WO2022012368A1 - 一种页岩原位转化可采油气资源量的预测方法及装置 - Google Patents

一种页岩原位转化可采油气资源量的预测方法及装置 Download PDF

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WO2022012368A1
WO2022012368A1 PCT/CN2021/104637 CN2021104637W WO2022012368A1 WO 2022012368 A1 WO2022012368 A1 WO 2022012368A1 CN 2021104637 W CN2021104637 W CN 2021104637W WO 2022012368 A1 WO2022012368 A1 WO 2022012368A1
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shale
recoverable
effective
oil
rock
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PCT/CN2021/104637
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English (en)
French (fr)
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侯连华
付金华
江涛
王玉华
刘显阳
王京红
李永新
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中国石油天然气股份有限公司
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Publication of WO2022012368A1 publication Critical patent/WO2022012368A1/zh
Priority to US18/154,555 priority Critical patent/US20230175961A1/en

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    • E—FIXED CONSTRUCTIONS
    • E21—EARTH OR ROCK DRILLING; MINING
    • E21B—EARTH OR ROCK DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS
    • E21B49/00—Testing the nature of borehole walls; Formation testing; Methods or apparatus for obtaining samples of soil or well fluids, specially adapted to earth drilling or wells
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
    • G01N21/55—Specular reflectivity
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/24—Earth materials
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/24—Earth materials
    • G01N33/241—Earth materials for hydrocarbon content
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/20—Design optimisation, verification or simulation

Definitions

  • the invention relates to a method and a device for predicting recoverable oil and gas resources for in-situ conversion of shale, belonging to the technical field of oil and gas exploration and development.
  • Shale refers to a sedimentary rock with high total organic carbon (TOC) content and laminar lamination.
  • TOC total organic carbon
  • the maturity of the shale is low, that is, the vitrinite reflectance (Ro) is less than 1.0%, the pores in the shale are not developed, and the fluid flow is difficult, and the existing horizontal well volume fracturing technology cannot achieve commercial scale development.
  • in situ conversion technology can be used to develop shale with lower maturity.
  • In-situ conversion technology is a technology that converts unconverted organic matter in shale into oil and gas by in-situ heating, and simultaneously recovers the in-situ converted oil and gas and the oil and gas retained in shale.
  • Shale here is a general term for shale with low to medium maturity, that is, Ro less than 1.0%, including low to medium maturity shale and immature oil shale.
  • the recoverable resources of in-situ conversion of shale in the world are more than 1.5 trillion tons, and the technically recoverable resources of natural gas are about 1,300 trillion cubic meters; the recoverable resources of in-situ conversion of shale in China are more than 80 billion tons.
  • the recoverable resources of natural gas are more than 60 trillion cubic meters; it is more than three times the recoverable resources of conventional oil and natural gas, and the potential is huge.
  • the generated oil and gas volume model of the shale from the original state and the retained oil and gas volume model at different Ro stages are established.
  • the amount of oil and gas retained and the amount of retained oil and gas are established, and a model of oil and gas production can be established, which can be extrapolated to carry out the evaluation of oil and gas resources produced by in-situ transformation.
  • one object of the present invention is to provide a method for predicting the amount of recoverable oil and gas resources for in-situ conversion of shale.
  • Another object of the present invention is to provide a device for predicting recoverable oil and gas resources for in-situ conversion of shale.
  • Yet another object of the present invention is to provide a computer device.
  • Still another object of the present invention is to provide a computer-readable storage medium.
  • the invention can quantitatively predict the recoverable oil and gas resources of shale in-situ transformation, and improve the prediction accuracy and efficiency of the recoverable oil and gas resources of shale in-situ transformation.
  • the present invention provides a method for predicting the amount of recoverable oil and gas resources by in-situ conversion of shale, wherein the method for predicting the amount of recoverable oil and gas resources by in-situ conversion of shale includes:
  • a prediction model of recoverable gas volume for in-situ transformation of shale is established, and the recoverable gas volume prediction model of in-situ transformation of shale is used according to the total organic carbon content and vitrinite reflectance of the shale to be tested to obtain the recoverable gas volume of the shale to be tested. gas volume;
  • the effective thickness, effective thickness interval and effective shale distribution area of shale in-situ transformed shale determine the effective thickness, effective thickness interval and effective shale distribution area of shale in-situ transformed shale ;
  • the models of recoverable oil resource abundance and recoverable gas resource abundance value in the effective thickness interval are respectively established, and the recoverable oil volume per unit mass of rock and the recoverable gas volume per unit mass of rock at the logging interpretation point are obtained respectively to be evaluated.
  • a prediction model for recoverable oil resources and recoverable gas resources is established respectively, and recoverable oil resources and recoverable gas resources are obtained according to the prediction models of recoverable oil resources and recoverable gas resources.
  • a recoverable oil quantity prediction model for in-situ conversion of shale including:
  • the recoverable oil amount prediction model of the in-situ conversion of shale is established according to the following formula:
  • Q po is the recoverable oil amount of the shale to be tested, mg/g rock
  • Ro is the vitrinite reflectance of the shale to be tested, %
  • TOC is the total organic carbon content of the shale to be tested, wt%
  • a 1 , a 2 , a 3 , a 4 , a 5 , and a 6 are empirical parameters.
  • the g ⁇ rock in the unit mg/g ⁇ rock of the recoverable oil quantity Q po of the shale to be tested refers to the mass per gram of rock
  • a recoverable gas volume prediction model for in-situ conversion of shale including:
  • the recoverable gas volume prediction model of the in-situ conversion of shale is established according to the following formula:
  • Q pg is the recoverable gas volume of the shale to be tested, m 3 /t ⁇ rock;
  • Ro is the vitrinite reflectance of the shale to be tested, %;
  • TOC is the total organic carbon content of the shale to be tested, wt% ;
  • b 1 , b 2 , b 3 , b 4 , b 5 , b 6 , b 7 , b 8 , b 9 , b 10 , b 11 , b 12 , b 13 , b 14 , b 15 are empirical parameters;
  • w 1 is 0.5%-1.0%, w 2 is 1.0%-1.4%.
  • t ⁇ rock in the recoverable gas volume Q pg of the shale to be tested in m 3 /t ⁇ rock refers to the mass per ton of rock
  • the lower limit value of the recoverable oil amount per unit mass of rock converted in-situ is based on the same development area of the in-situ conversion of shale (the same development area refers to the same development area with similar).
  • the lower limit value of the cumulative oil output of any production well group in the in-situ transformation of geological conditions and the development area with similar development techniques) and the rock quality of the effective heating zone controlled by the production well group are obtained according to the following formula:
  • Q po_limt is the lower limit of oil recovery per unit mass of rock for in-situ conversion of shale, mg/g rock;
  • Q oil_limt is the lower limit of cumulative oil output of a production well group converted in-situ of shale, mg;
  • Wt rock is the rock mass in the effective heating zone controlled by the production well group converted in situ by shale, g.
  • a prediction model for the lower limit value of the total organic carbon content of effective shale including: a prediction model for the recoverable oil amount of in-situ conversion of shale and the unit mass of in-situ conversion of shale
  • the lower limit of the recoverable oil amount of the rock, the prediction model of the lower limit of the total organic carbon content of the effective shale is established according to the following formula:
  • TOC limt is the lower limit of total organic carbon content of effective shale, wt%;
  • Q po_limt is the lower limit of recoverable oil per unit mass of rock converted in situ by shale, mg/g rock;
  • Ro is to be measured Vitrinite reflectance of shale, %;
  • c 1 , c 2 , c 3 , c 4 , c 5 , and c 6 are empirical parameters.
  • the in-situ conversion of shale is determined according to the following principles.
  • Shale effective thickness, effective thickness interval and effective shale distribution area is determined according to the following principles.
  • the set value of 5 meters is used as the effective thickness of the shale.
  • the depth section corresponding to the apparent effective thickness of shale is the section with apparent effective thickness; between two adjacent sections with apparent effective thickness, when the total organic carbon content of shale logging interpretation is less than the total organic carbon content of effective shale.
  • the set value When the continuous thickness of the limit value is less than the set value of 0.5-5 meters, the set value is determined as 2 meters, and the interval is calculated into the effective thickness of the apparent shale; when the total organic When the continuous thickness whose carbon content is less than the lower limit of the total organic carbon content of the effective shale is greater than the set value of 0.5-5 meters, the set value is determined to be 2 meters, and the apparent effective shale thickness is not calculated for this interval middle;
  • the apparent shale effective thickness is greater than the set value of 3-15 meters, the set value of 5 meters is used as the apparent shale effective thickness, and the apparent shale effective thickness is the shale effective thickness.
  • the interval of is the effective thickness interval;
  • the apparent shale effective thickness is less than or equal to the set value of 3-15 meters, the set value of 5 meters is used as the apparent shale effective thickness, but the apparent shale effective thickness cannot be used as the shale effective thickness, and thus cannot be used as an independent development interval , the recoverable resources are not calculated for this interval; when the longitudinal distance between two or more effective thickness intervals exceeds the preset thickness value of 0.5-5 meters, each effective thickness interval will be effective as a separate shale.
  • Thickness section treatment that is, treatment as an independent development layer system;
  • the effective thickness distribution of shale in the evaluated area is obtained by the non-equidistant interpolation method, and the grid spacing of the non-equidistant interpolation method adopts the preset value of 0.1-10km (more preferably 2km), when the effective thickness of shale in the evaluated area is greater than the preset effective thickness of 3-15 meters, 5 meters are used as the boundary of the effective thickness distribution area of shale, and the area with effective shale thickness greater than 5 meters is effective Shale distribution area.
  • the set value can be determined according to in-situ transformation needs and geological conditions
  • the non-equidistant interpolation methods include three-point method, five-point method, finite element method, kriging method, linear interpolation method, nonlinear interpolation method, and the like.
  • models of recoverable oil resource abundance and recoverable gas resource abundance value in the effective shale interval are respectively established, including:
  • the recoverable oil resource abundance in the effective shale interval is established respectively. degree and recoverable gas resource abundance model.
  • models of recoverable oil resource abundance and recoverable gas resource abundance value in an effective shale interval are respectively established according to the following formulas:
  • AOR is the abundance of recoverable oil resources in the effective shale interval of the area to be evaluated, 10,000 tons/km 2 ;
  • AGR is the abundance of recoverable gas resources in the effective shale interval of the area to be evaluated, 100 million cubic meters/km 2 ;
  • Q po_i is the oil recovery per unit mass of the i-th logging point in the effective thickness interval of the area to be evaluated, mg/g rock;
  • Q pg_i is the i-th logging point in the effective thickness interval of the area to be evaluated
  • ⁇ i is the rock density value of the i-th logging point in the effective thickness interval of the area to be evaluated, g/cm 3 ;
  • L inter is the value of the well to be evaluated Log spacing, m;
  • n is the total number of logging points in the effective thickness interval, n is an integer.
  • the recoverable oil volume per unit mass of rock and the recoverable gas volume per unit mass of rock at the logging interpretation point are obtained according to the following steps:
  • the total organic carbon content of the logging interpretation in the area to be evaluated the total organic carbon content, rock density value, and measurement spacing value of the logging interpretation point in the effective shale interval are obtained, and then according to the logging interpretation point in the effective shale interval
  • the total organic carbon content, rock density value, measurement distance value, and vitrinite reflectance of the well point in the target layer are obtained by using the oil recovery prediction model of shale in-situ transformation and the recoverable gas volume prediction model of shale in-situ transformation.
  • the recoverable oil resource abundance of all well points in the evaluated area can be obtained according to the recoverable oil resource abundance value model and recoverable gas resource abundance value model in the effective shale interval established above. value, recoverable gas resource abundance value; then according to the recoverable oil resource abundance value and recoverable gas resource abundance value of all wells in the evaluated area, three-point method, five-point method, finite element method, Kerry
  • the non-equidistant interpolation methods such as gold method, linear interpolation method and nonlinear interpolation method can obtain the plane distribution of the abundance of recoverable oil resources and recoverable gas resources in the evaluated area; according to the plane distribution, the effective page can be obtained.
  • the abundance of recoverable oil resources in the jth grid in the shale distribution area and the recoverable gas resource abundance in the jth grid in the effective shale distribution area can be obtained according to the recoverable oil resource abundance value model and recoverable gas resource abundance value model in the effective shale interval established above. value, recoverable gas resource abundance value; then according to
  • the three-point method, five-point method, finite element method, kriging method, linear interpolation method, nonlinear interpolation method and other non-equidistant interpolation grid spacing adopts preset
  • the value is 0.1-10km, preferably 2km is used.
  • the recoverable oil resources and recoverable gas resources are respectively established according to the following formulas Volume prediction model:
  • NO is the recoverable oil resource in the area to be evaluated, 10,000 tons
  • NG is the recoverable gas resource in the area to be evaluated, 100 million cubic meters
  • AOR j is the recoverable oil resource abundance of the jth grid in the effective shale distribution area, 10,000 tons/km 2
  • AGR j is the recoverable gas resource abundance of the j-th grid in the effective shale distribution area, 100 million cubic meters/km 2
  • a j is the area of the j-th grid in the effective shale distribution area , km 2
  • m is the grid number in the effective shale distribution area, and m is an integer.
  • the present invention also provides a prediction device for in-situ conversion of recoverable oil and gas resources in shale, wherein the prediction device for in-situ conversion of recoverable oil and gas resources in shale includes:
  • the data acquisition module is used to acquire the total organic carbon content and vitrinite reflectance of the shale to be measured in the area to be evaluated;
  • the model building module for predicting the recoverable oil amount of shale in-situ transformation is used to establish a predictable oil amount prediction model for in-situ transformation of shale, and according to the total organic carbon content and vitrinite reflectance of the shale to be tested, the original shale Obtain the recoverable oil amount of the shale to be tested by using the oil-recovery prediction model of the bit conversion;
  • the module for establishing the recoverable gas volume prediction model of shale in-situ transformation is used to establish the recoverable gas volume prediction model of shale in-situ transformation. Obtain the recoverable gas volume of the shale to be tested by using the predicted model of the recoverable gas volume transformed by the bit position;
  • the model building module for the prediction model of the lower limit of the total organic carbon content of effective shale is used to establish the prediction model of the lower limit value of the total organic carbon content of effective shale, and based on the lower limit of recoverable oil volume per unit mass of rock transformed in situ from shale value and the vitrinite reflectance of the shale to be tested to obtain the lower limit of the total organic carbon content of the effective shale;
  • the module for determining the effective thickness, effective thickness interval and effective shale distribution area of shale transformed in situ is used for the total organic carbon content and the total organic carbon content of the effective shale according to the logging interpretation of the area to be evaluated.
