Classification and Prediction Method for Development Indicators of Offshore Water-Drive Sandstone Oil Reservoirs

Abstract

This invention relates to a method for classifying and predicting development indicators for offshore water-driven sandstone reservoirs. The steps include: classifying producing offshore water-driven sandstone reservoirs based on sedimentary basins, oil-bearing strata, sedimentary facies, crude oil viscosity, and reservoir permeability; establishing recovery rate prediction formulas for different types of offshore water-driven sandstone reservoirs based on parameters of producing reservoirs; establishing peak production rate evaluation charts for different types of offshore water-driven sandstone reservoirs; defining and calculating decline characteristic parameters for different types of reservoirs; determining the type of newly discovered reservoirs; calculating the reasonable well density for newly discovered reservoirs; calculating the recovery rate, peak production rate, and decline characteristic parameters based on the type of newly discovered reservoirs; and iteratively calculating the annual oil production profile of newly discovered offshore water-driven sandstone reservoirs. This provides a method for classifying and predicting development indicators based on the systematic classification of offshore water-driven sandstone reservoirs and big data analysis of producing reservoirs, enabling rapid prediction of development indicators during the target pre-exploration, exploration evaluation, and reserve evaluation stages.

Description

Technical Field

[0001] This invention relates to the field of offshore oil and gas extraction technology, specifically to a method for classifying and predicting development indicators of offshore water-driven sandstone oil reservoirs. Background Technology

[0002] With the increasing level of offshore exploration and development, it is becoming increasingly difficult to discover large and medium-sized integrated oil and gas reservoirs that are shallow, have low technical requirements, are easy to develop, and have good economic benefits. Exploration targets are gradually shifting towards small structural traps, stratigraphic traps, and lithological traps. Oil and gas field types are changing from conventional reservoirs to areas with low abundance, low permeability, and heavy oil. Compared to onshore oilfield exploration and development, offshore water-driven sandstone reservoirs are characterized by high investment, high risk, and high technical requirements. Therefore, making reasonable predictions of development indicators as early as possible during the target pre-exploration, exploration evaluation, and reserve evaluation stages is a crucial foundation for the initial economic assessment of offshore oilfield development projects and an important basis for deciding whether to initiate the next stage of evaluation work and even the preparation of a formal development plan. Currently, the prediction of development indicators for offshore water-driven sandstone reservoirs during the target pre-exploration, exploration evaluation, and reserve evaluation stages is mainly determined based on reservoir analogy and oilfield empirical formulas. The reservoir analogy method theoretically requires that the assessed reservoir and the analogous reservoir be geographically adjacent and have similar sedimentary environments, lithology, fluids, reservoir properties, development methods, and well patterns. However, in practice, it is difficult to find completely similar reservoirs, necessitating adjustments to development indicators based on expert experience and analogy, thus introducing a degree of subjectivity. The empirical formula method currently mainly draws on empirical methods for predicting development indicators in onshore oilfields. It considers three quantifiable factors—fluid properties, reservoir properties, and well density—based on development methods and lithological differences to predict development indicators. However, it lacks sufficient consideration of qualitative aspects such as sedimentary basins, oil-bearing strata, and sedimentary facies. Currently, a systematic classification and prediction method for development indicators of offshore water-driven sandstone reservoirs has not yet been developed for the target pre-exploration, exploration evaluation, and reserve evaluation stages. Therefore, a systematic reservoir classification method is needed for offshore water-driven sandstone reservoirs. Based on this, through big data analysis of offshore producing reservoirs, a comprehensive development index classification and prediction method should be developed that considers multiple factors such as sedimentary basins, oil-bearing strata, sedimentary facies, fluid characteristics, reservoir properties, and well density. This will improve the reliability of development index predictions for offshore water-driven sandstone reservoirs in the target pre-exploration, exploration evaluation, and reserve evaluation stages, and provide a reliable basis for the preliminary economic evaluation of offshore water-driven reservoir development projects. Summary of the Invention

[0003] To address the aforementioned issues, this invention provides a classification and prediction method for development indicators of offshore water-driven sandstone reservoirs. This method is applicable to offshore sandstone reservoirs that are developed using water injection and pressure maintenance before the formal development plan research is initiated (target pre-exploration, exploration evaluation, and reserve evaluation stages).

[0004] To achieve the above objectives, the present invention adopts the following technical solution: a method for classifying and predicting development indicators of offshore water-driven sandstone oil reservoirs, comprising:

[0005] Step 1: Classify offshore water-driven sandstone reservoirs based on sedimentary basins, oil-bearing strata, sedimentary facies, formation conditions, average crude oil viscosity, and average reservoir permeability;

[0006] Step 2: Based on the classification results of water-driven sandstone reservoirs in Step 1, establish recovery prediction models for different types of offshore water-driven sandstone reservoirs according to reservoir type.

[0007] Step 3: Based on the classification results of water-driven sandstone reservoirs in Step 1, establish peak production rate evaluation charts for different types of offshore water-driven sandstone reservoirs according to reservoir type;

[0008] Step 4: Define reservoir decline characteristic parameters. Based on the classification results of producing water-driven sandstone reservoirs in Step 1 and the production profile of primary well networks for different types of producing water-driven sandstone reservoirs, calculate the decline characteristic parameters of different types of reservoirs.

[0009] Step 5: Statistically analyze the static geological parameters of the newly discovered offshore water-driven sandstone oil reservoirs, and determine the type of the newly discovered offshore water-driven sandstone oil reservoirs based on the principles in Step 1.

[0010] Step 6: Based on the newly discovered offshore water-driven sandstone reservoir type obtained in Step 5, calculate the average well-controlled reserves of the same type of offshore water-driven sandstone reservoir in production. Calculate the required number of development wells and the reasonable well density based on the average well-controlled reserves and the geological reserves of the newly discovered offshore water-driven sandstone reservoir.

