizontal well A is 0.69. And then, through the numerical simulation of the ground stress, the rock mass fracture development degree of the test area has different characteristic values in different areas, the fracture intersection area is 2.2, the single-group fracture area is 1.2, and the fracture non-development area is 0.7. The A horizontal well is positioned in a single group of fracture areas, and the fracture strength of the areas is 1.2. And (3) calculating by a formula (2), wherein the fracture strength coefficient S of the horizontal well A is 1.89 for explaining the accumulation of the fracture strength and the zone fracture strength for well logging.
Finally, the average (effective) thickness of the high-quality source rock at the position of the horizontal well A is 11 meters, the average TOC is 5.7, and the mass coefficient S of the source rock of the well is calculated by a formula (3)3It was 62.7.
(2) Respectively carrying out normalization processing on the geological characterization parameters of the target oil well to obtain normalized geological characterization parameters
The formula according to which the normalized geologic characterization parameters are obtained is:
S′i＝(Si-Si-min)/(Si-max-Si-min) (4)
of formula (II) S'iNormalized geological characterization parameters for the target well, where i is 1, 2 or 3, SiIs a geological characterization parameter of the target well, Si-maxFor the target well and SiMaximum value, S, in geological characterization parameters of the same typei-minFor the target well and SiMinimum value in geological characterization parameters of the same type.
Specifically, due to different geological environments, the geological characterization parameters (including matrix reservoir coefficients, fracture strength coefficients and hydrocarbon source rock coefficients) of different horizontal wells are greatly different and cannot be transversely compared with each other, so that the geological characterization parameters of each horizontal well are placed under the same reference system for processing. In this embodiment, the geological characterization parameters (including the matrix reservoir coefficient, the fracture intensity coefficient, and the source rock coefficient) in each horizontal well are normalized by the formula (4) to obtain normalized geological characterization parameters, including the normalized matrix reservoir coefficient, the normalized fracture intensity coefficient, and the normalized source rock coefficient.
Taking horizontal well A as an example, reservoir coefficient S after normalization1' 0.24, crack coefficient S2' 0.47, Source rock coefficient S3' is 0.48.
(3) Determining capacity data in target well production data
And preferably, establishing a horizontal well of the productivity prediction model as a target oil well. The productivity of the target oil well is the accumulated productivity of the horizontal well in the same natural time period, and can be the accumulated oil production in the natural time period of the first 90 days, the first 180 days or the first 1 year. The standard for determining the target oil well is as follows: the productivity of the horizontal well is not affected by flooding, fracturing abnormity and well track abnormity, and the accumulated production time exceeds 1 year.
In this example, there are 310 horizontal wells in which a tight oil reservoir in an oil field in the south of the jaw is co-produced, and 82 horizontal wells which meet the above criteria.
In this embodiment, the horizontal well a is a target well for preferably establishing the productivity prediction model, and the total oil production amount of 1301.4 tons in the first 90 days is taken.
(4) And (3) establishing a productivity prediction model of the target oil well in the test area, namely establishing a quantitative relation model between the productivity of the target oil well and the normalized geological characterization parameters.
The formula for establishing the productivity prediction model of the target oil well in the test area is as follows:
wherein Y is the cumulative production capacity data, S ', in the target oil well production data'1To normalized reservoir coefficients, a is the weight of the normalized reservoir coefficients, S'2Is a normalized fracture intensity coefficient, b is a weight of the normalized fracture intensity coefficient, S'3Is normalized source rock coefficient, c is weight of normalized source rock coefficient, d is constantAnd D, counting, Q is the average daily oil yield of the target oil well, and T is the production days.
In this embodiment, on the basis of normalization processing of the matrix reservoir coefficient, the hydrocarbon source rock coefficient, and the fracture intensity coefficient of the horizontal well with 82 ports in the tight oil block, a multivariate linear regression method is adopted to fit a correlation relationship with the oil yield accumulated in the first 90 days of the horizontal well, so as to obtain a productivity prediction model of the horizontal well based on geological parameters:
cumulative productivity Y of the horizontal well is 915.3S1′+1685.7*S2′+936.9*S3' -280.8; average daily oil production Q10.17S1′+18.73*S2′+10.41*S3' -3.12 (as shown in FIG. 4).
(5) And inputting the normalized geological characterization parameters of the target oil well into a productivity prediction model of the target oil well, and calculating to obtain the predicted accumulated oil yield and the average daily oil yield of the target oil well.