  • the lower limit value is used to determine the effective thickness of shale, effective thickness interval and effective shale distribution area for in-situ transformation of shale;
  • the model building module of recoverable oil resource abundance value and recoverable gas resource abundance value in the effective thickness interval is used to respectively establish the recoverable oil resource abundance value and recoverable gas resource abundance value model in the effective thickness interval, According to the recoverable oil volume per unit mass of rock and the recoverable gas volume per unit mass of rock at the logging interpretation point, the recoverable oil resource abundance value and recoverable gas resource abundance value in the effective thickness interval of the evaluated well are obtained respectively;
  • Recoverable oil resources and recoverable gas resources prediction model building modules are used to respectively establish recoverable oil resources and recoverable gas resources prediction models, and obtain recoverable oil resources according to the recoverable oil resources and recoverable gas resources prediction models. and recoverable gas resources.
  • the model establishment module for predicting the recoverable oil volume of the in-situ conversion of shale is specifically used for producing oil volume data obtained by performing thermal simulation experiments on a plurality of different shale samples, As well as the total organic carbon content and vitrinite reflectance of shale samples, a relationship model between oil production and total organic carbon content is established, and the empirical parameters and vitrinite reflectance in the model are extracted to establish a model, thereby establishing a model.
  • the recoverable oil quantity prediction model for in-situ conversion of shale is specifically used for producing oil volume data obtained by performing thermal simulation experiments on a plurality of different shale samples, As well as the total organic carbon content and vitrinite reflectance of shale samples, a relationship model between oil production and total organic carbon content is established, and the empirical parameters and vitrinite reflectance in the model are extracted to establish a model, thereby establishing a model.
  • the recoverable oil quantity prediction model for in-situ conversion of shale is specifically used
  • the in-situ conversion of shale oil recovery prediction model establishment module is further used to establish the shale in-situ conversion of shale oil prediction model according to the following formula:
  • Q po is the recoverable oil amount of the shale to be tested, mg/g rock
  • Ro is the vitrinite reflectance of the shale to be tested, %
  • TOC is the total organic carbon content of the shale to be tested, wt%
  • a 1 , a 2 , a 3 , a 4 , a 5 , and a 6 are empirical parameters.
  • the module for establishing the model for predicting the recoverable gas volume of the in-situ conversion of shale is specifically used for producing gas volume data obtained by thermal simulation experiments on a plurality of different shale samples, and Total organic carbon content and vitrinite reflectance of shale samples, establish a relationship model between produced gas and total organic carbon content, and then extract the empirical parameters and vitrinite reflectance in the model to establish a model, thereby establishing the above Prediction model of recoverable gas volume for in-situ conversion of shale.
  • the model building module for predicting the recoverable gas volume of the in-situ conversion of shale is further used to establish the prediction model of the recoverable gas volume of the in-situ transformation of shale according to the following formula:
  • Q pg is the recoverable gas volume of the shale to be tested, m 3 /t ⁇ rock;
  • Ro is the vitrinite reflectance of the shale to be tested, %;
  • TOC is the total organic carbon content of the shale to be tested, wt% ;
  • b 1 , b 2 , b 3 , b 4 , b 5 , b 6 , b 7 , b 8 , b 9 , b 10 , b 11 , b 12 , b 13 , b 14 , b 15 are empirical parameters;
  • w 1 is 0.5%-1.0%, w 2 is 1.0%-1.4%.
  • the establishment module for the prediction model for the lower limit value of the total organic carbon content of the effective shale includes a unit for obtaining the lower limit value of the recoverable oil amount per unit mass of rock transformed by the shale in situ, using According to the lower limit of the cumulative oil output of any production well group in the same development area according to the in-situ conversion of shale and the rock quality of the effective heating zone controlled by the production well group, the in-situ conversion of shale can be obtained according to the following formula.
  • Q po_limt is the lower limit of oil recovery per unit mass of rock for in-situ conversion of shale, mg/g rock;
  • Q oil_limt is the lower limit of cumulative oil output of a production well group converted in-situ of shale, mg;
  • Wt rock is the rock mass in the effective heating zone controlled by the production well group converted in situ by shale, g.
  • the establishment module for the prediction model of the lower limit value of the total organic carbon content of the effective shale is specifically used for predicting the recoverable oil amount according to the in-situ conversion of shale and the unit of the in-situ conversion of shale.
  • the lower limit of the recoverable oil amount of the quality rock, the prediction model of the lower limit of the total organic carbon content of the effective shale is established according to the following formula:
  • TOC limt is the lower limit of total organic carbon content of effective shale, wt%;
  • Q po_limt is the lower limit of recoverable oil per unit mass of rock converted in situ by shale, mg/g rock;
  • Ro is to be measured Vitrinite reflectance of shale, %;
  • c 1 , c 2 , c 3 , c 4 , c 5 , and c 6 are empirical parameters.
  • the shale effective thickness, effective thickness interval and effective shale distribution area determination module for in-situ conversion of shale is specifically used to determine the total shale according to the logging interpretation of the area to be evaluated.
  • the organic carbon content and the lower limit of the total organic carbon content of the effective shale are determined according to the following principles:
  • the set value of 5 meters is used as the effective thickness of the shale.
  • the depth section corresponding to the apparent effective thickness of shale is the section with apparent effective thickness; between two adjacent sections with apparent effective thickness, when the total organic carbon content of shale logging interpretation is less than the total organic carbon content of effective shale.
  • the set value When the continuous thickness of the limit value is less than the set value of 0.5-5 meters, the set value is determined as 2 meters, and the interval is calculated into the effective thickness of the apparent shale; when the total organic When the continuous thickness whose carbon content is less than the lower limit of the total organic carbon content of the effective shale is greater than the set value of 0.5-5 meters, the set value is determined to be 2 meters, and the apparent effective shale thickness is not calculated for this interval middle;
  • the apparent shale effective thickness is greater than the set value of 3-15 meters, the set value of 5 meters is used as the apparent shale effective thickness, and the apparent shale effective thickness is the shale effective thickness.
  • the interval of is the effective thickness interval;
  • the apparent shale effective thickness is less than or equal to the set value of 3-15 meters, the set value of 5 meters is used as the apparent shale effective thickness, but the apparent shale effective thickness cannot be used as the shale effective thickness, and thus cannot be used as an independent development interval , the recoverable resources are not calculated for this interval; when the longitudinal distance between two or more effective thickness intervals exceeds the preset thickness value of 0.5-5 meters, each effective thickness interval will be effective as a separate shale.
  • Thickness section treatment that is, treatment as an independent development layer system;
  • the effective thickness distribution of shale in the evaluated area is obtained by the non-equidistant interpolation method, and the grid spacing of the non-equidistant interpolation method adopts the preset value of 0.1-10km , when the effective thickness of shale in the evaluated area is greater than the preset effective thickness of 3-15 meters, 5 meters are used as the boundary of the effective shale thickness distribution area, and the area with an effective shale thickness greater than 5 meters is the effective shale distribution area.
  • the model building module for the abundance value of recoverable oil resources and the abundance value of recoverable gas resources in the effective thickness interval is specifically used for recovering oil and gas volume per unit mass of rock, logging well Spacing, rock density and effective thickness interval, according to the recoverable oil and gas recoverable amount of rock in the effective thickness interval per unit area, respectively establish the recoverable oil resource abundance value and recoverable gas resource abundance value in the effective shale interval Model.
  • the model establishment module for the abundance value of recoverable oil resources and the abundance value of recoverable gas resources in the effective thickness interval is further configured to respectively establish the abundance value of recoverable oil resources in the effective shale interval according to the following formulas
  • the recoverable oil resource abundance value and recoverable gas resource abundance value model of:
  • AOR is the abundance of recoverable oil resources in the effective shale interval of the area to be evaluated, 10,000 tons/km 2 ;
  • AGR is the abundance of recoverable gas resources in the effective shale interval of the area to be evaluated, 100 million cubic meters/km 2 ;
  • Q po_i is the oil recovery per unit mass of the i-th logging point in the effective thickness interval of the area to be evaluated, mg/g rock;
  • Q pg_i is the i-th logging point in the effective thickness interval of the area to be evaluated
  • ⁇ i is the rock density value of the i-th logging point in the effective thickness interval of the area to be evaluated, g/cm 3 ;
  • L inter is the value of the well to be evaluated Log spacing, m;
  • n is the total number of logging points in the effective thickness interval, n is an integer.
  • the model building module for the abundance value of recoverable oil resources and the abundance value of recoverable gas resources in the effective thickness interval includes the recoverable oil volume per unit mass of rock at the logging interpretation point and the recoverable gas volume acquisition unit per unit mass of rock for:
  • the total organic carbon content of the logging interpretation in the area to be evaluated the total organic carbon content, rock density value, and measurement spacing value of the logging interpretation point in the effective shale interval are obtained, and then according to the logging interpretation point in the effective shale interval
  • the total organic carbon content, rock density value, measurement distance value, and vitrinite reflectance of the well point in the target layer are obtained by using the oil recovery prediction model of shale in-situ transformation and the recoverable gas volume prediction model of shale in-situ transformation.
  • the predicting model building module for recoverable oil resources and recoverable gas resources is specifically used for
  • the prediction models for recoverable oil resources and recoverable gas resources are established respectively according to the following formulas:
  • NO is the recoverable oil resource in the area to be evaluated, 10,000 tons
  • NG is the recoverable gas resource in the area to be evaluated, 100 million cubic meters
  • AOR j is the recoverable oil resource abundance of the jth grid in the effective shale distribution area, 10,000 tons/km 2
  • AGR j is the recoverable gas resource abundance of the j-th grid in the effective shale distribution area, 100 million cubic meters/km 2
  • a j is the area of the j-th grid in the effective shale distribution area , km 2
  • m is the grid number in the effective shale distribution area, and m is an integer.
  • the present invention also provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements all of the above when executing the computer program. Describe the steps of a method for predicting recoverable oil and gas resources by in-situ conversion of shale.
  • the present invention also provides a computer-readable storage medium on which a computer program is stored, wherein, when the computer program is executed by a processor, the above-mentioned shale in-situ conversion of recoverable oil and gas resources is realized. The steps of the prediction method.
  • the recoverable oil volume and recoverable gas volume of the shale to be tested are obtained. It overcomes the defect in the prior art that the original HI or original H/C, original TOC, and immature shale generated oil and gas volume and retained oil and gas volume must be obtained in order to establish recoverable oil volume and recoverable gas volume.
  • the present invention applies the recoverable oil volume prediction model and recoverable gas volume prediction model of the in-situ transformation of shale, not only to achieve quantitative prediction of recoverable oil and gas volume of shale in-situ transformation, but also to The prediction accuracy of recoverable oil and gas volume by in-situ conversion of shale is improved.
  • the same development area refers to the development area with similar in-situ conversion geological conditions and similar development techniques
  • the rock quality of an effective heating zone controlled by a production well group to obtain the lower limit of recoverable oil volume per unit mass of rock converted in situ by shale, and then establish a prediction model for the lower limit of TOC of effective shale, and obtain effective shale
  • the lower limit of TOC of shale so as to accurately obtain the effective thickness of shale, effective thickness interval and effective shale distribution area, overcoming the defect that the lower limit of effective shale TOC cannot be determined in the prior art, and the inability to accurately obtain Defects of shale effective thickness, effective thickness interval and effective shale distribution area.
  • the amount of resources and recoverable gas resources overcomes the defect of using the parameter average value to calculate the relevant parameters in the prior art, and overcomes the actual situation that the use of the parameter average value cannot reflect the nonlinear relationship between the recoverable oil and gas resources and TOC.
  • the calculation of the different contribution of different vertical TOC points to the recoverable oil and gas resources in the effective shale interval is presented.
  • the technical solution provided by the present invention realizes quantitative prediction of recoverable oil and gas resources by in-situ transformation of shale, and improves the prediction accuracy and efficiency of recoverable oil and gas resources by in-situ transformation of shale.
  • FIG. 1 is a schematic flowchart of a method for predicting recoverable oil and gas resources by in-situ conversion of shale provided by an embodiment of the present invention
  • Fig. 2 is the relationship diagram of thermal simulation temperature and Ro in the embodiment of the present invention.
  • Fig. 3 is the relationship diagram of oil output and TOC obtained by thermal simulation in the embodiment of the present invention.
  • Fig. 4 is the output gas quantity and TOC relation diagram that thermal simulation obtains in the embodiment of the present invention.
  • Fig. 5 is the relationship diagram of the maximum output gas amount and the maximum output oil amount of thermal simulation in the embodiment of the present invention.
  • Fig. 6 is the TOC lower limit value and Ro relation diagram when the unit shale oil output lower limit value is 14mg/g in the embodiment of the present invention
  • FIG. 7 is a schematic diagram of no interlayer in an effective shale interval in an embodiment of the present invention.
  • FIG. 8 is a schematic diagram of an interlayer existing in an effective shale interval in an embodiment of the present invention.
  • Fig. 9 is the TOC distribution map of shale in Chang 7 3 sub-member of Ordos Basin in the embodiment of the present invention.
  • Fig. 10 is the Ro distribution map of shale in Chang 7 3 sub-member of Ordos Basin in the embodiment of the present invention.
  • Fig. 11 is the distribution diagram of effective thickness of shale in Chang 7 3 sub-member of Ordos Basin in the embodiment of the present invention.
  • Fig. 12 is the abundance distribution map of shale recoverable oil resources in Chang 7 3 sub-member of Ordos Basin in the embodiment of the present invention.
  • FIG. 14 is a schematic structural diagram of a device for predicting recoverable oil and gas resources for in-situ conversion of shale according to an embodiment of the present invention.
  • the development of oil and gas with shale in-situ conversion technology is different from the existing technology. It is subversive.
  • the in-situ conversion technology is to generate light oil and natural gas by artificial heating of the organic matter and retained oil in the formation, which is suitable for immature oil and natural gas.