[0011] Step 7: Based on the reasonable well network density and static parameters of the newly discovered offshore water-driven sandstone reservoir in Step 6, select the recovery rate prediction model of the same type as the newly discovered offshore water-driven sandstone reservoir from Step 2 to calculate the recovery rate of the newly discovered offshore water-driven sandstone reservoir;

[0012] Step 8: Select the peak oil recovery rate evaluation chart from Step 3 that is the same type as the newly discovered offshore water-driven sandstone reservoir as the basis for calculating the peak oil recovery rate of the newly discovered offshore water-driven sandstone reservoir;

[0013] Step 9: Based on the decline characteristic parameters of different types of offshore water-driven sandstone reservoirs in Step 4, select the reservoir decline characteristic parameters that are the same as the newly discovered offshore water-driven sandstone reservoir type as the decline characteristic parameters of the newly discovered offshore water-driven sandstone reservoir.

[0014] Step 10: Based on the decline characteristic parameters of the newly discovered offshore water-driven sandstone reservoir in Step 9, the recovery rate of the newly discovered offshore water-driven sandstone reservoir in Step 7, and the peak production rate of the newly discovered offshore water-driven sandstone reservoir in Step 8, iteratively calculate the annual oil production profile of the newly discovered offshore water-driven sandstone reservoir.

[0015] The present invention has the following advantages due to the adoption of the above technical solutions:

[0016] 1. This invention provides for the first time a method for classifying and predicting development indicators based on the classification of offshore water-driven sandstone reservoir systems and big data analysis of offshore producing reservoirs, which can realize rapid prediction of development indicators for offshore water-driven sandstone reservoirs in the target pre-exploration, exploration evaluation or reserve evaluation stages.

[0017] 2. The method of the present invention avoids the shortcomings of conventional analogy methods in prediction, which are affected by subjective experience, and empirical formula methods, which do not adequately consider qualitative factors such as sedimentary basins, oil-bearing strata, and sedimentary facies, thus improving the rationality and reliability of the prediction.

[0018] 3. The method of the present invention can update the development parameters and related fitting coefficients in real time according to the actual dynamic changes in the development of producing oil reservoirs. The technical method is convenient, fast, highly applicable and highly reliable.

[0019] 4. This invention is not only applicable to offshore water-driven sandstone reservoirs, but can also provide a reference for the prediction of development indicators for other types of offshore reservoirs, such as offshore edge-bottom water-driven sandstone reservoirs. Attached Figure Description

[0020] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Throughout the drawings, the same reference numerals denote the same parts. In the drawings:

[0021] Figure 1A These are evaluation charts of peak oil recovery rates for different types of offshore water-driven sandstone reservoirs according to embodiments of this application;

[0022] Figure 1B These are evaluation charts of peak oil recovery rates for different types of offshore water-driven sandstone reservoirs according to embodiments of this application;

[0023] Figure 2A These are the annual production profile prediction results of different types of offshore water-driven sandstone oil reservoirs according to embodiments of this application; and

[0024] Figure 2B These are the annual production profile prediction results of different types of offshore water-driven sandstone oil reservoirs according to embodiments of this application. Detailed Implementation

[0025] Exemplary embodiments of the invention will now be described in more detail 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 implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided to enable a more thorough understanding of the invention and to fully convey the scope of the invention to those skilled in the art.

[0026] According to some embodiments of this application, a method for classifying and predicting development indicators of offshore water-driven sandstone oil reservoirs is proposed, including the following steps:

[0027] 1) Based on the average crude oil viscosity of the reservoir under the conditions of sedimentary basin, oil-bearing strata, sedimentary facies, and stratigraphy. m o Average permeability of the reservoir K o Classify offshore water-driven sandstone oil reservoirs that are in production.

[0028] 2) Based on the classification results of water-driven sandstone reservoirs in step 1), establish recovery rate prediction formulas for different types of offshore water-driven sandstone reservoirs according to reservoir type;

[0029] 3) Based on the classification results of water-driven sandstone reservoirs in step 1), establish peak production rate evaluation charts for different types of offshore water-driven sandstone reservoirs according to reservoir type;

[0030] 4) Define reservoir decline characteristic parameters. Based on the classification results of producing water-driven sandstone reservoirs in step 1) and the production profiles of primary well networks for different types of producing water-driven sandstone reservoirs, calculate the decline characteristic parameters for different types of reservoirs. D D ;

[0031] 5) Statistical analysis of the geological static parameters of newly discovered offshore water-driven sandstone oil reservoirs, including sedimentary basins, oil-bearing strata, sedimentary facies, and average crude oil viscosity under formation conditions. m n Average permeability of the reservoir K n Based on the classification method in step 1), the newly discovered offshore water-driven sandstone oil reservoirs are classified.

[0032] 6) Based on the newly discovered offshore water-driven sandstone reservoir type obtained in step 5), calculate the average well-controlled reserves of producing offshore water-driven sandstone reservoirs of the same type as the newly discovered water-driven sandstone reservoir. N wave Based on average well-controlled reserves N wave The number of development wells required to calculate the geological reserves of newly discovered offshore water-driven sandstone oil reservoirs. W o and reasonable well densityF n ;

[0033] 7) Based on the reasonable well density and static parameters of the newly discovered offshore water-driven sandstone reservoir in step 6), select the same recovery rate prediction formula as the newly discovered water-driven sandstone reservoir type from step 2) to calculate the recovery rate of the newly discovered offshore water-driven sandstone reservoir. E Rn ;

[0034] 8) From step 3), select a peak production rate evaluation chart that is the same type as the newly discovered offshore water-driven sandstone reservoir as the basis for calculating the peak production rate of the newly discovered offshore water-driven sandstone reservoir. R maxn ;

[0035] 9) Based on the decline characteristic parameters of different types of offshore water-driven sandstone reservoirs in step 4), D D The decline characteristic parameters of the newly discovered offshore water-driven sandstone oil reservoirs were selected as the decline characteristic parameters of the newly discovered offshore water-driven sandstone oil reservoirs. D Dn ;

[0036] 10) Based on the newly discovered decline characteristic parameters of offshore water-driven sandstone reservoirs in step 9). D Dn Step 7) Newly discovered offshore water-driven sandstone oil reservoir recovery rate E Rn Step 8) The newly discovered offshore water-driven sandstone oil reservoir has a peak oil production rate R maxn Iterative calculations were performed to obtain the annual oil production profile of newly discovered offshore water-driven sandstone oil reservoirs.