In the embodiment, the average daily oil yield predicted by the horizontal well is mainly used as a main index for developing and selecting the area. By normalizing geologic characterization parameters of horizontal wells, including normalized reservoir coefficients S1', normalized fracture Strength coefficient S2', normalized Source rock coefficient S3And', inputting a productivity prediction model of the target oil well, and calculating to obtain the average daily oil yield Q of the horizontal well.
(6) Determining a productivity prediction contour map of a target oil well in a test area, wherein the productivity prediction contour map comprises an accumulated oil production prediction contour map and an average daily oil production prediction contour map
In this embodiment, an average daily oil production prediction contour map of the horizontal well is compiled by an interwell difference method by using average daily oil production data of the horizontal well (as shown in fig. 5).
(7) And determining development and selection standards of the test area, including a cumulative oil production lower limit standard and an average daily oil production lower limit standard of the target oil well.
In this example, the economic threshold value of single well technology at different oil prices is used as the standard for developing the selected area, wherein the abandoned production limit of the single well is used as the lower limit of the cumulative oil production, and the initial production limit of the single well is used as the lower limit of the average daily oil production (as shown in table 1). The higher the oil price, the lower the single well abandonment production limit and the single well initial production limit; the lower the oil price, the higher the single well abandonment production limit and the single well initial production limit.
TABLE 1 initial single well production Limit as average daily oil production lower Limit
| International oil price dollar/barrel | Initial production limit per well, ton/day | Single well waste production limit of ten thousand tons |
| 50 | 20.7 | 1.32 |
| 60 | 15.92 | 1.08 |
| 70 | 13.00 | 0.92 |
| 80 | 11.51 | 0.83 |
| 90 | 10.3 | 0.76 |
In practice, the single well initial production limit is selected as the average daily oil production lower limit. When the oil price reaches $ 70/barrel, namely the initial production of a single well reaches 13 tons/day, the production well has development value and can realize profit.
(8) According to the target oil well productivity prediction contour map and the development selection area standard of the test area, determining the development selection area range of the test area
This embodiment requires the development of a selected zone spread, i.e., a zone on the cumulative oil production prediction contour that is greater than the single well abandonment production limit, or a zone on the average daily oil production prediction contour that is greater than the single well initial production limit. When the oil price is higher, the area range meeting the development and selection standard is larger; the lower the oil price, the smaller the area range that meets the development election criteria.
In actual operation, the area on the daily oil production prediction contour map larger than the 13 ton/day contour is the development selection area (as shown in fig. 6). For example, for a certain compact reservoir in an oil field in the south of the jaw, 7 regions (as shown in fig. 7) larger than 13 tons/day contour on the daily oil production prediction contour map are provided, and the 7 regions are all compact sandstone reservoir development favorable regions. Wherein, 2, 4 and 6 blocks are developed areas, 3 and 5 blocks are water-logging damaged areas, and the areas can not be developed again. 1. 7 blocks of predicted initial daily oil production are high, the number of drilling well positions is small at present, and decision basis is provided for developing a potential area and for next-step development of the tight sandstone oil reservoir as a final result of developing a selected area under the condition of the oil price of 70 dollars in the embodiment.
In this embodiment, when the average daily oil production prediction contour map is used for development and selection, the production data of the horizontal well required to be counted are all production data within 180 days before the oil well. When the cumulative oil production prediction contour map is used for development and selection, the method is not limited by the production days. The development and selection can also be carried out by utilizing the cumulative oil production prediction contour map and the area determined by the single well abandoned production limit.
Although the embodiments of the present invention have been described above, the above description is only for the convenience of understanding the present invention, and is not intended to limit the present invention. It will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (10)
1. A tight sandstone reservoir development and region selection method is characterized by comprising the following steps:
(1) obtaining a normalized geological characterization parameter according to the geological characterization parameter of the target oil well in the test area;
(2) establishing a productivity prediction model of the target oil well according to the productivity data in the production data of the target oil well and the normalized geological characterization parameters;
(3) acquiring the predicted capacity data of the target oil well according to the capacity prediction model of the target oil well;
(4) determining a capacity prediction contour map of the target oil well according to the predicted capacity data of the target oil well;
(5) and determining the development selection range of the test area according to the capacity prediction contour map of the target oil well and the development selection standard of the test area.