  • the in-situ transformation of shale to recover oil and gas resources is the key to in-situ transformation and development, and controls the benefits of in-situ transformation and development.
  • the in-situ conversion technology for predicting recoverable oil and gas resources is obviously different from the currently developed oil and gas resources evaluation technology that has been generated and stored in the formation. It is necessary to use a brand-new idea and evaluation method to predict the recoverable oil and gas resources of in-situ transformation in order to meet the needs of in-situ transformation evaluation and exploration and development.
  • FIG. 1 is a schematic flowchart of a method for predicting recoverable oil and gas resources by in-situ conversion of shale provided in an embodiment of the present invention. As can be seen from FIG. 1 , the method includes the following steps:
  • the recoverable oil volume and recoverable gas volume of the shale to be tested are obtained. It overcomes the defect in the prior art that the original HI or original H/C, original TOC, and immature shale generated oil and gas volume and retained oil and gas volume must be obtained in order to establish recoverable oil volume and recoverable gas volume.
  • the present invention applies the recoverable oil volume prediction model and recoverable gas volume prediction model of the in-situ transformation of shale, not only to achieve quantitative prediction of recoverable oil and gas volume of shale in-situ transformation, but also to The prediction accuracy of recoverable oil and gas volume by in-situ conversion of shale is improved.
  • the unit of shale in-situ transformation is obtained according to the lower limit value of the cumulative oil output of any production well group in the same development area of shale in-situ transformation and the rock quality of the effective heating area controlled by one production well group
  • the lower limit of the recoverable oil amount of the quality rock, and then the prediction model of the lower limit of TOC of the effective shale is established, and the lower limit of the TOC of the effective shale is obtained, so as to accurately obtain the effective thickness of shale, effective thickness interval and
  • the effective shale distribution area overcomes the defect in the prior art that the lower limit value of the effective shale TOC cannot be determined, and the defect that the effective shale thickness, the effective thickness interval and the effective shale distribution area cannot be accurately obtained.
  • the amount of resources and recoverable gas resources overcomes the defect of using the parameter average value to calculate the relevant parameters in the prior art, and overcomes the actual situation that the use of the parameter average value cannot reflect the nonlinear relationship between the recoverable oil and gas resources and TOC.
  • the calculation of the different contribution of different vertical TOC points to the recoverable oil and gas resources in the effective shale interval is presented.
  • the technical solutions provided by the embodiments of the present invention realize quantitative prediction of recoverable oil and gas resources by in-situ conversion of shale, and improve the prediction accuracy and efficiency of recoverable oil and gas resources by in-situ conversion of shale.
  • the multiple sets of shale samples are outcrop shale samples collected from Chang 7 Member in the Ordos Basin.
  • the TOC of each group of shale samples is measured according to the national standard GB/T 19145-2003 "Determination of Total Organic Carbon in Sedimentary Rocks"; Ro is measured according to the industry standard SY/T 5124-2012 “Vitrinite Reflection in Sedimentary Rocks” rate measurement method”.
  • the thermal simulation experiments in this embodiment all adopt a semi-open experimental system with a preset pressure of 5 MPa and different preset temperatures.
  • the thermal simulation experiment specifically includes: loading the shale sample into the reaction kettle and repeatedly compacting it with a pressure of 20 MPa, weighing the shale sample in the reaction kettle before the simulation, and then evacuating the reaction kettle and injecting He.
  • There are 11 preset temperature points in the thermal simulation experiment which are 250°C, 300°C, 320°C, 335°C, 350°C, 360°C, 390°C, 440°C, 500°C, 540°C, and 580°C respectively. These preset temperatures cover the different stages from the start of oil and gas generation to the end.
  • the programmed heating rate is 20°C/d; when the simulated temperature is between 200°C and 250°C, the programmed heating rate is 5°C/d; for the 2nd to 11th preset temperature points, before the simulated temperature reaches the temperature of the preset temperature point before the target preset temperature point, the programmed heating rate is 20°C/d, and the simulated temperature is at the target temperature.
  • the programmed heating rate is 5°C/d; after the simulated temperature reaches the preset temperature, the preset temperature is maintained and kept at a constant temperature for 10 hours.
  • the preset pressure for hydrocarbon expulsion is 7MPa, and the amount of oil and gas discharged during the thermal simulation process is used to calculate the amount of oil and gas produced per unit mass of rock.
  • the TOC of each group of source rock samples is measured according to the national standard GB/T 19145-2003 "Determination of Total Organic Carbon in Sedimentary Rocks"; Ro is measured according to the industry standard SY/T 5124-2012 “Vitrinite in Sedimentary Rocks” Measurement method of reflectance”.
  • Cumulative oil production mg/g rock
  • Cumulative gas production mL/g rock
  • Ro vitrinite reflectance, %
  • T pyrolysis simulation temperature, °C
  • x 1 and x 2 are empirical coefficients, which can be 0.13797 and 0.005667, respectively.
  • the oil output of shale is related to shale Ro and TOC. According to the results of thermal simulation experiments, a relationship model between oil production and TOC is established, and the empirical parameters in the model are extracted to establish a model with Ro, and the following formula (2) and Fig. 3 shows the oil output evaluation model.
  • Qpo is the remaining oil output per unit mass of shale (to be determined), mg/g rock; Ro is the vitrinite reflectance, %; TOC is the organic carbon content, wt%; a 1 , a 2 , a 3 , a 4 , a 5 , and a 6 are empirical parameters, and a 1 and a 6 are respectively 0.99892 and 0.01538; when Ro ⁇ 0.76%, a 2 and a 3 are respectively 0.4265 and 0.7516, and when 0.76% ⁇ Ro ⁇ When 1.0%, a 2 and a 3 are respectively -0.4593 and 1.41; when Ro>0.98%, a 2 and a 3 are respectively -4.164 and 5.3161; when Ro ⁇ 0.77%, a 4 and a 5 are respectively 0.068 , 1.1297, when 0.775% ⁇ Ro ⁇ 1.06%, a 4 and a 5 were -2.6881 and 3.2629, respectively, and when Ro>1.06%, a 4 and
  • Shale gas production is related to shale Ro and TOC. According to the results of thermal simulation experiments, a relationship model between produced gas and TOC is established, and the empirical parameters in the model are extracted to establish a model with Ro, and the following formula (3) and Figure 4 are established. The output gas evaluation model shown.
  • Qpg is the remaining gas output per unit mass of shale, m 3 /t ⁇ rock;
  • Ro is the vitrinite reflectance, %;
  • TOC is the organic carbon content, wt%;
  • b 1 , b 2 , b 3 , b 4 , b 5 , b 6 , b 7 , b 8 , b 9 , b 10 , b 11 , b 12 , b 13 , b 14 , b 15 are empirical parameters, which are 1.0062, 0.9478, 0.5744, -0.0997, - 1.1745, 3.4118, 2.1756, 1.5235, -2.3651, -0.2334, 2.9012, -2.9174, -0.0967, 0.5035, -0.4776.
  • the solution provided by the example of the present invention overcomes the problem that in the prior art, only by providing simulation experiments or only providing shale original TOC and original HI or original H/C, and only obtaining the amount of generated oil and gas and the amount of retained oil and gas, can the output be obtained.
  • Defects in oil and gas volume the established relationship between TOC, Ro and produced oil and gas volume (shale in-situ conversion oil production prediction model and shale in-situ conversion gas production prediction model) overcomes the inability to evaluate (prediction) the existing technology. )
  • the defects of oil and gas production of different TOC and Ro shale can predict the oil production and gas production corresponding to different shale TOC and Ro values.
  • equations (3)-(4) can be used to obtain the oil and gas produced by in-situ conversion of shale in the evaluated area.
  • the quantitative data is used to carry out the evaluation and optimization of recoverable oil and gas resources and "sweet spots”.
  • Fig. 5 is the relationship between the maximum recoverable oil amount and the maximum recoverable gas amount of the experimental thermally simulated shale sample.
  • the lower limit of the recoverable oil volume per unit mass of rock converted in-situ is based on the cumulative oil output of any production well group in the same development area for in-situ conversion of shale.
  • the lower limit value of the quantity and the rock quality of the effective heating zone controlled by the production well group are obtained according to the following formula (4).
  • Q po_limt is the lower limit of oil recovery per unit mass of rock in situ conversion of shale, mg/g rock;
  • Q oil_limt is the lower limit of cumulative oil output of a production well group, mg;
  • Wt rock is the Rock mass in effective heating zone controlled by production well group, g.
  • the use of horizontal wells, according to a production well group comprises 10 heater well and a production well, heating wells using 15 m well spacing, horizontal well length of 1200 meters, the rock mass effective heating zone of 708 ⁇ 10 4 tons.
  • the lower limit of the oil output of a production well group is 10 ⁇ 10 4 tons, and the lower limit of the recoverable oil per unit mass of rock calculated from the above formula (4) is 14 mg/g ⁇ rock.
  • the lower limit of TOC for in-situ conversion of shale corresponding to the lower limit of the recoverable oil per unit mass of rock is derived according to formula (2).
  • the pre-established effective shale The TOC lower limit prediction model of in situ transformation is shown in the following formula (5).
  • TOC limt is the lower limit of the total organic carbon content of effective shale, wt%;
  • Q po_limt is the lower limit of oil recovery per unit mass of rock converted in situ by shale, mg/g rock;
  • Ro is the shale to be tested Vitrinite reflectance of rock, %;
  • c 1 , c 2 , c 3 , c 4 , c 5 , c 6 are empirical parameters, c 1 and c 4 are 1.0011 and 0.0154, respectively; when Ro ⁇ 0.77%, c 2 and c 3 are 0.068 and 1.1297 respectively, when 0.775% ⁇ Ro ⁇ 1.06%, c 2 and c 3 are -2.6881 and 3.2629 respectively, and when Ro>1.06%, c 2 and c 3 are -3.5488 and 4.1449 respectively; when when Ro ⁇ 0.76%, c 5, c 6 are 0.4265,0.7516, when 0.76% ⁇ when Ro ⁇ 1.0%, c 5, c 6 respectively
  • Figure 6 shows the variation of the lower limit of total organic carbon content of effective shale calculated by formula (5) with Ro when the lower limit of recoverable oil per unit mass of rock is 14 mg/g rock.
  • the lower limit value of the corresponding total organic carbon content of the effective shale can be obtained; when Ro is about 0.8%, the minimum value of the corresponding lower limit value of the total organic carbon content of the effective shale is about 6%.
  • the effective thickness of shale, effective thickness interval and effective shale for in-situ transformation of shale are determined according to the following principles rock distribution area.
  • the set value of 5 meters is used as the effective thickness of the shale.
  • the depth section corresponding to the apparent effective thickness of shale is the section with apparent effective thickness; between two adjacent sections with apparent effective thickness, when the total organic carbon content of shale logging interpretation is less than the total organic carbon content of effective shale.
  • the set value When the continuous thickness of the limit value is less than the set value of 0.5-5 meters, the set value is determined as 2 meters, and the interval is calculated into the effective thickness of the apparent shale; when the total organic When the continuous thickness whose carbon content is less than the lower limit of the total organic carbon content of the effective shale is greater than the set value of 0.5-5 meters, the set value is determined to be 2 meters, and the apparent effective shale thickness is not calculated for this interval middle;
  • the apparent shale effective thickness is greater than the set value of 3-15 meters, the set value of 5 meters is used as the apparent shale effective thickness, and the apparent shale effective thickness is the shale effective thickness.
  • the interval of is the effective thickness interval;
  • the apparent shale effective thickness is less than or equal to the set value of 3-15 meters, the set value of 5 meters is used as the apparent shale effective thickness, but the apparent shale effective thickness cannot be used as the shale effective thickness, and thus cannot be used as an independent development interval , the recoverable resource is not calculated for this interval; when the longitudinal distance between two or more effective thickness intervals exceeds the preset thickness value of 0.5-5 meters (preferably 3 meters), each effective thickness interval will be Treat it as a separate effective thickness section of shale, that is, treat it as an independent development stratum;
  • the three-point method, five-point method, finite element method, kriging method, linear interpolation method, nonlinear interpolation method and other non-equidistant interpolation methods are used to obtain the
  • the effective thickness distribution of shale in the evaluation area, the grid spacing of the non-equidistant interpolation method adopts the preset value of 0.1-10km (for example, 2km), and the effective thickness of the shale in the evaluated area is greater than the preset value of the effective thickness by 3-15 meters.
  • 5 meters are used as the boundary of the effective shale thickness distribution area, and the area with an effective shale thickness greater than 5 meters is the effective shale distribution area.
  • FIG. 7 is a diagram showing the situation where there is no interlayer in the effective shale interval
  • FIG. 8 is a diagram showing the situation in which the interlayer exists in the effective shale interval.
  • the TOC of logging interpretation obtain the TOC value, rock density value, and measurement spacing value of the logging interpretation point in the effective shale interval, and use the pre-established recoverable oil amount to predict the Ro value of the well point in the target layer obtained by the analysis and test.
  • the model and the recoverable gas volume prediction model are used to obtain the recoverable oil volume per unit mass of rock and the recoverable gas volume per unit mass of rock at the logging interpretation point.
  • recoverable oil resource abundance value and recoverable gas resource abundance value in the effective shale interval of the evaluated well are obtained according to the models shown in the following equations (6) and (7) respectively.
  • AOR is the abundance of recoverable oil resources in the assessed area, 10,000 tons/km 2 ;
  • AGR is the abundance of recoverable gas resources in the assessed area, 100 million cubic meters/km 2 ;
  • Q po_i is the i-th measurement in the effective interval Recoverable oil volume per unit mass of rock at the well point, mg/g rock;
  • Q pg_i is the recoverable gas volume per unit mass of rock at the ith logging point in the effective interval, m 3 /t rock;
  • ⁇ i is the effective interval Rock density value of the ith logging point, g/cm 3 ;
  • L inter is the logging interval of the evaluated well, m;
  • n is the total number of logging points in the effective interval, n is an integer.
  • Three-point method, five-point method, finite element method, kriging method, linear interpolation method and nonlinear interpolation method can be used according to the abundance value of recoverable oil resources and recoverable gas resources of all well points in the evaluated area.
  • non-equidistant interpolation methods such as method, obtain the planar distribution of recoverable oil resource abundance and recoverable gas resource abundance in the evaluated area.