[0037] The classification and prediction method, preferably, in step 1), refers to the reservoir average crude oil viscosity under formation conditions. m o Average permeability of the reservoir K o The calculation methods and classification methods for offshore water-driven sandstone reservoirs in production are as follows:

[0038] (1)

[0039] (2)

[0040] In the formula, N j Oil reservoir reserve calculation unit j Geological reserves, 10,000 cubic meters; m The number of reservoir reserve calculation units included in the utilized reserves; The average crude oil viscosity in the reservoir under formation conditions, in mPa.. s; m oj Oil reservoir reserve calculation unit j Crude oil viscosity under formation conditions, mPa . s; K o The mean permeability of the reservoir is expressed in mD. Oil reservoir reserve calculation unit j The penetration rate, mD.

[0041] The classification of offshore water-driven sandstone reservoirs mainly considers sedimentary basins, oil-bearing strata, sedimentary facies, crude oil viscosity, and reservoir permeability. The specific classification methods are as follows:

[0042] Classification method of offshore water-drive sandstone reservoirs

[0043]

[0044] In the table, offshore oilfield sedimentary basins mainly include the Beibu Gulf Basin, the Pearl River Estuary Basin, and the Bohai Bay Basin, which is common knowledge in the field of offshore oil and gas extraction technology. Oil-bearing strata refer to the stratigraphic age of offshore water-driven sandstone reservoirs, mainly classified into Paleogene and Neogene based on their production status. Sedimentary facies are divided into seven categories based on the production status of offshore water-driven sandstone reservoirs: fluvial facies, shallow-water deltaic facies, deltaic facies, fan deltaic facies, lacustrine facies, platform facies, and littoral-shallow marine facies. All categories are professional terms in the field of oil and gas extraction technology. Crude oil viscosity refers to the viscosity of crude oil under formation conditions. Reservoirs with crude oil viscosity greater than 50 mPa·s under formation conditions are classified as heavy oil, and those with crude oil viscosity less than 50 mPa·s are classified as medium-low viscosity crude oil. Reservoirs with permeability less than 50 mD are classified as low-permeability reservoirs, and those with permeability greater than 50 mD are classified as medium-high permeability reservoirs.

[0045] Step 2) involves establishing recovery prediction formulas for different types of offshore water-drive sandstone reservoirs based on reservoir type.

[0046] Statistics on the recovery rate after the implementation of a primary well network development plan for producing water-drive sandstone oil reservoirs at sea. E Ro Average porosity of the reservoir f o Average crude oil viscosity in reservoirs under formation conditions m o (Calculation method as shown in equation (1)), average permeability of the reservoir K o (Calculation method as shown in formula (2)), well network density F o According to step 1), the reservoir types are respectively fitted using the relevant formulas. E R = a+ b ×log( K o / m o )+ c × f o +d × F o Coefficient identification was performed for different types of reservoirs, among which... a、b、c、d The fitting coefficients are required to be no less than 0, thus establishing a formula for predicting the recovery rate of different types of offshore water-driven sandstone reservoirs.

[0047] Among them, the average porosity of the oil reservoir f o and well network density F o The calculation method is as follows:

[0048] (3)

[0049] (4)

[0050] In the formula, f o The average porosity of the reservoir is a decimal. f oj Oil reservoir reserve calculation unit j Porosity, decimal; N j Oil reservoir reserve calculation unit j Geological reserves, 10,000 cubic meters; m The number of reservoir reserve calculation units included in the utilized reserves; F o The reservoir well network density is expressed in wells per km. 2 ; W d The number of directional wells; W h The total number of horizontal and branch wells; A For the overlapping oil-bearing area of ​​the active zone, km 2 .

[0051] The aforementioned classification and prediction method, preferably, involves the following method in step 3) for establishing peak oil recovery rate evaluation charts for different types of offshore water-driven sandstone reservoirs:

[0052] ①Statistical analysis of the recovery rate after the implementation of the primary well network development plan for offshore water-drive sandstone oil reservoirs E Ro Peak oil production rate R maxo And calculate reservoir mobility M= K o / m o ;

[0053] ②Draw the peak production rate of different types of producing reservoirs according to reservoir type. R max With reservoir mobility M The scatter plot after taking the logarithm was fitted using the fitted relationship. R max = e ×log( M)+g Perform coefficient identification and calculate the squared correlation coefficient R. 2 (1), where e、g These are the fitting coefficients;

[0054] ③ Draw different types of producing reservoirs (peak production rate) according to reservoir type. R max / Reservoir recovery rate E Ro ) With reservoir mobility M The scatter plot after taking the logarithm is used to fit the relationship ( R max / E Ro )= e ×log( M ) +g Perform coefficient identification and calculate the squared correlation coefficient R. 2 (2);

[0055] ④If R 2 (1)>R 2 (2) Then adopt R max with log( M The relationship is used as a chart to evaluate the peak production rate of this type of reservoir; if R 2 (1) <R 2 (2), then adopt ( R max / E Ro ) and log( M This serves as a chart for evaluating the peak production rate of this type of reservoir.