2. The tight sandstone reservoir development zoning method of claim 1, wherein in the step (1), the geological characterization parameters comprise matrix reservoir coefficients, fracture strength coefficients and source rock coefficients;
the matrix reservoir coefficients are determined according to the formula:
S1＝L*H*φ (1)
in the formula, S1Taking the matrix reservoir coefficient, L as the length of a target oil well drilling sand body, H as the thickness of the target layer sand body, and phi as the average porosity;
the formula according to which the fracture strength parameters are determined is:
S2＝φf*bf+nf(2)
in the formula, S2Is the crack strength coefficient, phifIs the porosity of the crack, bfOpening of crack, nfIs the regional crack strength;
the formula according to which the hydrocarbon source rock coefficient is determined is as follows:
S3＝TOC*h (3)
in the formula, S3And the TOC is the total organic carbon content of the source rock at the position of the target oil well track, and h is the effective thickness of the source rock at the position of the target oil well track.
3. The tight sandstone reservoir development zoning method of claim 1, wherein in the step (1), the normalized geological characterization parameters are obtained according to the formula:
S′i＝(Si-Si-min)/(Si-max-Si-min) (4)
of formula (II) S'iNormalized geological characterization parameters for the target well, where i is 1, 2 or 3, SiIs a geological characterization parameter of the target well, Si-maxFor the target well and SiMaximum value, S, in geological characterization parameters of the same typei-minFor the target well and SiMinimum value in geological characterization parameters of the same type.
4. The tight sandstone reservoir development zoning method of claim 1, wherein in the step (2), the productivity data of the production data of the target oil well is determined as a dependent variable, the normalized geological characterization parameter of the target oil well is an independent variable, and a productivity prediction model of the target oil well in the test zone is established through multiple linear regression;
the formula for establishing the productivity prediction model of the target oil well in the test area is as follows:
wherein Y is the cumulative production capacity data, S ', in the target oil well production data'1To normalized reservoir coefficients, a is the weight of the normalized reservoir coefficients, S'2Is a normalized fracture intensity coefficient, b is a weight of the normalized fracture intensity coefficient, S'3For normalizing the source rock coefficients, c is normalizationAnd d is a constant, Q is the average daily oil yield of the target oil well, and T is the production days.
5. The tight sandstone reservoir development zoning method of claim 4, wherein, in the step (2), the cumulative capacity data in the production data of the target well is the cumulative capacity of the target well in the same natural time period.
6. The tight sandstone reservoir development zoning method according to claim 1, wherein in the step (3), the normalized geological characterization parameters of the target oil well are input into the capacity prediction model of the target oil well, so as to obtain the predicted capacity data of the target oil well; the normalized geologic characterization parameters include a normalized reservoir coefficient, a normalized fracture intensity coefficient, and a normalized source rock coefficient; the predicted capacity data of the target oil well comprises predicted cumulative oil production and average daily oil production data.
7. The tight sandstone reservoir development zoning method of claim 6, wherein in the step (4), the cumulative oil production prediction contour map of the target oil well is determined by an interwell difference method according to the predicted cumulative oil production data of the target oil well, and the average daily oil production prediction contour map of the target oil well is determined by an interwell difference method according to the predicted average daily oil production data of the target oil well.
8. The tight sandstone reservoir development zonal method of claim 7, wherein in the step (5), the development zonal standard of the test zone is set as a single-well technical-economic threshold value at different oil prices, the single-well abandonment production limit is used as the cumulative oil production lower limit of the target oil well, and the single-well initial production limit is used as the average daily oil production lower limit of the target oil well.
9. The tight sandstone reservoir development zonal method of claim 8, wherein, in the step (5), the development zonal range of the test zone comprises an area on the cumulative oil production prediction contour map of the target oil well which is greater than the single-well abandonment production limit,
or a region on the predicted contour plot of average daily oil production for the target well that is greater than the initial production limit for a single well.
10. The tight sandstone reservoir development zoning method according to claim 9, wherein in the step (5), when development zoning is performed according to the average daily oil production prediction contour map of the target oil well, the statistical capacity data in the production data of the target oil well are all the production data in the previous 180 days; and when the development and selection are carried out according to the contour map of the cumulative oil production of the target oil well, the limitation of the production days is avoided.
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| US20180252627A1 (en) * | 2017-03-01 | 2018-09-06 | Proptester, Inc. | Fracture Fluid And Proppant Transport Testing Systems And Methods Of Using Same |
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