  • the recoverable oil resources and recoverable gas resources of the effective shale distribution area in the evaluated area are obtained by using the models shown in equations (8) and (9) respectively.
  • NO is the recoverable oil resource in the evaluated area, ten thousand tons
  • NG is the recoverable gas resource in the evaluated area, in billion cubic meters
  • AOR j is the recoverable oil resource abundance of the jth grid in the effective shale distribution area, 10,000 tons/km 2
  • AGR j is the recoverable gas resource abundance of the j-th grid in the effective shale distribution area, 100 million cubic meters/km 2
  • a j is the area of the j-th grid in the effective shale distribution area , km 2
  • m is the number of grids in the effective shale distribution area, an integer.
  • Fig. 9 is the TOC distribution map for the shale of Chang 7 3 sub-member in the Ordos Basin, the TOC obtained by logging interpretation is greater than TOC limt. The greater the potential for bit conversion.
  • Fig. 10 is the Ro distribution map obtained by core analysis for the shale of the Chang 7 3 sub-member in the Ordos Basin. From Fig. 9, we can see the maturity of shale suitable for in-situ conversion mining and the potential for in-situ conversion of shale , where the smaller the Ro, the greater the potential for in situ transformation.
  • FIG 11 is directed Ordos Basin 73 subsegmental shale, shale effective thickness distribution according to FIG method provided in the embodiment of the present invention is obtained, wherein the effective thickness greater shale, in situ transforming potential greater.
  • FIG 13 is a profile for the abundance of available resources gas production method Ordos Basin 73 subsegmental shale, using the provided embodiment of the present invention obtained, wherein the larger gas recoverable resource abundance per unit area of the original shale The larger the recoverable gas resources of in situ transformation, the more favorable it is for in situ transformation and development.
  • the in-situ conversion of the shale in Chang 7 3rd member of the Ordos Basin obtained by the method provided by the embodiment of the present invention has a recoverable oil resource of 45.2 billion tons and a recoverable gas resource of 37 trillion cubic meters.
  • the technical solutions provided by the examples of the present invention realize the quantitative evaluation of recoverable oil resources and recoverable gas resources by in-situ conversion of different TOC and Ro shale.
  • the embodiment of the present invention also provides a prediction device for in-situ conversion of recoverable oil and gas resources in shale, because the principle of the device for solving problems is similar to the prediction method for in-situ conversion of shale oil and gas resources. , so the implementation of the device may refer to the implementation of the method, and the repeated parts will not be repeated.
  • 14 is a schematic structural diagram of a device for predicting recoverable oil and gas resources for in-situ conversion of shale according to an embodiment of the present invention. As shown in Figure 14, the predicting device for in-situ conversion of shale recoverable oil and gas resources includes:
  • the data acquisition module 1 is used to acquire the total organic carbon content and vitrinite reflectance of the shale to be tested in the area to be evaluated;
  • Model building module 2 for in-situ conversion of shale oil recovery prediction model used to establish a shale in-situ conversion oil recovery prediction model, and use shale according to the total organic carbon content and vitrinite reflectance of the shale to be tested
  • the in-situ converted recoverable oil quantity prediction model can obtain the recoverable oil quantity of the shale to be tested;
  • Module 3 for the prediction model of recoverable gas volume of shale in-situ transformation is used to establish the recoverable gas volume prediction model of shale in-situ transformation, and use shale according to the total organic carbon content and vitrinite reflectance of the shale to be measured.
  • the in-situ converted recoverable gas volume prediction model can obtain the recoverable gas volume of the shale to be tested;
  • Model establishment module 4 of the lower limit value prediction model of the total organic carbon content of effective shale which is used to establish a prediction model for the lower limit value of the total organic carbon content of effective shale, and predict the lower limit value of the total organic carbon content of effective shale, and predict the lower limit value of total organic carbon content according to the in-situ transformation of shale.
  • the limit value and the vitrinite reflectance of the shale to be tested are obtained to obtain the lower limit value of the total organic carbon content of the effective shale;
  • the module 5 for determining the effective thickness, effective thickness interval and effective shale distribution area of shale in-situ transformed shale is used for the total organic carbon content and the total organic carbon of the effective shale according to the logging interpretation of the area to be evaluated.
  • the lower limit value of the content is determined, and the effective thickness of shale, effective thickness interval and effective shale distribution area for in-situ transformation of shale are determined;
  • Model building module 6 for recoverable oil resource abundance value and recoverable gas resource abundance value in the effective thickness interval which is used to respectively establish the recoverable oil resource abundance value and recoverable gas resource abundance value model in the effective thickness interval , and according to the recoverable oil volume per unit mass of rock and the recoverable gas volume per unit mass of rock at the logging interpretation point, the recoverable oil resource abundance value and recoverable gas resource abundance value in the effective thickness interval of the evaluated well are obtained respectively;
  • a module 7 for establishing a prediction model for recoverable oil resources and recoverable gas resources is used to respectively establish a prediction model for recoverable oil resources and recoverable gas resources, and obtain recoverable oil according to the prediction models for recoverable oil resources and recoverable gas resources resources and recoverable gas resources.
  • the model building module for predicting the recoverable oil volume of the in-situ conversion of shale is specifically used for producing oil volume data obtained by performing thermal simulation experiments on a plurality of different shale samples, and the total oil volume of the shale samples.
  • Organic carbon content and vitrinite reflectance establish a relationship model between oil production and total organic carbon content, and then extract the empirical parameters in the model and vitrinite reflectance to establish a model, so as to establish the shale in situ Transformed oil recovery prediction model.
  • the in-situ conversion of shale oil recovery prediction model establishment module is further used to establish the shale in-situ conversion of shale oil prediction model according to the following formula:
  • Q po is the recoverable oil amount of the shale to be tested, mg/g rock
  • Ro is the vitrinite reflectance of the shale to be tested, %
  • TOC is the total organic carbon content of the shale to be tested, wt%
  • a 1 , a 2 , a 3 , a 4 , a 5 , and a 6 are empirical parameters.
  • the model building module for predicting the recoverable gas volume of in-situ conversion of shale is specifically used for producing gas volume data obtained from thermal simulation experiments on multiple different shale samples, and the total organic Carbon content and vitrinite reflectance, establish the relationship model between the produced gas and total organic carbon content, and then extract the empirical parameters and vitrinite reflectance in the model to establish a model, so as to establish the in-situ transformation of the shale.
  • Recoverable gas volume prediction model is specifically used for producing gas volume data obtained from thermal simulation experiments on multiple different shale samples, and the total organic Carbon content and vitrinite reflectance, establish the relationship model between the produced gas and total organic carbon content, and then extract the empirical parameters and vitrinite reflectance in the model to establish a model, so as to establish the in-situ transformation of the shale.
  • Recoverable gas volume prediction model is specifically used for producing gas volume data obtained from thermal simulation experiments on multiple different shale samples, and the total organic Carbon content and vitrinite reflectance, establish
  • the model building module for predicting the recoverable gas volume of the in-situ conversion of shale is further configured to establish the prediction model of the recoverable gas volume of the in-situ transformation of shale according to the following formula:
  • Q pg is the recoverable gas volume of the shale to be tested, m 3 /t ⁇ rock;
  • Ro is the vitrinite reflectance of the shale to be tested, %;
  • TOC is the total organic carbon content of the shale to be tested, wt% ;
  • b 1 , b 2 , b 3 , b 4 , b 5 , b 6 , b 7 , b 8 , b 9 , b 10 , b 11 , b 12 , b 13 , b 14 , b 15 are empirical parameters;
  • w 1 is 0.5%-1.0%, w 2 is 1.0%-1.4%.
  • the model establishment module for predicting the lower limit value of the total organic carbon content of the effective shale includes a unit for obtaining the lower limit value of the recoverable oil amount per unit mass of rock converted in situ by the shale, which is used for obtaining the lower limit value of the recoverable oil per unit mass of rock transformed by the shale in situ.
  • the lower limit of the cumulative oil output of any production well group in the same development area converted and the rock quality of the effective heating zone controlled by the production well group can be obtained according to the following formula to obtain the shale in-situ converted unit mass of rock.
  • Q po_limt is the lower limit of oil recovery per unit mass of rock for in-situ conversion of shale, mg/g rock;
  • Q oil_limt is the lower limit of cumulative oil output of a production well group converted in-situ of shale, mg;
  • Wt rock is the rock mass in the effective heating zone controlled by the production well group converted in situ by shale, g.
  • the lower limit value prediction model building module of the total organic carbon content of the effective shale is specifically used for predicting the recoverable oil amount according to the in-situ transformation of shale and the recoverable oil amount per unit mass of rock transformed in situ.
  • the lower limit of the total organic carbon content of the effective shale is established according to the following formula:
  • TOC limt is the lower limit of total organic carbon content of effective shale, wt%;
  • Q po_limt is the lower limit of recoverable oil per unit mass of rock converted in situ by shale, mg/g rock;
  • Ro is to be measured Vitrinite reflectance of shale, %;
  • c 1 , c 2 , c 3 , c 4 , c 5 , and c 6 are empirical parameters.
  • the module for determining the effective thickness, effective thickness interval and effective shale distribution area of shale in-situ converted shale is specifically used for the total organic carbon content and the The lower limit of the total organic carbon content of effective shale is determined according to the following principles:
  • the set value of 5 meters is used as the effective thickness of the shale.
  • the depth section corresponding to the apparent effective thickness of shale is the section with apparent effective thickness; between two adjacent sections with apparent effective thickness, when the total organic carbon content of shale logging interpretation is less than the total organic carbon content of effective shale.
  • the set value When the continuous thickness of the limit value is less than the set value of 0.5-5 meters, the set value is determined as 2 meters, and the interval is calculated into the effective thickness of the apparent shale; when the total organic When the continuous thickness whose carbon content is less than the lower limit of the total organic carbon content of the effective shale is greater than the set value of 0.5-5 meters, the set value is determined to be 2 meters, and the apparent effective shale thickness is not calculated for this interval middle;
  • the apparent shale effective thickness is greater than the set value of 3-15 meters, the set value of 5 meters is used as the apparent shale effective thickness, and the apparent shale effective thickness is the shale effective thickness.
  • the interval of is the effective thickness interval;
  • the apparent shale effective thickness is less than or equal to the set value of 3-15 meters, the set value of 5 meters is used as the apparent shale effective thickness, but the apparent shale effective thickness cannot be used as the shale effective thickness, and thus cannot be used as an independent development interval , the recoverable resources are not calculated for this interval; when the longitudinal distance between two or more effective thickness intervals exceeds the preset thickness value of 0.5-5 meters, each effective thickness interval will be effective as a separate shale.
  • Thickness section treatment that is, treatment as an independent development layer system;
  • the effective thickness distribution of shale in the evaluated area is obtained by the non-equidistant interpolation method, and the grid spacing of the non-equidistant interpolation method adopts the preset value of 0.1-10km , when the effective thickness of shale in the evaluated area is greater than the preset effective thickness of 3-15 meters, 5 meters are used as the boundary of the effective shale thickness distribution area, and the area with an effective shale thickness greater than 5 meters is the effective shale distribution area.
  • the model building module for the abundance value of recoverable oil resources and the abundance value of recoverable gas resources in the effective thickness interval is specifically used for recovering oil and gas volume per unit mass of rock, logging spacing, rock density and effective
  • the recoverable oil resource abundance value and recoverable gas resource abundance value model in the effective shale interval are respectively established according to the recoverable oil volume and recoverable gas volume of the rock in the effective thickness interval per unit area.
  • the model building module for the abundance value of recoverable oil resources and the abundance value of recoverable gas resources in the effective thickness interval is further configured to respectively establish the abundance of recoverable oil resources in the effective shale interval according to the following formula: value and recoverable gas resource abundance value model:
  • AOR is the abundance of recoverable oil resources in the effective shale interval of the area to be evaluated, 10,000 tons/km 2 ;
  • AGR is the abundance of recoverable gas resources in the effective shale interval of the area to be evaluated, 100 million cubic meters/km 2 ;
  • Q po_i is the oil recovery per unit mass of the i-th logging point in the effective thickness interval of the area to be evaluated, mg/g rock;
  • Q pg_i is the i-th logging point in the effective thickness interval of the area to be evaluated
  • ⁇ i is the rock density value of the i-th logging point in the effective thickness interval of the area to be evaluated, g/cm 3 ;
  • L inter is the value of the well to be evaluated Log spacing, m;
  • n is the total number of logging points in the effective thickness interval, n is an integer.
  • the model building module for the abundance value of recoverable oil resources and the abundance value of recoverable gas resources in the effective thickness interval includes the recoverable oil quantity per unit mass of rock and the recoverable quantity of rock per unit mass at the logging interpretation point.
  • the total organic carbon content of the logging interpretation in the area to be evaluated the total organic carbon content, rock density value, and measurement spacing value of the logging interpretation point in the effective shale interval are obtained, and then according to the logging interpretation point in the effective shale interval
  • the total organic carbon content, rock density value, measurement distance value, and vitrinite reflectance of the well point in the target layer are obtained by using the oil recovery prediction model of shale in-situ transformation and the recoverable gas volume prediction model of shale in-situ transformation.
  • the predictable model building module for recoverable oil resources and recoverable gas resources is specifically used for
  • the prediction models for recoverable oil resources and recoverable gas resources are established respectively according to the following formulas:
  • NO is the recoverable oil resource in the area to be evaluated, 10,000 tons
  • NG is the recoverable gas resource in the area to be evaluated, 100 million cubic meters
  • AOR j is the recoverable oil resource abundance of the jth grid in the effective shale distribution area, 10,000 tons/km 2
  • AGR j is the recoverable gas resource abundance of the j-th grid in the effective shale distribution area, 100 million cubic meters/km 2
  • a j is the area of the j-th grid in the effective shale distribution area , km 2
  • m is the grid number in the effective shale distribution area, and m is an integer.