[0056] The classification and prediction method, preferably, includes the decline characteristic parameters of different types of offshore water-driven sandstone reservoirs in step 4). D D The definition and calculation method are as follows:

[0057] (5)

[0058] (6)

[0059] In the formula, The first as defined in this invention patent k The characteristic parameters of the decline in offshore water-driven sandstone reservoirs of this type are dimensionless. L Indicates the first k The number of offshore water-driven sandstone reservoirs of this type; Indicates the first k Type No. l One dimensionless characteristic parameter for the decline of offshore water-driven sandstone oil reservoirs; Indicates the first k Type No. l The Arps index decline rate of the first stage of a water-driven sandstone reservoir in production, annually -1 ; Indicates the first k Type No. l The Arps index decline rate in the second stage of a producing offshore water-driven sandstone reservoir, annually. -1 The Arps index decrease rate is common knowledge in the field of oil and gas extraction technology.

[0060] The aforementioned classification and prediction method, preferably, involves the average well-controlled reserves in producing offshore water-driven sandstone reservoirs of the same type as newly discovered reservoirs in step 6). N wave Number of development wells required for new oil reservoirs W o and reasonable well density F n The calculation method is as follows:

[0061] (7)

[0062] (8)

[0063] (9)

[0064] In the formula, The average well-controlled reserves of offshore water-driven sandstone reservoirs of the same type as the newly discovered reservoirs, in 10,000 cubic meters per reservoir; L This indicates the number of producing offshore water-driven sandstone reservoirs of the same type as the newly discovered reservoir; Indicating newly discovered oil reservoirs of the same type l The well-controlled reserves of a single offshore water-driven sandstone oil reservoir are 10,000 cubic meters per well. W o Number of development wells required for newly discovered offshore water-drive sandstone oil reservoirs (wells / km) 2 ; F nTo determine the optimal well density for newly discovered offshore water-driven sandstone oil reservoirs, the well density is calculated as follows: wells per km. 2 ; N in The utilized reserves of the newly discovered offshore water-driven sandstone oil reservoir are 10,000 cubic meters. A n The superimposed oil-bearing area of ​​the newly discovered offshore water-drive sandstone oil reservoir is measured in km². 2 .

[0065] The classification and prediction method, preferably, involves the peak oil production rate of newly discovered offshore water-driven sandstone oil reservoirs in step 8). R maxn The calculation method is as follows:

[0066] ①Based on step 5), the viscosity of crude oil under the subsurface conditions of the newly discovered oil reservoirs is statistically analyzed. m n reservoir permeability K n Calculate the mobility of the new reservoir M n= K n / m n :

[0067] ② From step 3), select the same chart type as the newly discovered reservoir to evaluate the peak oil production rate of the different types of offshore water-driven sandstone reservoirs. R maxn If the image is R max with log( M Relationship diagram ， Based on the new reservoir mobility M n Using the formula in step 3) R maxn = e ×log( M n ) +g Calculate peak oil production rate R maxn If the diagram is ( R max / E Ro ) and log( M Relationship diagram ， Based on the new reservoir mobility M n Using the formula in step 3) R max / E Ro ) n = e×log( M n ) +g Calculate the ratio of peak oil production rate to reservoir recovery rate in a new oil reservoir. R max / E Ro ) n Then utilize the recovery rate of the new reservoir in step 7). E Rn Calculate peak oil recovery R maxn =( R max / E Ro ) n × E Rn .

[0068] The classification and prediction method, preferably, involves the following method for calculating the annual oil production profile of newly discovered offshore water-driven sandstone oil reservoirs in step 10):

[0069] ①Based on the newly discovered oil reservoir's recoverable reserves N in And the recovery rate of newly discovered oil reservoirs in step 7) E Rn Calculate the identified recoverable reserves of the reservoir N R = N in × E Rn .

[0070] ②Based on the number of development wells required for the newly discovered offshore water-drive sandstone oil reservoirs in step 6). W o Assess the time required for the reservoir to reach peak production rate. W o The time required to reach peak oil production rate is 2 years when the oil production rate is ≤20; when W o > It will take 3 years to reach peak oil production rate at 20:00.

[0071] ③ Calculate the annual oil production before the reservoir reaches peak production rate. If the time required to reach peak production rate is 2 years, the annual oil production in the first year is: P (1)= R maxn × N in / 2, the annual oil production in the second year is P (2)= R maxn × N inIf it takes 3 years to reach peak oil production rate, the annual oil production in the first year will be: P (1)= R maxn × N in / 3, the annual oil production in the second year is P (2)= R maxn × N in / 3×2, the annual oil production in the third year is P (3)= R maxn × N in ;

[0072] ④ Given initial values ​​for the two decline rates of the newly discovered reservoir. The initial decline rate for the first stage is given as follows: D 1n (0), based on the newly discovered reservoir characteristic parameters in step 9) D Dn Calculate the initial value of the second decreasing segment. D 2n (0)= D 1n (0) / D Dn ;

[0073] ⑤ Calculate the annual oil production profile after reaching peak production rate. If the time required to reach peak production rate is 2 years, then the annual oil production from year 3 to year 11 is... P ( y )= P ( y -1)×ln(- D 1n (0)), while the annual oil production from year 12 to year 20 was P ( y )= P ( y -1)×ln(- D 2n (0)); If the time required to reach peak oil production rate is 3 years, then the annual oil production from year 4 to year 11 is P ( y )= P ( y -1)×ln(- D 1n (0)), while the annual oil production from year 12 to year 20 was P ( y )= P ( y -1)×ln(- D2n (0)); where y Indicates the production period in years.

[0074] ⑥ Iteratively calculate the annual oil production until the total annual oil production reaches the recoverable reserves specified in ①. N R The total cumulative oil production is calculated based on the annual oil production figures in sections ③ and ⑤. To determine whether the target recoverable reserves have been reached, if... Then the annual oil production is P ( y );like and Then update the first segment's decrease rate to... D 1n ( k )= D 1n (0)+0.0005. Repeat steps ① to ⑥ until the condition is met. ;like and Then update the initial decrease rate of the first segment to: D 1n ( k )= D 1n (0)-0.0005 Repeat steps ① to ⑥ until the condition is met. .