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Abstract

一种页岩原位转化可采油气资源量的预测方法及装置，该方法包括建立页岩原位转化的可采油量预测模型，并获取待测页岩的可采油量；建立页岩原位转化的可采气量预测模型，并获取待测页岩的可采气量；建立有效页岩的总有机碳含量下限值预测模型，并获取有效页岩的总有机碳含量下限值；根据待评价区的测井解释的总有机碳含量和有效页岩的总有机碳含量下限值，确定页岩原位转化的页岩有效厚度、有效厚度层段及有效页岩分布区；建立有效厚度层段内的可采油资源丰度值和可采气资源丰度值模型，并获取被评价井有效厚度层段内的可采油资源丰度值和可采气资源丰度值；建立可采油资源量和可采气资源量预测模型，并获取可采油资源量和可采气资源量。

Description

一种页岩原位转化可采油气资源量的预测方法及装置 技术领域
本发明涉及一种页岩原位转化可采油气资源量的预测方法及装置，属于油气勘探开发技术领域。
背景技术
页岩是指总有机碳含量(TOC)较高，具有纹层状页理的沉积岩石。当页岩的成熟度较低，即镜质体反射率(Ro)小于1.0％时，页岩中孔隙不发育，流体流动困难，用现有的水平井体积压裂技术无法实现商业规模开发，但可利用原位转化技术对成熟度较低的页岩进行开发。原位转化技术是通过原位加热方法使页岩中的未转化有机质转化为油气，将原位转化的油气与滞留于页岩中的油气同时采出的技术。这里的页岩是具有中低成熟度，即Ro小于1.0％的页岩的统称，包括中低成熟度页岩和未成熟的油页岩。
据初步研究估算，世界范围内页岩原位转化可采资源量大于1.5万亿吨、天然气技术可采资源量约1300万亿立方米；中国页岩原位转化可采资源量大于800亿吨、天然气可采资源量大于60万亿立方米；是常规石油、天然气可采资源量的3倍以上，潜力巨大。
现有技术中预测中低成熟度页岩油原位转化产出油气的方案有两种，可借鉴开展可采油气资源量的评价，但尚没有页岩原位转化可采资源量预测技术。一是根据页岩的原始氢碳比(H/C)、原始总有机碳含量(TOC)和Ro值，建立页岩从原始状态开始的生成油气量模型和不同Ro阶段的滞留油气量模型，根据生成油气量和滞留油气量，建立产出油气量模型，可以外推开展原位转化产出油气资源量的评价。二是根据页岩的原始氢指数(HI)、原始总有机碳含量(TOC)和Ro值，建立页岩从原始状态开始的生成油气量模型和不同Ro阶段的滞留油气量模型，根据生成油气量和滞留油气量，建立产出油气量模型，可以外推开展原位转化产出油气资源量的评价。
现有技术中对中低成熟度页岩油产出油气量评价的两种方案，在外推开展原位转化可采资源量预测时均存在缺陷：一是必须获得页岩的原始氢碳比(H/C)、原始总有机碳含量(TOC)和Ro值；而页岩本身都经历了一定的热演化，并非原始状态， 利用现有技术很难准确得到页岩的原始H/C或原始HI、原始TOC，因此由原始H/C或原始HI和原始TOC，得到的产出油气量存在较大误差。二是必须确定页岩从原始状态开始的生成油气量和不同Ro阶段的滞留油气量，才能根据生成油气量和滞留油气量得到产出油气量，在没有原始状态页岩及未开展热模拟实验情况下，无法准确确定生成油气量和滞留油气量，也就无法获得原位转化的产出油气量，更无法外推获得页岩的可采油气量。
综上，现有相关技术利用具有一定热演化的页岩无法准确获得页岩原始H/C、原始HI、原始TOC、生成油气量和滞留油气量，进而无法准确开展页岩原位转化产出油气量研究。同时，页岩原位转化可采油气资源评价技术与现有技术存在很大差别，目前尚未形成页岩原位转化可采油气资源预测技术。
因此，提供一种新型的页岩原位转化可采油气资源量的预测方法及装置已经成为本领域亟需解决的技术问题。
发明内容
为了解决上述的缺点和不足，本发明的一个目的在于提供一种页岩原位转化可采油气资源量的预测方法。
本发明的另一个目的在于提供一种页岩原位转化可采油气资源量的预测装置。
本发明的又一个目的还在于提供一种计算机设备。
本发明的再一个目的还在于提供一种计算机可读存储介质。本发明可以定量预测页岩原位转化可采油气资源量，提高页岩原位转化可采油气资源量的预测精度和效率。
为了实现以上目的，一方面，本发明提供了一种页岩原位转化可采油气资源量的预测方法，其中，所述页岩原位转化可采油气资源量的预测方法包括：
获取待评价区待测页岩的总有机碳含量和镜质体反射率；
建立页岩原位转化的可采油量预测模型，并根据待测页岩的总有机碳含量和镜质体反射率利用页岩原位转化的可采油量预测模型，获取待测页岩的可采油量；
建立页岩原位转化的可采气量预测模型，并根据待测页岩的总有机碳含量和镜质体反射率利用页岩原位转化的可采气量预测模型，获取待测页岩的可采气量；
建立有效页岩的总有机碳含量下限值预测模型，并根据页岩原位转化的单位质量岩石的可采油量下限值及待测页岩的镜质体反射率，获取有效页岩的总有机碳含量下 限值；
根据待评价区的测井解释的总有机碳含量和所述有效页岩的总有机碳含量下限值，确定页岩原位转化的页岩有效厚度、有效厚度层段及有效页岩分布区；
分别建立有效厚度层段内的可采油资源丰度值和可采气资源丰度值模型，并根据测井解释点的单位质量岩石的可采油量和单位质量岩石的可采气量分别获取被评价井有效厚度层段内的可采油资源丰度值和可采气资源丰度值；
分别建立可采油资源量和可采气资源量预测模型，并根据可采油资源量和可采气资源量预测模型获取可采油资源量和可采气资源量。
在以上所述的预测方法中，优选地，建立页岩原位转化的可采油量预测模型，包括：
根据对多个不同页岩样品进行热模拟实验获得的产出油量数据，以及页岩样品的总有机碳含量和镜质体反射率，建立产出油量与总有机碳含量之间的关系模型，再提取模型中的经验参数与镜质体反射率建立模型，从而建立所述页岩原位转化的可采油量预测模型。
在以上所述的预测方法中，优选地，按照以下公式建立所述页岩原位转化的可采油量预测模型：
Figure PCTCN2021104637-appb-000001
其中，Q po为待测页岩的可采油量，mg/g·rock；Ro为待测页岩的镜质体反射率，％；TOC为待测页岩的总有机碳含量，wt％；a 1、a 2、a 3、a 4、a 5、a 6为经验参数。
其中，待测页岩的可采油量Q po的单位mg/g·rock中的g·rock是指每g岩石的质量；
此外，本领域技术人员可以通过待评价区的热模拟实验结果得到以上经验参数a 1、a 2、a 3、a 4、a 5、a 6的具体数值。
在以上所述的预测方法中，优选地，建立页岩原位转化的可采气量预测模型，包括：
根据对多个不同页岩样品进行热模拟实验获得的产出气量数据，以及页岩样品的总有机碳含量和镜质体反射率，建立产出气量与总有机碳含量之间的关系模型，再提取模型中的经验参数与镜质体反射率建立模型，从而建立所述页岩原位转化的可采气 量预测模型。
在以上所述的预测方法中，优选地，按照以下公式建立所述页岩原位转化的可采气量预测模型：
Figure PCTCN2021104637-appb-000002
其中，Q pg为待测页岩的可采气量，m 3/t·rock；Ro为待测页岩的镜质体反射率，％；TOC为待测页岩的总有机碳含量，wt％；b 1、b 2、b 3、b 4、b 5、b 6、b 7、b 8、b 9、b 10、b 11、b 12、b 13、b 14、b 15为经验参数；w 1为0.5％-1.0％，w 2为1.0％-1.4％。
其中，待测页岩的可采气量Q pg单位m 3/t·rock中的t·rock是指每吨岩石的质量；
此外，本领域技术人员可以通过待评价区的热模拟实验结果得到以上经验参数b 1、b 2、b 3、b 4、b 5、b 6、b 7、b 8、b 9、b 10、b 11、b 12、b 13、b 14、b 15的具体数值。
在以上所述的预测方法中，优选地，所述页岩原位转化的单位质量岩石的可采油量下限值是根据页岩原位转化的同一开发区域(同一开发区域是指具有相似的原位转化地质条件、相似的开发工艺的开发区域)内的任一个生产井组的累积产出油量下限值和该生产井组控制的有效加热区的岩石质量按照以下公式获取得到的：
Figure PCTCN2021104637-appb-000003
其中，Q po_limt为页岩原位转化的单位质量岩石可采油量下限值，mg/g·rock；Q oil_limt为页岩原位转化的一个生产井组的累计产出油量下限值，mg；Wt rock为页岩原位转化的该生产井组控制的有效加热区的岩石质量，g。
在以上所述的预测方法中，优选地，建立有效页岩的总有机碳含量下限值预测模型，包括：根据页岩原位转化的可采油量预测模型及页岩原位转化的单位质量岩石的可采油量下限值，按照以下公式建立所述有效页岩的总有机碳含量下限值预测模型：
Figure PCTCN2021104637-appb-000004
其中，TOC limt为有效页岩的总有机碳含量下限值，wt％；Q po_limt为页岩原位转化的单位质量岩石的可采油量下限值，mg/g·rock；Ro为待测页岩的镜质体反射率，％； c 1、c 2、c 3、c 4、c 5、c 6为经验参数。
本领域技术人员可以通过待评价区的热模拟实验结果、开发工艺及开发成本等得到以上经验参数c 1、c 2、c 3、c 4、c 5、c 6的具体数值。
在以上所述的预测方法中，优选地，根据待评价区的测井解释的总有机碳含量和所述有效页岩的总有机碳含量下限值，根据以下原则确定页岩原位转化的页岩有效厚度、有效厚度层段及有效页岩分布区：
当页岩的测井解释的总有机碳含量大于有效页岩的总有机碳含量下限值的连续厚度大于设定值1-15米时，采用设定值5米作为视页岩有效厚度，视页岩有效厚度对应的深度段为视有效厚度层段；相邻两个视有效厚度层段之间，当页岩的测井解释的总有机碳含量小于有效页岩的总有机碳含量下限值的连续厚度小于设定值0.5-5米时，将所述设定值确定为2米，并将该层段计算到视页岩有效厚度中；当页岩的测井解释的总有机碳含量小于有效页岩的总有机碳含量下限值的连续厚度大于设定值0.5-5米时，将所述设定值确定为2米，且该层段不计算到视有效页岩厚度中；
当视页岩有效厚度大于设定值3-15米时，采用设定值5米作为视页岩有效厚度，所述视页岩有效厚度即为页岩有效厚度，页岩有效厚度顶底对应的层段为有效厚度层段；
当视页岩有效厚度小于等于设定值3-15米时，采用设定值5米作为视页岩有效厚度，但视页岩有效厚度不能作为页岩有效厚度，进而不能作为独立开发层段，该层段不计算可采资源量；当两个或多个有效厚度层段之间纵向距离超过预设厚度值0.5-5米时，每个有效厚度层段将分别作为单独的页岩有效厚度段处理，即作为独立开发层系处理；
根据获得的被评价区井点的页岩有效厚度，采用非等边距内插方法获得被评价区的页岩有效厚度分布，非等边距内插方法网格间距采用预设值0.1-10km(更优选为2km)，被评价区内页岩有效厚度大于有效厚度预设值3-15米时，采用5米作为页岩有效厚度分布区边界，页岩有效厚度大于5米的区域为有效页岩分布区。
其中，本领域技术人员可以根据系统取心井的岩心分析化验结果标定测井资料，获取得到待评价区的测井解释数据；
所述设定值可以根据原位转化需要和地质情况确定；
所述非等边距内插方法包括三点法、五点法、有限元法、克里金法、线性插值法、 非线性插值法等。
在以上所述的预测方法中，优选地，分别建立有效页岩层段内的可采油资源丰度值和可采气资源丰度值模型，包括：
根据单位质量岩石可采油气量、测井间距、岩石密度和有效厚度层段，按照单位面积的有效厚度层段内岩石可采油量、可采气量，分别建立有效页岩层段内的可采油资源丰度值和可采气资源丰度值模型。
在以上所述的预测方法中，优选地，按照以下公式分别建立有效页岩层段内的可采油资源丰度值和可采气资源丰度值模型：
Figure PCTCN2021104637-appb-000005
Figure PCTCN2021104637-appb-000006
其中，AOR为待评价区的有效页岩层段内的可采油资源丰度，万吨/km 2；AGR为待评价区的有效页岩层段内的可采气资源丰度，亿立方米/km 2；Q po_i为待评价区的有效厚度层段内第i测井点的单位质量岩石可采油量，mg/g·rock；Q pg_i为待评价区的有效厚度层段内第i测井点的单位质量岩石可采气量，m 3/t·rock；ρ i为待评价区的有效厚度层段内第i测井点的岩石密度值，g/cm 3；L int er为被评价井的测井间距，m；n为有效厚度层段内的测井点总数，n为整数。
在以上所述的预测方法中，优选地，测井解释点的单位质量岩石的可采油量和单位质量岩石的可采气量按照以下步骤获取：
根据待评价区的测井解释的总有机碳含量，获取有效页岩层段内测井解释点的总有机碳含量、岩石密度值、测量间距值，再根据有效页岩层段内测井解释点的总有机碳含量、岩石密度值、测量间距值及目的层井点的镜质体反射率，利用页岩原位转化的可采油量预测模型及页岩原位转化的可采气量预测模型，获取测井解释点的单位质量岩石的可采油量和单位质量岩石的可采气量。
在以上所述的预测方法中，根据以上建立的有效页岩层段内的可采油资源丰度值模型和可采气资源丰度值模型可以获得被评价区内所有井点的可采油资源丰度值、可采气资源丰度值；再根据被评价区内所有井点的可采油资源丰度值、可采气资源丰度值，利用三点法、五点法、有限元法、克里金法、线性插值法、非线性插值法等非等 边距内插方法可以获得被评价区内的可采油资源丰度和可采气资源丰度平面分布；根据该平面分布即可获得有效页岩分布区内第j个网格可采油资源丰度及有效页岩分布区内第j个网格可采气资源丰度。
其中，在本发明较为优选的实施例中，三点法、五点法、有限元法、克里金法、线性插值法、非线性插值法等非等边距内插网格间距采用预设值0.1-10km，优选地采用2km。
在以上所述的预测方法中，优选地，根据有效页岩分布区网格点的可采油气资源丰度和有效页岩分布区面积，按照以下公式分别建立可采油资源量和可采气资源量预测模型：
Figure PCTCN2021104637-appb-000007
Figure PCTCN2021104637-appb-000008
其中，NO为待评价区可采油资源量，万吨；NG为待评价区可采气资源量，亿立方米；AOR j为有效页岩分布区内第j个网格可采油资源丰度，万吨/km 2；AGR j为有效页岩分布区内第j个网格可采气资源丰度，亿立方米/km 2；A j为有效页岩分布区内第j个网格的面积，km 2；m为有效页岩分布区内的网格数，m为整数。
另一方面，本发明还提供了一种页岩原位转化可采油气资源量的预测装置，其中，所述页岩原位转化可采油气资源量的预测装置包括：
数据获取模块，用于获取待评价区待测页岩的总有机碳含量和镜质体反射率；
页岩原位转化的可采油量预测模型建立模块，用于建立页岩原位转化的可采油量预测模型，并根据待测页岩的总有机碳含量和镜质体反射率利用页岩原位转化的可采油量预测模型，获取待测页岩的可采油量；
页岩原位转化的可采气量预测模型建立模块，用于建立页岩原位转化的可采气量预测模型，并根据待测页岩的总有机碳含量和镜质体反射率利用页岩原位转化的可采气量预测模型，获取待测页岩的可采气量；
有效页岩的总有机碳含量下限值预测模型建立模块，用于建立有效页岩的总有机碳含量下限值预测模型，并根据页岩原位转化的单位质量岩石的可采油量下限值及待测页岩的镜质体反射率，获取有效页岩的总有机碳含量下限值；
页岩原位转化的页岩有效厚度、有效厚度层段及有效页岩分布区确定模块，用于根据待评价区的测井解释的总有机碳含量和所述有效页岩的总有机碳含量下限值，确定页岩原位转化的页岩有效厚度、有效厚度层段及有效页岩分布区；
有效厚度层段内的可采油资源丰度值和可采气资源丰度值模型建立模块，用于分别建立有效厚度层段内的可采油资源丰度值和可采气资源丰度值模型，并根据测井解释点的单位质量岩石的可采油量和单位质量岩石的可采气量分别获取被评价井有效厚度层段内的可采油资源丰度值和可采气资源丰度值；
可采油资源量和可采气资源量预测模型建立模块，用于分别建立可采油资源量和可采气资源量预测模型，并根据可采油资源量和可采气资源量预测模型获取可采油资源量和可采气资源量。
在以上所述的预测装置中，优选地，所述页岩原位转化的可采油量预测模型建立模块具体用于根据对多个不同页岩样品进行热模拟实验获得的产出油量数据，以及页岩样品的总有机碳含量和镜质体反射率，建立产出油量与总有机碳含量之间的关系模型，再提取模型中的经验参数与镜质体反射率建立模型，从而建立所述页岩原位转化的可采油量预测模型。
在以上所述的预测装置中，优选地，所述页岩原位转化的可采油量预测模型建立模块进一步用于按照以下公式建立所述页岩原位转化的可采油量预测模型：
Figure PCTCN2021104637-appb-000009
其中，Q po为待测页岩的可采油量，mg/g·rock；Ro为待测页岩的镜质体反射率，％；TOC为待测页岩的总有机碳含量，wt％；a 1、a 2、a 3、a 4、a 5、a 6为经验参数。
在以上所述的预测装置中，优选地，所述页岩原位转化的可采气量预测模型建立模块具体用于根据对多个不同页岩样品进行热模拟实验获得的产出气量数据，以及页岩样品的总有机碳含量和镜质体反射率，建立产出气量与总有机碳含量之间的关系模型，再提取模型中的经验参数与镜质体反射率建立模型，从而建立所述页岩原位转化的可采气量预测模型。
在以上所述的预测装置中，优选地，所述页岩原位转化的可采气量预测模型建立模块进一步用于按照以下公式建立所述页岩原位转化的可采气量预测模型：
Figure PCTCN2021104637-appb-000010
其中，Q pg为待测页岩的可采气量，m 3/t·rock；Ro为待测页岩的镜质体反射率，％；TOC为待测页岩的总有机碳含量，wt％；b 1、b 2、b 3、b 4、b 5、b 6、b 7、b 8、b 9、b 10、b 11、b 12、b 13、b 14、b 15为经验参数；w 1为0.5％-1.0％，w 2为1.0％-1.4％。
在以上所述的预测装置中，优选地，所述有效页岩的总有机碳含量下限值预测模型建立模块包括页岩原位转化的单位质量岩石的可采油量下限值获取单元，用于根据页岩原位转化的同一开发区域内的任一个生产井组的累积产出油量下限值和该生产井组控制的有效加热区的岩石质量按照以下公式获取得到页岩原位转化的单位质量岩石的可采油量下限值：
Figure PCTCN2021104637-appb-000011
其中，Q po_limt为页岩原位转化的单位质量岩石可采油量下限值，mg/g·rock；Q oil_limt为页岩原位转化的一个生产井组的累计产出油量下限值，mg；Wt rock为页岩原位转化的该生产井组控制的有效加热区的岩石质量，g。
在以上所述的预测装置中，优选地，有效页岩的总有机碳含量下限值预测模型建立模块具体用于根据页岩原位转化的可采油量预测模型及页岩原位转化的单位质量岩石的可采油量下限值，按照以下公式建立所述有效页岩的总有机碳含量下限值预测模型：
Figure PCTCN2021104637-appb-000012
其中，TOC limt为有效页岩的总有机碳含量下限值，wt％；Q po_limt为页岩原位转化的单位质量岩石的可采油量下限值，mg/g·rock；Ro为待测页岩的镜质体反射率，％；c 1、c 2、c 3、c 4、c 5、c 6为经验参数。
在以上所述的预测装置中，优选地，所述页岩原位转化的页岩有效厚度、有效厚度层段及有效页岩分布区确定模块具体用于根据待评价区的测井解释的总有机碳含量和所述有效页岩的总有机碳含量下限值，根据以下原则确定页岩原位转化的页岩有 效厚度、有效厚度层段及有效页岩分布区：
当页岩的测井解释的总有机碳含量大于有效页岩的总有机碳含量下限值的连续厚度大于设定值1-15米时，采用设定值5米作为视页岩有效厚度，视页岩有效厚度对应的深度段为视有效厚度层段；相邻两个视有效厚度层段之间，当页岩的测井解释的总有机碳含量小于有效页岩的总有机碳含量下限值的连续厚度小于设定值0.5-5米时，将所述设定值确定为2米，并将该层段计算到视页岩有效厚度中；当页岩的测井解释的总有机碳含量小于有效页岩的总有机碳含量下限值的连续厚度大于设定值0.5-5米时，将所述设定值确定为2米，且该层段不计算到视有效页岩厚度中；
当视页岩有效厚度大于设定值3-15米时，采用设定值5米作为视页岩有效厚度，所述视页岩有效厚度即为页岩有效厚度，页岩有效厚度顶底对应的层段为有效厚度层段；
当视页岩有效厚度小于等于设定值3-15米时，采用设定值5米作为视页岩有效厚度，但视页岩有效厚度不能作为页岩有效厚度，进而不能作为独立开发层段，该层段不计算可采资源量；当两个或多个有效厚度层段之间纵向距离超过预设厚度值0.5-5米时，每个有效厚度层段将分别作为单独的页岩有效厚度段处理，即作为独立开发层系处理；
根据获得的被评价区井点的页岩有效厚度，采用非等边距内插方法获得被评价区的页岩有效厚度分布，非等边距内插方法网格间距采用预设值0.1-10km，被评价区内页岩有效厚度大于有效厚度预设值3-15米时，采用5米作为页岩有效厚度分布区边界，页岩有效厚度大于5米的区域为有效页岩分布区。
在以上所述的预测装置中，优选地，所述有效厚度层段内的可采油资源丰度值和可采气资源丰度值模型建立模块具体用于根据单位质量岩石可采油气量、测井间距、岩石密度和有效厚度层段，按照单位面积的有效厚度层段内岩石可采油量、可采气量，分别建立有效页岩层段内的可采油资源丰度值和可采气资源丰度值模型。
在以上所述的预测装置中，优选地，所述有效厚度层段内的可采油资源丰度值和可采气资源丰度值模型建立模块进一步用于按照以下公式分别建立有效页岩层段内的可采油资源丰度值和可采气资源丰度值模型：
Figure PCTCN2021104637-appb-000013
Figure PCTCN2021104637-appb-000014
其中，AOR为待评价区的有效页岩层段内的可采油资源丰度，万吨/km 2；AGR为待评价区的有效页岩层段内的可采气资源丰度，亿立方米/km 2；Q po_i为待评价区的有效厚度层段内第i测井点的单位质量岩石可采油量，mg/g·rock；Q pg_i为待评价区的有效厚度层段内第i测井点的单位质量岩石可采气量，m 3/t·rock；ρ i为待评价区的有效厚度层段内第i测井点的岩石密度值，g/cm 3；L int er为被评价井的测井间距，m；n为有效厚度层段内的测井点总数，n为整数。
在以上所述的预测装置中，优选地，所述有效厚度层段内的可采油资源丰度值和可采气资源丰度值模型建立模块包括测井解释点的单位质量岩石的可采油量和单位质量岩石的可采气量获取单元，用于：
根据待评价区的测井解释的总有机碳含量，获取有效页岩层段内测井解释点的总有机碳含量、岩石密度值、测量间距值，再根据有效页岩层段内测井解释点的总有机碳含量、岩石密度值、测量间距值及目的层井点的镜质体反射率，利用页岩原位转化的可采油量预测模型及页岩原位转化的可采气量预测模型，获取测井解释点的单位质量岩石的可采油量和单位质量岩石的可采气量。
在以上所述的预测装置中，优选地，所述可采油资源量和可采气资源量预测模型建立模块具体用于
根据有效页岩分布区网格点的可采油气资源丰度和有效页岩分布区面积，按照以下公式分别建立可采油资源量和可采气资源量预测模型：
Figure PCTCN2021104637-appb-000015
Figure PCTCN2021104637-appb-000016
其中，NO为待评价区可采油资源量，万吨；NG为待评价区可采气资源量，亿立方米；AOR j为有效页岩分布区内第j个网格可采油资源丰度，万吨/km 2；AGR j为有效页岩分布区内第j个网格可采气资源丰度，亿立方米/km 2；A j为有效页岩分布区内第j个网格的面积，km 2；m为有效页岩分布区内的网格数，m为整数。
又一方面，本发明还提供了一种计算机设备，包括存储器、处理器及存储在存储器上并可在处理器上运行的计算机程序，其中，所述处理器执行所述计算机程序时实 现以上所述页岩原位转化可采油气资源量的预测方法的步骤。
再一方面，本发明还提供了一种计算机可读存储介质，其上存储有计算机程序，其中，所述计算机程序被处理器执行时实现以上所述页岩原位转化可采油气资源量的预测方法的步骤。
本发明提供的技术方案达到了如下有益技术效果：
首先，根据待测页岩的TOC值和Ro值，以及预先建立的页岩原位转化的可采油量预测模型和可采气量预测模型，得到待测页岩的可采油量和可采气量，克服了现有技术中必须获得页岩原始HI或原始H/C、原始TOC、未成熟页岩生成油气量和滞留油气量，才能建立可采油量和可采气量的缺陷，克服了利用经历过一定热演化页岩恢复原始HI或原始TOC精度不高的缺陷，克服了必须获得滞留油气量和生成油气量才能获得产出油气量的缺陷，实现了利用地层中页岩现今TOC和Ro求取原位转化可采油量和可采气量，因此，本发明应用该页岩原位转化的可采油量预测模型和可采气量预测模型，不仅实现了定量预测页岩原位转化可采油气量，还提高了页岩原位转化可采油气量的预测精度。
其次，根据页岩原位转化的同一开发区域内(同一开发区域是指具有相似的原位转化地质条件、相似的开发工艺的开发区域)的任一个生产井组的累积产出油量下限值和一个生产井组控制的有效加热区的岩石质量，获得页岩原位转化的单位质量岩石的可采油量下限值，并由此建立有效页岩的TOC下限值预测模型，得到有效页岩的TOC下限值，从而实现了准确得到页岩有效厚度、有效厚度层段及有效页岩分布区，克服了现有技术中无法确定有效页岩TOC下限值的缺陷，无法准确获得页岩有效厚度、有效厚度层段及有效页岩分布区的缺陷。
最后，根据待评价区的测井解释的TOC值、岩石密度值、测量间距值、Ro分析化验值(目的层井点的镜质体反射率)和有效厚度层段，以及预先建立的可采油量预测模型和可采气量预测模型，获得测井解释点的单位质量岩石的可采油量和单位质量岩石的可采气量，根据预先建立的可采油资源丰度值和可采气资源丰度值模型，得到可采油资源丰度值和可采气资源丰度值，根据被评价区内的有效页岩分布区，以及预先建立的可采油资源量和可采气资源量预测模型，获得可采油资源量和可采气资源量，克服了现有技术中采用参数平均值计算相关参数的缺陷，克服了采用参数平均值无法体现可采油气资源量与TOC之间非线性关系的实际情况，实现了有效页岩层段 内纵向不同TOC点对可采油气资源量贡献不同的计算。
综上，本发明提供的技术方案实现了页岩原位转化可采油气资源量的定量预测，提高了页岩原位转化可采油气资源量的预测精度和效率。
附图说明
图1是本发明实施例所提供的页岩原位转化可采油气资源量的预测方法的流程示意图；
图2是本发明实施例中热模拟温度与Ro关系图；
图3是本发明实施例中热模拟得到的产出油量与TOC关系图；
图4是本发明实施例中热模拟得到的产出气量与TOC关系图；
图5是本发明实施例中热模拟的最大产出气量与最大产出油量关系图；
图6是本发明实施例中单位页岩产出油量下限值为14mg/g时的TOC下限值与Ro关系图；
图7是本发明实施例中有效页岩层段内不存在夹层示意图；
图8是本发明实施例中有效页岩层段内存在夹层示意图；
图9是本发明实施例中鄂尔多斯盆地长7 3亚段页岩TOC分布图；
图10是本发明实施例中鄂尔多斯盆地长7 3亚段页岩Ro分布图；
图11是本发明实施例中鄂尔多斯盆地长7 3亚段页岩有效厚度分布图；