[0075] According to some embodiments of this application, a method for classifying and predicting development indicators of offshore water-drive sandstone oil reservoirs is provided, including the following steps:

[0076] 1. Based on the average crude oil viscosity of the reservoir under the conditions of sedimentary basin, oil-bearing strata, sedimentary facies, and formation. m o Average permeability of the reservoir K o Offshore water-driven sandstone oil reservoirs are classified. Among these classifications, the average crude oil viscosity under formation conditions is considered. m o Average permeability of the reservoir K o The calculation methods and classification methods for offshore water-driven sandstone reservoirs in production are shown in Equations (1) and (2).

[0077] Offshore water-driven sandstone reservoirs are classified primarily based on sedimentary basins, oil-bearing strata, sedimentary facies, crude oil viscosity, and reservoir permeability. Crude oil viscosity refers to the viscosity of crude oil under formation conditions. Reservoirs with a viscosity greater than 50 mPa·s under formation conditions are classified as heavy oil, while those with a viscosity less than 50 mPa·s are classified as medium-low viscosity crude oil. Similarly, reservoirs with a permeability less than 50 mD are classified as low-permeability reservoirs, while those with a permeability greater than 50 mD are classified as medium-high permeability reservoirs.

[0078] Taking the R oil reservoir in production as an example, this reservoir is located in Basin A, the oil-bearing strata are Paleogene, the sedimentary facies are deltaic, the average crude oil viscosity under the formation conditions is 4.6 mPa·s, and the average permeability is 1312 mD. According to the classification method, this oil reservoir belongs to the low viscosity and medium permeability oil reservoir of the Paleogene deltaic facies in Basin A.

[0079] 2. Based on the reservoir classification results in step 1), establish recovery prediction formulas for different types of offshore water-driven sandstone reservoirs according to reservoir type. The specific process is as follows:

[0080] Statistics on the recovery rate after the implementation of a primary well network development plan for producing water-drive sandstone oil reservoirs at sea. E Ro Average porosity of the reservoir f o Average crude oil viscosity in reservoirs under formation conditions m o (Calculation method as in step 1) Average reservoir permeability K o (Calculation method as in step 1) Well pattern density F o According to step 1), the reservoir types are respectively fitted using the relevant formulas. E R = a + b ×log( K o / m o )+ c × f o +d × F o Coefficient identification was performed for different types of reservoirs, among which... a、b、c、d The fitting coefficients are required to be no less than 0, thus establishing a formula for predicting the recovery rate of different types of offshore water-driven sandstone reservoirs.

[0081] Among them, the average porosity of the oil reservoir f o and well network density F o The calculation methods are as shown in equations (3) and (4).

[0082] Taking two reservoir types as examples, the recovery prediction formulas for different types of offshore water-drive sandstone reservoirs are as follows:

[0083] Table 1. Formulas for predicting the recovery rate of different types of offshore water-driven sandstone reservoirs.

[0084]

[0085] 3. Based on the reservoir classification results in step 1), establish peak production rate evaluation charts for different types of offshore water-driven sandstone reservoirs according to reservoir type. The specific method for establishing these charts is as follows:

[0086] ①Statistical analysis of the recovery rate after the implementation of the primary well network development plan for offshore water-drive sandstone oil reservoirs E Ro Peak oil production rate R maxo And calculate reservoir mobility M = K o / m o ;

[0087] ② Plot the peak oil production rate of different types of producing reservoirs according to reservoir type. R max With reservoir mobility M The scatter plot after taking the logarithm was fitted using the fitted relationship. R max = e ×log( M)+g Perform coefficient identification and calculate the squared correlation coefficient R. 2 (1), where e、g These are the fitting coefficients;

[0088] ③ Draw different types of producing reservoirs (peak production rate) according to reservoir type. R max / Reservoir recovery rate E Ro ) With reservoir mobility M The scatter plot after taking the logarithm is used to fit the relationship ( R max / E Ro )= e ×log( M ) +g Perform coefficient identification and calculate the squared correlation coefficient R. 2 (2);

[0089] ④If R 2 (1)>R 2 (2) Then adopt R max with log( M The relationship is used as a chart to evaluate the peak production rate of this type of reservoir; if R 2 (1) <R 2 (2), then adopt ( R max / E Ro ) and log(M This serves as a chart for evaluating the peak production rate of this type of reservoir.

[0090] Taking two reservoir types as examples, the peak oil recovery rate evaluation diagrams for different types of offshore water-driven sandstone reservoirs are shown below. Figure 1A and Figure 1B As shown.

[0091] 4. Define reservoir decline characteristic parameters. Based on the reservoir classification results in step 1) and the production profiles of different types of primary well networks in producing reservoirs, calculate the decline characteristic parameters for different types of reservoirs. D D The decreasing feature parameter D D The definitions and calculation methods are as shown in equations (5) and (6).

[0092] Taking two reservoir types as examples, the decline characteristic parameters of different types of offshore water-driven sandstone reservoirs are as follows:

[0093] Table 2. Decline characteristic parameters of different types of offshore water-driven sandstone reservoirs

[0094]

[0095] 5. Statistical analysis of the static geological parameters of newly discovered offshore water-driven sandstone oil reservoirs, including sedimentary basins, oil-bearing strata, sedimentary facies, and average crude oil viscosity under formation conditions. m n Average permeability of the reservoir K n Based on the classification principles in step 2), the newly discovered offshore water-driven sandstone reservoirs are then categorized.

[0096] 6. Based on the newly discovered offshore water-drive sandstone reservoir type obtained in step 5), calculate the average well-controlled reserves of producing offshore water-drive sandstone reservoirs of the same type as the newly discovered reservoir. N wave Based on average well-controlled reserves N wave The number of development wells required to calculate the geological reserves of newly discovered offshore water-driven sandstone oil reservoirs. W o and reasonable well density F n The specific calculation methods are shown in equations (7), (8) and (9).

[0097] Taking two reservoir types as examples, the average well-controlled reserves of different types of offshore water-drive sandstone reservoirs are as follows:

[0098] Table 3. Average well-controlled reserves data for different types of offshore water-driven sandstone reservoirs.