图12是本发明实施例中鄂尔多斯盆地长7 3亚段页岩可采油资源丰度分布图；
图13是本发明实施例中鄂尔多斯盆地长7 3亚段页岩可采气资源丰度分布图；
图14为本发明实施例所提供的页岩原位转化可采油气资源量的预测装置的结构示意图。
具体实施方式
下面将结合本发明实施例中的附图，对本发明实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例仅是本发明一部分实施例，而不是全部的实施例。基于本发明中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例，都属于本发明保护的范围。
页岩原位转化技术开发油气不同于现有技术，具有颠覆性，原位转化技术是将地层中尚未转化的有机质和滞留油，通过人工加热生成轻质油和天然气并产出，适用于 未熟-中低成熟度页岩，页岩原位转化可采油气资源量是原位转化开发的关键，控制着原位转化开发的效益。原位转化可采油气资源预测技术明显不同于目前开发的已经生成并储存于地层中的油气资源评价技术。需要用一种全新的思路和评价方法对原位转化可采油气资源量进行预测，才能满足原位转化选区评价及勘探开发的需要。
为了克服现有技术中尚无页岩原位转化可采油气资源量预测技术，提出了一种页岩原位转化可采油气资源量的预测方案。下面对本发明实施例涉及的页岩原位转化可采油气资源量的预测方案进行详细介绍。
图1是本发明实施例中提供的页岩原位转化可采油气资源量的预测方法的流程示意图，从图1中可以看出，所述方法包括以下步骤：
101：获取待测页岩的总有机碳含量和镜质体反射率；
102：建立页岩原位转化的可采油量预测模型，并根据待测页岩的总有机碳含量和镜质体反射率利用页岩原位转化的可采油量预测模型，获取待测页岩的可采油量；
103：建立页岩原位转化的可采气量预测模型，并根据待测页岩的总有机碳含量和镜质体反射率利用页岩原位转化的可采气量预测模型，获取待测页岩的可采气量；
104：根据页岩原位转化的一个生产井组的累积产出油量下限值和一个生产井组控制的有效加热区的岩石质量，获取得到页岩原位转化的单位质量岩石的可采油量下限值；
105：建立有效页岩的总有机碳含量下限值预测模型，并根据页岩原位转化的单位质量岩石的可采油量下限值及待测页岩的镜质体反射率，获取有效页岩的总有机碳含量下限值；
106：根据待评价区的测井解释的总有机碳含量和所述有效页岩的总有机碳含量下限值，获取页岩原位转化的页岩有效厚度、有效厚度层段及有效页岩分布区；
107：分别建立有效厚度层段内的可采油资源丰度值和可采气资源丰度值模型，并根据测井解释点的单位质量岩石的可采油量和单位质量岩石的可采气量分别获取被评价井有效厚度层段内的可采油资源丰度值和可采气资源丰度值；
108：分别建立可采油资源量和可采气资源量预测模型，并根据可采油资源量和可采气资源量预测模型获取可采油资源量和可采气资源量。
本发明实施例所提供的技术方案达到了如下有益技术效果：
首先，根据待测页岩的TOC值和Ro值，以及预先建立的页岩原位转化的可采 油量预测模型和可采气量预测模型，得到待测页岩的可采油量和可采气量，克服了现有技术中必须获得页岩原始HI或原始H/C、原始TOC、未成熟页岩生成油气量和滞留油气量，才能建立可采油量和可采气量的缺陷，克服了利用经历过一定热演化页岩恢复原始HI或原始TOC精度不高的缺陷，克服了必须获得滞留油气量和生成油气量才能获得产出油气量的缺陷，实现了利用地层中页岩现今TOC和Ro求取原位转化可采油量和可采气量，因此，本发明应用该页岩原位转化的可采油量预测模型和可采气量预测模型，不仅实现了定量预测页岩原位转化可采油气量，还提高了页岩原位转化可采油气量的预测精度。
其次，根据页岩原位转化的同一开发区域内的任一个生产井组的累积产出油量下限值和一个生产井组控制的有效加热区的岩石质量，获得页岩原位转化的单位质量岩石的可采油量下限值，并由此建立有效页岩的TOC下限值预测模型，得到有效页岩的TOC下限值，从而实现了准确得到页岩有效厚度、有效厚度层段及有效页岩分布区，克服了现有技术中无法确定有效页岩TOC下限值的缺陷，无法准确获得页岩有效厚度、有效厚度层段及有效页岩分布区的缺陷。
最后，根据待评价区的测井解释的TOC值、岩石密度值、测量间距值、Ro分析化验值(目的层井点的镜质体反射率)和有效厚度层段，以及预先建立的可采油量预测模型和可采气量预测模型，获得测井解释点的单位质量岩石的可采油量和单位质量岩石的可采气量，根据预先建立的可采油资源丰度值和可采气资源丰度值模型，得到可采油资源丰度值和可采气资源丰度值，根据被评价区内的有效页岩分布区，以及预先建立的可采油资源量和可采气资源量预测模型，获得可采油资源量和可采气资源量，克服了现有技术中采用参数平均值计算相关参数的缺陷，克服了采用参数平均值无法体现可采油气资源量与TOC之间非线性关系的实际情况，实现了有效页岩层段内纵向不同TOC点对可采油气资源量贡献不同的计算。
综上，本发明实施例提供的技术方案实现了页岩原位转化可采油气资源量的定量预测，提高了页岩原位转化可采油气资源量的预测精度和效率。
下面再结合图2至图13，对本发明实施例所提供的页岩原位转化可采油气资源量的预测方法涉及的各个步骤进行详细介绍。
一、建立各个模型前，对页岩样品进行热模拟实验。
采集被评价区目的层不同TOC值，Ro值小于0.5％的多组页岩样品，本实施例 中，所述多组页岩样品为采集自鄂尔多斯盆地长7段的露头页岩样品，不同TOC，Ro小于0.5％的页岩样品共9组，记为No.1-No.9，分别将每组页岩样品粉碎成40-80目，优选为60目，并充分混合均匀，再将每组混合均匀的页岩样品分成11份，每份质量大于3kg。
分别测量每组页岩样品的有机碳含量(TOC)和镜质体反射率(Ro)，所得实验数据详见下表1所示。
其中，每组页岩样品的TOC是根据国家标准GB/T 19145-2003《沉积岩中总有机碳的测定》进行测量的；Ro是根据行业标准SY/T 5124-2012《沉积岩中镜质体反射率测定方法》进行测量的。
表1被评价区目的层页岩样品特征参数
样品序号 No.1 No.2 No.3 No.4 No.5 No.6 No.7 No.8 No.9
TOC(wt％) 0.51 2.03 3.50 5.03 6.44 8.51 13.34 20.67 25.99
HI(mg/g·TOC) 388.1 423.0 494.5 487.9 498.2 498.6 503.5 541.5 531.8
Ro(％) 0.43 0.46 0.47 0.47 0.47 0.47 0.48 0.47 0.48
本实施例中的热模拟实验均采用预设压力为5MPa和不同预设温度的半开放实验体系。所述热模拟实验的具体包括：将页岩样品装入反应釜并用20MPa压力反复压实，在模拟前称取反应釜中页岩样品的质量，再将反应釜内抽真空并注入He。所述热模拟实验中预设温度点共11个，分别为250℃、300℃、320℃、335℃、350℃、360℃、390℃、440℃、500℃、540℃、580℃，该些预设温度涵盖了从油气开始生成到结束的不同阶段。对于温度为250℃的第一个预设温度点，在模拟温度为200℃前，采用的程序升温速率为20℃/d；模拟温度为200℃-250℃之间，采用的程序升温速率为5℃/d；对于第2个到第11个预设温度点，模拟温度达到目标预设温度点前一个预设温度点温度前，采用的程序升温速率为20℃/d，模拟温度处于目标预设温度点前一个预设温度点温度与目标预设温度点温度之间时，采用的程序升温速率为5℃/d；模拟温度达到预设温度后保持预设温度并恒温10小时，依次类推，完成所有预设温度点的热模拟。排烃预设压力为7MPa，热模拟过程中排出的油气量用于计算单位质量岩石的产出油气量。
针对每一页岩样品，分别开展11个预设温度的产出油气量热模拟实验，完成模拟后，根据收集到的产出油量和产出气量与对应反应釜内热模拟前页岩样品质量之 比，获得对应预设温度点的单位质量岩石的产出油量和产出气量，实验数据见表2所示。在每一个预设温度点的热模拟结束后，测量抽提后残留物的TOC和Ro，实验数据见表3所示。
其中，每组烃源岩样品的TOC是根据国家标准GB/T 19145-2003《沉积岩中总有机碳的测定》进行测量的；Ro是根据行业标准SY/T 5124-2012《沉积岩中镜质体反射率测定方法》进行测量的。
表2被评价区目的层页岩样品热模拟实验产出油量、产出气量数据表
Figure PCTCN2021104637-appb-000017
注：累计产出油量—mg/g·rock；累计产出气量—mL/g·rock。
表3被评价区目的层页岩样品热模拟实验抽提后残留物的TOC和Ro
Figure PCTCN2021104637-appb-000018
Figure PCTCN2021104637-appb-000019
注：TOC—wt％；Ro—％。
获取热模拟实验中，不同页岩样品于同一预设温度下的热模拟后的Ro平均值，建立热解模拟温度与Ro关系。页岩热模拟的产出油气量与Ro相关，为了便于对地层条件下的页岩热演化程度进行对应研究，按照如下述式(1)将模拟温度转化为对应的Ro值。
Figure PCTCN2021104637-appb-000020
式(1)中：Ro为镜质体反射率，％；T为热解模拟温度，℃；x 1和x 2为经验系数，可以分别为：0.13797、0.005667。
本实施例中，不同页岩样品于同一预设温度下的热模拟后的Ro平均值与热解模拟温度之间的关系曲线图如图2所示。
二、根据上述热模拟实验过程得到的数据，建立各个模型。
1、根据以上热模拟实验获得的产出油量、页岩样品的TOC值和Ro值数据，预先建立对应TOC、Ro条件下的不同页岩产出油量评价模型(页岩原位转化的可采油量预测模型)。
页岩产出油量与页岩Ro、TOC相关，根据热模拟实验结果，建立产出油量与TOC关系模型，提取模型中的经验参数与Ro建立模型，建立了如下式(2)及图3所示的产出油量评价模型。
Figure PCTCN2021104637-appb-000021
其中，Qpo为单位质量页岩的剩余产出油量(待求)，mg/g·rock；Ro为镜质体反射率，％；TOC为有机碳含量，wt％；a 1、a 2、a 3、a 4、a 5、a 6为经验参数，a 1、a 6分别为0.99892、0.01538；当Ro≤0.76％时，a 2、a 3分别为0.4265、0.7516，当0.76％<Ro≤1.0％时，a 2、a 3分别为-0.4593、1.41，当Ro>0.98％时，a 2、a 3分别为-4.164、5.3161；当Ro≤0.77％时，a 4、a 5分别为0.068、1.1297，0.775％<Ro≤1.06％时，a 4、a 5分别为-2.6881、3.2629，Ro>1.06％时，a 4、a 5分别为-3.5488、4.1449。
2、根据以上热模拟实验获得的产出气量、页岩样品的TOC值和Ro值数据，预先建立对应TOC、Ro条件下的不同页岩产出气量评价模型(页岩原位转化的可采气量预测模型)。
页岩产出气量与页岩Ro、TOC相关，根据热模拟实验结果，建立产出气量与TOC关系模型，提取模型中的经验参数与Ro建立模型，建立了如下式(3)及图4所示的产出气量评价模型。
Figure PCTCN2021104637-appb-000022
其中，Qpg为单位质量页岩的剩余产出气量，m 3/t·rock；Ro为镜质体反射率，％；TOC为有机碳含量，wt％；b 1、b 2、b 3、b 4、b 5、b 6、b 7、b 8、b 9、b 10、b 11、b 12、b 13、b 14、b 15为经验参数，分别为1.0062、0.9478、0.5744、-0.0997、-1.1745、3.4118、2.1756、1.5235、-2.3651、-0.2334、2.9012、-2.9174、-0.0967、0.5035、-0.4776。
具体实施时，本发明实例提供的方案克服了现有技术中只有提供模拟实验或只有提供页岩原始TOC和原始HI或原始H/C，只有获得生成油气量和滞留油气量，才能获得产出油气量的缺陷，所建立的TOC、Ro与产出油气量关系(页岩原位转化产出油量预测模型和页岩原位转化产出气量预测模型)克服了现有技术无法评价(预测)不同TOC和Ro页岩产出油气量的缺陷，可以预测不同页岩TOC及Ro值对应的产出油量、产出气量。
由于模拟原位转化条件下页岩产出油气量需要时间较长，对于没有热模拟实验数 据的地区，可采用式(3)-(4)获得被评价区的页岩原位转化产出油气量数据，用于开展可采油气资源和“甜点区”评价优选。
三、基于以上所获得的页岩原位转化产出油量预测模型和页岩原位转化产出气量预测模型，建立可采油量资源量和可采气量资源量预测模型。
1、建立页岩原位转化的单位质量岩石的可采油量下限值预测模型。
页岩原位转化开发过程中，要想经济规模开发，单位质量页岩的可采油量和可采气量必须大于一定的下限值，由于最大可采油量和最大可采气量存在非常好的线性关系，因此，只要确定了可采油量下限值即可，图5是实验热模拟页岩样品的最大可采油量和最大可采气量关系图。
根据页岩原位转化规模经济开发时，页岩原位转化的单位质量岩石的可采油量下限值是根据页岩原位转化的同一开发区域内的任一个生产井组的累积产出油量下限值和该生产井组控制的有效加热区的岩石质量按照如下式(4)获得的。
Figure PCTCN2021104637-appb-000023
其中，Q po_limt为页岩原位转化的单位质量岩石可采油量下限值，mg/g·rock；Q oil_limt为一个生产井组的累计产出油量下限值，mg；Wt rock为该生产井组控制的有效加热区的岩石质量，g。