[0099]

[0100] 7. Based on the reasonable well density and static parameters of the newly discovered reservoir in step 6), select the same recovery rate prediction formula as the newly discovered reservoir type from step 2) to calculate the recovery rate of the newly discovered offshore water-drive sandstone reservoir. E Rn ;

[0101] 8. From step 3), select the peak production rate evaluation chart that is the same type as the newly discovered reservoir as the basis for calculating the peak production rate of the newly discovered offshore water-drive sandstone reservoir. R maxn The specific calculation process is as follows:

[0102] ①Based on step 5), the viscosity of crude oil under the subsurface conditions of the newly discovered oil reservoirs is statistically analyzed. m n reservoir permeability K n Calculate the mobility of the new reservoir M n= K n / m n :

[0103] ② From step 3), select the same chart type as the newly discovered reservoir to evaluate the peak oil production rate of the different types of offshore water-driven sandstone reservoirs. R maxn If the image is R max with log( M Relationship diagram ， Based on the new reservoir mobility M n Using the formula in step 3) R maxn = e ×log( M n ) +g Calculate peak oil production rate R maxn If the diagram is ( R max / E Ro ) and log( M Relationship diagram ， Based on the new reservoir mobility M n Using the formula in step 3) R max / E Ro ) n = e ×log(M n ) +g Calculate the ratio of peak oil production rate to reservoir recovery rate in a new oil reservoir. R max / E Ro ) n Then utilize the recovery rate of the new reservoir in step 7). E Rn Calculate peak oil recovery R maxn =( R max / E Ro ) n × E Rn .

[0104] 9. Based on the decline characteristic parameters of different types of offshore water-driven sandstone reservoirs in step 4), D D The decline characteristic parameters of the newly discovered oil reservoirs were selected as those of the same type. D Dn ;

[0105] 10. Based on the newly discovered reservoir decline characteristic parameters in step 9). D Dn Step 7) Newly discovered offshore water-driven sandstone oil reservoir recovery rate E Rn Step 8) The newly discovered offshore water-driven sandstone oil reservoir has a peak oil production rate R maxn The annual oil production profile of the newly discovered offshore water-driven sandstone oil reservoir was calculated iteratively. The specific process is as follows:

[0106] ①Based on the newly discovered oil reservoir's recoverable reserves N in And the recovery rate of newly discovered oil reservoirs in step 7) E Rn Calculate the identified recoverable reserves of the reservoir N R = N in × E Rn .

[0107] ②Based on the number of development wells required for the newly discovered offshore water-drive sandstone oil reservoirs in step 6). W o Assess the time required for the reservoir to reach peak production rate. W o The time required to reach peak oil production rate is 2 years when the oil production rate is ≤20; when W o> It will take 3 years to reach peak oil production rate at 20:00.

[0108] ③ Calculate the annual oil production before the reservoir reaches peak production rate. If the time required to reach peak production rate is 2 years, the annual oil production in the first year is: P (1)= R maxn × N in / 2, the annual oil production in the second year is P (2)= R maxn × N in If it takes 3 years to reach peak oil production rate, the annual oil production in the first year will be: P (1)= R maxn × N in / 3, the annual oil production in the second year is P (2)= R maxn × N in / 3×2, the annual oil production in the third year is P (3)= R maxn × N in ;

[0109] ④ Given initial values ​​for the two decline rates of the newly discovered reservoir. The initial decline rate for the first stage is given as follows: D 1n (0), based on the newly discovered reservoir characteristic parameters in step 9) D Dn Calculate the initial value of the second decreasing segment. D 2n (0)= D 1n (0) / D Dn ;

[0110] ⑤ Calculate the annual oil production profile after reaching peak production rate. If the time required to reach peak production rate is 2 years, then the annual oil production from year 3 to year 11 is... P ( y )= P ( y -1)×ln(- D 1n (0)), while the annual oil production from year 12 to year 20 was P ( y )= P ( y -1)×ln(-D 2n (0)); If the time required to reach peak oil production rate is 3 years, then the annual oil production from year 4 to year 11 is P ( y )= P ( y -1)×ln(- D 1n (0)), while the annual oil production from year 12 to year 20 was P ( y )= P ( y -1)×ln(- D 2n (0)); where y Indicates the production period in years.

[0111] ⑥ Iteratively calculate the annual oil production until the total annual oil production reaches the recoverable reserves specified in ①. N R The total cumulative oil production is calculated based on the annual oil production figures in sections ③ and ⑤. To determine whether the target recoverable reserves have been reached, if... Then the annual oil production is P ( y );like and Then update the first segment's decrease rate to... D 1n ( k )= D 1n (0)+0.0005. Repeat steps ① to ⑥ until the condition is met. ;like and Then update the initial decrease rate of the first segment to: D 1n ( k )= D 1n (0)-0.0005 Repeat steps ① to ⑥ until the condition is met. .

[0112] Taking two reservoir types as examples, the predicted annual production profiles of different types of offshore water-driven sandstone reservoirs are shown in the figure below. Figure 2A and Figure 2B As shown.

[0113] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for classifying and predicting development indicators of offshore water-drive sandstone oil reservoirs, characterized in that, include: Step 1: Classify offshore water-driven sandstone reservoirs based on sedimentary basins, oil-bearing strata, sedimentary facies, formation conditions, average crude oil viscosity, and average reservoir permeability; Step 2: Based on the classification results of water-driven sandstone reservoirs in Step 1, establish recovery prediction models for different types of offshore water-driven sandstone reservoirs according to reservoir type. Step 3: Based on the classification results of water-driven sandstone reservoirs in Step 1, establish peak production rate evaluation charts for different types of offshore water-driven sandstone reservoirs according to reservoir type; Step 4: Define reservoir decline characteristic parameters. Based on the classification results of producing water-driven sandstone reservoirs in Step 1 and the production profile of primary well networks for different types of producing water-driven sandstone reservoirs, calculate the decline characteristic parameters of different types of reservoirs. Step 5: Statistically analyze the static geological parameters of the newly discovered offshore water-driven sandstone oil reservoirs, and determine the type of the newly discovered offshore water-driven sandstone oil reservoirs based on the principles in Step 1. Step 6: Based on the newly discovered offshore water-driven sandstone reservoir type obtained in Step 5, calculate the average well-controlled reserves of the same type of offshore water-driven sandstone reservoir in production. Calculate the required number of development wells and the reasonable well density based on the average well-controlled reserves and the geological reserves of the newly discovered offshore water-driven sandstone reservoir. Step 7: Based on the reasonable well network density and static parameters of the newly discovered offshore water-driven sandstone reservoir in Step 6, select the recovery rate prediction model from Step 2 that is the same type as the newly discovered offshore water-driven sandstone reservoir to calculate the recovery rate of the newly discovered offshore water-driven sandstone reservoir. Step 8: Select the peak oil recovery rate evaluation chart from Step 3 that is the same type as the newly discovered offshore water-driven sandstone reservoir as the basis for calculating the peak oil recovery rate of the newly discovered offshore water-driven sandstone reservoir; Step 9: Based on the decline characteristic parameters of different types of offshore water-driven sandstone reservoirs in Step 4, select the reservoir decline characteristic parameters that are the same as the newly discovered offshore water-driven sandstone reservoir type as the decline characteristic parameters of the newly discovered offshore water-driven sandstone reservoir. Step 10: Based on the decline characteristic parameters of the newly discovered offshore water-driven sandstone reservoir in Step 9, the recovery rate of the newly discovered offshore water-driven sandstone reservoir in Step 7, and the peak oil production rate of the newly discovered offshore water-driven sandstone reservoir in Step 8, iteratively calculate the annual oil production profile of the newly discovered offshore water-driven sandstone reservoir. Based on newly discovered offshore water-driven sandstone oil reservoirs, the recoverable reserves N in The recovery rate of newly discovered offshore water-driven sandstone oil reservoirs in step 7 E Rn Calculate the identified recoverable reserves of the reservoir N R = N in × E Rn ; Based on the number of development wells required for the newly discovered offshore water-driven sandstone oil reservoirs in step 6. W o Assess the time required for the reservoir to reach peak production rate; when W o The time required to reach peak oil production rate is 2 years when the oil production rate is ≤20; when W o > It will take 3 years to reach peak oil production rate at 20:

00. Calculate the annual oil production before the reservoir reaches peak production rate. If the time required to reach peak production rate is 2 years, the annual oil production in the first year is... P (1)= R maxn × N in / 2, the annual oil production in the second year is P (2)= R maxn × N in If it takes 3 years to reach peak oil production rate, the annual oil production in the first year will be: P (1)= R maxn × N in / 3, the annual oil production in the second year is P (2)= R maxn × N in / 3×2, the annual oil production in the third year is P (3)= R maxn × N in ; in, R maxn This represents the peak oil production rate for the newly discovered offshore water-driven sandstone oil reservoir; Given initial values ​​for the two decline rates of a newly discovered reservoir; given the initial decline rate of the first stage as... D 1n (0), based on the newly discovered decline characteristic parameters of offshore sandstone reservoirs in step 9 D Dn Calculate the initial value of the second decreasing segment. D 2n (0)= D 1n (0) / D Dn ; Calculate the annual oil production profile after reaching peak production rate; if the time required to reach peak production rate is 2 years, then the annual oil production from year 3 to year 11 is... P ( y )= P ( y -1)×ln(- D 1n (0)), while the annual oil production from year 12 to year 20 was P ( y )= P ( y -1)×ln(- D 2n (0)); If the time required to reach peak oil production rate is 3 years, then the annual oil production from year 4 to year 11 is P ( y )= P ( y -1)×ln(- D 1n (0)), while the annual oil production from year 12 to year 20 was P ( y )= P ( y -1)×ln(- D 2n (0)); where y Indicates the production period over a given year; Iterative calculations of annual oil production are performed until the sum of annual oil production reaches the calibrated recoverable reserves. N R ; The total cumulative oil production is calculated based on historical oil production figures. To determine whether the target recoverable reserves have been reached, if... Then the annual oil production is P ( y );like and Then update the first segment's decrease rate to... D 1n ( k )= D 1n (0) + 0.0005, until the condition is met. ;like and Then update the initial decrease rate of the first segment to be... D 1n ( k )= D 1n (0)-0.0005, until satisfied. .

2. The method for classifying and predicting development indicators of offshore water-driven sandstone oil reservoirs according to claim 1, characterized in that, The calculation methods for average crude oil viscosity and average permeability of the reservoir under formation conditions in Step 1, and the classification methods for offshore water-driven sandstone reservoirs in production are as follows: （1） （2） In the formula The average crude oil viscosity of the reservoir under formation conditions; K o The average permeability of the reservoir; N j Oil reservoir reserve calculation unit j Geological reserves; m The number of reservoir reserve calculation units included in the utilized reserves; μ oj Oil reservoir reserve calculation unit j Crude oil viscosity under formation conditions; Oil reservoir reserve calculation unit j Penetration rate.

3. The method for classifying and predicting development indicators of offshore water-drive sandstone oil reservoirs according to claim 2, characterized in that, The classification of offshore water-driven sandstone reservoirs is based on sedimentary basins, oil-bearing strata, sedimentary facies, crude oil viscosity, and reservoir permeability.

4. The method for classifying and predicting development indicators of offshore water-drive sandstone oil reservoirs according to claim 3, characterized in that, The method for establishing recovery prediction formulas for different types of offshore water-drive sandstone reservoirs in step 2 is as follows: The recovery rate, average reservoir porosity, average crude oil viscosity under formation conditions, average reservoir permeability, and well density of offshore waterflood sandstone reservoirs after the implementation of a single well pattern development program were statistically analyzed. Reservoir types were then analyzed using fitted relationships. E R = a + b ×log( K o / μ o )+ c × φ o +d × F o Coefficient identification was performed for different types of reservoirs, among which... a, b, c, d These are the fitting coefficients; E R For recovery rate; K o The average permeability of the reservoir; μ o The average crude oil viscosity of the reservoir under formation conditions; φ o The average porosity of the reservoir; F o Well density; The fitting coefficients are required to be no less than 0, so as to establish the recovery rate prediction formula for different types of offshore water-driven sandstone reservoirs.

5. The method for classifying and predicting development indicators of offshore water-driven sandstone oil reservoirs according to claim 4, characterized in that, The calculation methods for reservoir average porosity and well pattern density are as follows: （3） (4) In the formula φ o The average porosity of the reservoir; φ oj Oil reservoir reserve calculation unit j Porosity; N j Oil reservoir reserve calculation unit j Geological reserves; m The number of reservoir reserve calculation units included in the utilized reserves; F o This refers to the density of the reservoir well network. W d Number of directional wells; W h This represents the total number of horizontal and branch wells. A The area of ​​oil-bearing area is the superimposed area of ​​the active zone.

6. The method for classifying and predicting development indicators of offshore water-drive sandstone oil reservoirs according to claim 5, characterized in that, The method for establishing peak oil recovery rate evaluation charts for different types of offshore water-drive sandstone reservoirs in step 3 is as follows: Statistics on the recovery rate after the implementation of a primary well pattern development program for offshore water-drive sandstone oil reservoirs E Ro Peak oil production rate R maxo And calculate reservoir mobility M = K o / μ o ; Peak oil recovery rates for different types of producing reservoirs are plotted according to reservoir type. R max With reservoir mobility M The scatter plot after taking the logarithm was fitted using the fitted relationship. R max = e ×log( M)+g Perform coefficient identification and calculate the squared correlation coefficient R. 2 (1), where e, g These are the fitting coefficients; Map different types of producing reservoirs according to reservoir type. R max / E Ro With reservoir mobility M The scatter plot after taking the logarithm is used to fit the relationship ( R max / E Ro )= e ×log( M ) +g Perform coefficient identification and calculate the squared correlation coefficient R. 2 (2); If R 2 (1)>R 2 (2) Then adopt R max with log( M The relationship is used as a chart to evaluate the peak production rate of this type of reservoir; if R 2 (1) <R 2 (2), then adopt ( R max / E Ro ) and log( M This serves as a chart for evaluating the peak production rate of this type of reservoir.

7. The method for classifying and predicting development indicators of offshore water-drive sandstone oil reservoirs according to claim 6, characterized in that, Step 4) Decline characteristic parameters of different types of offshore water-driven sandstone reservoirs D D The definition and calculation method are as follows: (5) (6) In the formula For the first k Decline characteristic parameters of offshore water-driven sandstone reservoirs of various types; L Indicates the first k The number of offshore water-driven sandstone reservoirs of this type in production; Indicates the first k Type No. l One characteristic parameter for the decline of offshore water-driven sandstone oil reservoirs; Indicates the first k Type No. l The Arps index decline rate in the first stage of offshore water-driven sandstone reservoirs; Indicates the first k Type No. l The Arps index decrease rate in the second stage of a water-driven sandstone reservoir in production.

8. The method for classifying and predicting development indicators of offshore water-drive sandstone oil reservoirs according to claim 7, characterized in that, In step 6, the average well-controlled reserves of producing offshore water-driven sandstone reservoirs of the same type as newly discovered offshore water-driven sandstone reservoirs... N wave Number of development wells required for newly discovered offshore water-drive sandstone oil reservoirs W o and reasonable well density F n The calculation method is as follows: (7) (8) (9) In the formula The average well-controlled reserves of offshore producing water-driven sandstone reservoirs of the same type as newly discovered offshore water-driven sandstone reservoirs; L This indicates the number of producing offshore water-driven sandstone reservoirs of the same type as newly discovered offshore water-driven sandstone reservoirs. This indicates that the newly discovered offshore water-driven sandstone oil reservoirs are of the same type. l One well-controlled reserve in a producing offshore water-driven sandstone oil reservoir; W o The number of development wells required for newly discovered offshore water-driven sandstone oil reservoirs; F n To determine the optimal well density for newly discovered offshore water-driven sandstone oil reservoirs; N in This represents the activated reserves of newly discovered offshore water-driven sandstone oil reservoirs; A n This represents the superimposed oil-bearing area of ​​the newly discovered offshore water-driven sandstone oil reservoir's activation zone.

9. The method for classifying and predicting development indicators of offshore water-drive sandstone oil reservoirs according to claim 8, characterized in that, The newly discovered offshore water-driven sandstone oil reservoir in step 8 has a peak oil production rate. R maxn The calculation method is as follows: Based on the statistical analysis of crude oil viscosity under subsurface conditions of newly discovered oil reservoirs in step 5... μ n reservoir permeability K n Calculate the mobility of the new reservoir M n= K n / μ n : From Step 3, select charts of the same type as the newly discovered offshore water-driven sandstone reservoirs to evaluate the peak oil recovery rate of the newly discovered offshore water-driven sandstone reservoirs. R maxn ; If the map is R max with log( M Relationship diagram ， Based on the new reservoir mobility M n Using formula R maxn = e ×log( M n ) +g Calculate peak oil production rate R maxn If the diagram is ( R max / E Ro ) and log( M Relationship diagram ， Based on the new reservoir mobility M n Using the formula ( R max / E Ro ) n = e ×log( M n ) +g Calculate the ratio of peak oil production rate to reservoir recovery rate in a new oil reservoir. R max / E Ro ) n The recovery rate of the newly discovered offshore water-driven sandstone oil reservoirs in step 7) can be further utilized. E Rn Calculate peak oil production rate R maxn =( R max / E Ro ) n × E Rn .

Images