如采用水平井开发，按一个生产井组包括10口加热井和1口生产井，加热井采用15米井距，水平井长度为1200米，有效加热区的岩石质量为708×10 4吨。一个生产井组产出油量下限值为10×10 4吨，由以上式(4)计算得到的单位质量岩石可采油量下限值为14mg/g·rock。
2、建立页岩原位转化的TOC下限值预测模型。
在确定了单位质量岩石可采油量下限值基础上，根据式(2)推导获得单位质量岩石可采油量下限值对应的页岩原位转化的TOC下限值，预先建立的有效页岩原位转化的TOC下限值预测模型见如下式(5)所示。
Figure PCTCN2021104637-appb-000024
其中，TOC limt为有效页岩的总有机碳含量下限值，wt％；Q po_limt为页岩原位转 化的单位质量岩石可采油量下限值，mg/g·rock；Ro为待测页岩的镜质体反射率，％；c 1、c 2、c 3、c 4、c 5、c 6为经验参数，c 1、c 4分别为1.0011、0.0154；当Ro≤0.77％时，c 2、c 3分别为0.068、1.1297，0.775％<Ro≤1.06％时，c 2、c 3分别为-2.6881、3.2629，Ro>1.06％时，c 2、c 3分别为-3.5488、4.1449；当Ro≤0.76％时，c 5、c 6分别为0.4265、0.7516，当0.76％<Ro≤1.0％时，c 5、c 6分别为-0.4593、1.41，当Ro>0.98％时，c 5、c 6分别为-4.164、5.3161。
图6是当单位质量岩石可采油量下限值为14mg/g·rock时，利用式(5)计算得到的有效页岩的总有机碳含量下限值随Ro的变化图，根据不同Ro值可获得对应的有效页岩的总有机碳含量下限值；当Ro约为0.8％时，对应的有效页岩的总有机碳含量下限值最小约为6％。
3、确定页岩原位转化的页岩有效厚度、有效厚度层段及有效页岩分布区。
利用得到的有效页岩的总有机碳含量下限值和测井解释的TOC、镜质体反射率Ro，根据以下原则确定页岩原位转化的页岩有效厚度、有效厚度层段及有效页岩分布区。
当页岩的测井解释的总有机碳含量大于有效页岩的总有机碳含量下限值的连续厚度大于设定值1-15米时，采用设定值5米作为视页岩有效厚度，视页岩有效厚度对应的深度段为视有效厚度层段；相邻两个视有效厚度层段之间，当页岩的测井解释的总有机碳含量小于有效页岩的总有机碳含量下限值的连续厚度小于设定值0.5-5米时，将所述设定值确定为2米，并将该层段计算到视页岩有效厚度中；当页岩的测井解释的总有机碳含量小于有效页岩的总有机碳含量下限值的连续厚度大于设定值0.5-5米时，将所述设定值确定为2米，且该层段不计算到视有效页岩厚度中；
当视页岩有效厚度大于设定值3-15米时，采用设定值5米作为视页岩有效厚度，所述视页岩有效厚度即为页岩有效厚度，页岩有效厚度顶底对应的层段为有效厚度层段；
当视页岩有效厚度小于等于设定值3-15米时，采用设定值5米作为视页岩有效厚度，但视页岩有效厚度不能作为页岩有效厚度，进而不能作为独立开发层段，该层段不计算可采资源量；当两个或多个有效厚度层段之间纵向距离超过预设厚度值0.5-5米(优选为3米)时，每个有效厚度层段将分别作为单独的页岩有效厚度段处理，即作为独立开发层系处理；
根据获得的被评价区井点的页岩有效厚度，采用三点法、五点法、有限元法、克里金法、线性插值法、非线性插值法等非等边距内插方法获得被评价区的页岩有效厚度分布，非等边距内插方法网格间距采用预设值0.1-10km(例如为2km)，被评价区内页岩有效厚度大于有效厚度预设值3-15米时，采用5米作为页岩有效厚度分布区边界，页岩有效厚度大于5米的区域为有效页岩分布区。
图7是有效页岩层段内不存在夹层情况图，图8是有效页岩层段内存在夹层情况图。
4、建立页岩原位转化的可采油气资源量预测模型。
根据测井解释的TOC，获取有效页岩层段内测井解释点的TOC值、岩石密度值、测量间距值，根据分析化验得到的目的层井点的Ro值，利用预先建立的可采油量预测模型和可采气量预测模型，获得测井解释点的单位质量岩石的可采油量和单位质量岩石的可采气量。
分别根据如下式(6)及式(7)所示的模型获得被评价井有效页岩层段内的可采油资源丰度值和可采气资源丰度值。
Figure PCTCN2021104637-appb-000025
Figure PCTCN2021104637-appb-000026
其中，AOR为被评价区的可采油资源丰度，万吨/km 2；AGR为被评价区的可采气资源丰度，亿立方米/km 2；Q po_i为有效层段内第i测井点的单位质量岩石可采油量，mg/g·rock；Q pg_i为有效层段内第i测井点的单位质量岩石可采气量，m 3/t·rock；ρ i为有效层段内第i测井点的岩石密度值，g/cm 3；L int er为被评价井的测井间距，m；n为有效层段内的测井点总数，n为整数。
根据被评价区内所有井点的可采油资源丰度值、可采气资源丰度值，可采用三点法、五点法、有限元法、克里金法、线性插值法、非线性插值法等非等边距内插方法，获得被评价区内的可采油资源丰度和可采气资源丰度平面分布，内插网格间距采用预设值0.1-10km，例如可采用2km。
根据被评价区内的有效页岩分布区内部，分别利用式(8)及式(9)所示的模型获得被评价区有效页岩分布区的可采油资源量和可采气资源量。
Figure PCTCN2021104637-appb-000027
Figure PCTCN2021104637-appb-000028
其中，NO为被评价区可采油资源量，万吨；NG为被评价区可采气资源量，亿立方米；AOR j为有效页岩分布区内第j个网格可采油资源丰度，万吨/km 2；AGR j为有效页岩分布区内第j个网格可采气资源丰度，亿立方米/km 2；A j为有效页岩分布区内第j个网格的面积，km 2；m为有效页岩分布区内的网格数，整数。
图9是针对鄂尔多斯盆地长7 3亚段页岩，利用测井解释的TOC得到的TOC大于TOC limt的TOC分布图，图9从TOC角度表征可进行原位转化开采的分布区，TOC越高原位转化潜力越大。
图10是针对鄂尔多斯盆地长7 3亚段页岩，利用岩心分析得到的Ro分布图，从图9中可以看出适合原位转化开采的页岩成熟度的情况以及页岩原位转化的潜力，其中Ro越小，原位转化潜力越大。
图11是针对鄂尔多斯盆地长7 3亚段页岩，根据本发明实施例中提供的方法得到的页岩有效厚度分布图，其中，页岩有效厚度越大，原位转化潜力越大。
图12是针对鄂尔多斯盆地长7 3亚段页岩，利用本发明实施例提供的方法得到的页岩有效厚度分布范围内的可采油资源丰度分布图，其中可采油资源丰度越大，单位面积的页岩原位转化可采油资源越大，越有利于原位转化开发。
图13是针对鄂尔多斯盆地长7 3亚段页岩，利用本发明实施例提供的方法得到的可采气资源丰度分布图，其中，可采气资源丰度越大，单位面积的页岩原位转化可采气资源越大，越有利于原位转化开发。
利用本发明实施例所提供的方法得到的鄂尔多斯盆地长7 3段页岩原位转化可采油资源量为452亿吨，可采气资源量为37万亿立方米。
具体实施时，本发明实例提供的技术方案实现了不同TOC及Ro页岩原位转化可采油资源量和可采气资源量的定量评价。
基于同一发明构思，本发明实施例还提供了一种页岩原位转化可采油气资源量的预测装置，由于该装置解决问题的原理与页岩原位转化可采油气资源量的预测方法相似，因此该装置的实施可以参见方法的实施，重复之处不再赘述。图14为本发明实施例所提供的页岩原位转化可采油气资源量的预测装置的结构示意图。如图14所示， 所述页岩原位转化可采油气资源量的预测装置包括：
数据获取模块1，用于获取待评价区待测页岩的总有机碳含量和镜质体反射率；
页岩原位转化的可采油量预测模型建立模块2，用于建立页岩原位转化的可采油量预测模型，并根据待测页岩的总有机碳含量和镜质体反射率利用页岩原位转化的可采油量预测模型，获取待测页岩的可采油量；
页岩原位转化的可采气量预测模型建立模块3，用于建立页岩原位转化的可采气量预测模型，并根据待测页岩的总有机碳含量和镜质体反射率利用页岩原位转化的可采气量预测模型，获取待测页岩的可采气量；
有效页岩的总有机碳含量下限值预测模型建立模块4，用于建立有效页岩的总有机碳含量下限值预测模型，并根据页岩原位转化的单位质量岩石的可采油量下限值及待测页岩的镜质体反射率，获取有效页岩的总有机碳含量下限值；
页岩原位转化的页岩有效厚度、有效厚度层段及有效页岩分布区确定模块5，用于根据待评价区的测井解释的总有机碳含量和所述有效页岩的总有机碳含量下限值，确定页岩原位转化的页岩有效厚度、有效厚度层段及有效页岩分布区；
有效厚度层段内的可采油资源丰度值和可采气资源丰度值模型建立模块6，用于分别建立有效厚度层段内的可采油资源丰度值和可采气资源丰度值模型，并根据测井解释点的单位质量岩石的可采油量和单位质量岩石的可采气量分别获取被评价井有效厚度层段内的可采油资源丰度值和可采气资源丰度值；
可采油资源量和可采气资源量预测模型建立模块7，用于分别建立可采油资源量和可采气资源量预测模型，并根据可采油资源量和可采气资源量预测模型获取可采油资源量和可采气资源量。
在一实施例中，所述页岩原位转化的可采油量预测模型建立模块具体用于根据对多个不同页岩样品进行热模拟实验获得的产出油量数据，以及页岩样品的总有机碳含量和镜质体反射率，建立产出油量与总有机碳含量之间的关系模型，再提取模型中的经验参数与镜质体反射率建立模型，从而建立所述页岩原位转化的可采油量预测模型。
在一实施例中，所述页岩原位转化的可采油量预测模型建立模块进一步用于按照以下公式建立所述页岩原位转化的可采油量预测模型：
Figure PCTCN2021104637-appb-000029
其中，Q po为待测页岩的可采油量，mg/g·rock；Ro为待测页岩的镜质体反射率，％；TOC为待测页岩的总有机碳含量，wt％；a 1、a 2、a 3、a 4、a 5、a 6为经验参数。
在一实施例中，所述页岩原位转化的可采气量预测模型建立模块具体用于根据对多个不同页岩样品进行热模拟实验获得的产出气量数据，以及页岩样品的总有机碳含量和镜质体反射率，建立产出气量与总有机碳含量之间的关系模型，再提取模型中的经验参数与镜质体反射率建立模型，从而建立所述页岩原位转化的可采气量预测模型。
在一实施例中，所述页岩原位转化的可采气量预测模型建立模块进一步用于按照以下公式建立所述页岩原位转化的可采气量预测模型：
Figure PCTCN2021104637-appb-000030
其中，Q pg为待测页岩的可采气量，m 3/t·rock；Ro为待测页岩的镜质体反射率，％；TOC为待测页岩的总有机碳含量，wt％；b 1、b 2、b 3、b 4、b 5、b 6、b 7、b 8、b 9、b 10、b 11、b 12、b 13、b 14、b 15为经验参数；w 1为0.5％-1.0％，w 2为1.0％-1.4％。
在一实施例中，所述有效页岩的总有机碳含量下限值预测模型建立模块包括页岩原位转化的单位质量岩石的可采油量下限值获取单元，用于根据页岩原位转化的同一开发区域内的任一个生产井组的累积产出油量下限值和该生产井组控制的有效加热区的岩石质量按照以下公式获取得到页岩原位转化的单位质量岩石的可采油量下限值：
Figure PCTCN2021104637-appb-000031
其中，Q po_limt为页岩原位转化的单位质量岩石可采油量下限值，mg/g·rock；Q oil_limt为页岩原位转化的一个生产井组的累计产出油量下限值，mg；Wt rock为页岩原位转化的该生产井组控制的有效加热区的岩石质量，g。
在一实施例中，有效页岩的总有机碳含量下限值预测模型建立模块具体用于根据页岩原位转化的可采油量预测模型及页岩原位转化的单位质量岩石的可采油量下限值，按照以下公式建立所述有效页岩的总有机碳含量下限值预测模型：
Figure PCTCN2021104637-appb-000032
其中，TOC limt为有效页岩的总有机碳含量下限值，wt％；Q po_limt为页岩原位转化的单位质量岩石的可采油量下限值，mg/g·rock；Ro为待测页岩的镜质体反射率，％；c 1、c 2、c 3、c 4、c 5、c 6为经验参数。
在一实施例中，所述页岩原位转化的页岩有效厚度、有效厚度层段及有效页岩分布区确定模块具体用于根据待评价区的测井解释的总有机碳含量和所述有效页岩的总有机碳含量下限值，根据以下原则确定页岩原位转化的页岩有效厚度、有效厚度层段及有效页岩分布区：
当页岩的测井解释的总有机碳含量大于有效页岩的总有机碳含量下限值的连续厚度大于设定值1-15米时，采用设定值5米作为视页岩有效厚度，视页岩有效厚度对应的深度段为视有效厚度层段；相邻两个视有效厚度层段之间，当页岩的测井解释的总有机碳含量小于有效页岩的总有机碳含量下限值的连续厚度小于设定值0.5-5米时，将所述设定值确定为2米，并将该层段计算到视页岩有效厚度中；当页岩的测井解释的总有机碳含量小于有效页岩的总有机碳含量下限值的连续厚度大于设定值0.5-5米时，将所述设定值确定为2米，且该层段不计算到视有效页岩厚度中；
当视页岩有效厚度大于设定值3-15米时，采用设定值5米作为视页岩有效厚度，所述视页岩有效厚度即为页岩有效厚度，页岩有效厚度顶底对应的层段为有效厚度层段；
当视页岩有效厚度小于等于设定值3-15米时，采用设定值5米作为视页岩有效厚度，但视页岩有效厚度不能作为页岩有效厚度，进而不能作为独立开发层段，该层段不计算可采资源量；当两个或多个有效厚度层段之间纵向距离超过预设厚度值0.5-5米时，每个有效厚度层段将分别作为单独的页岩有效厚度段处理，即作为独立开发层系处理；
根据获得的被评价区井点的页岩有效厚度，采用非等边距内插方法获得被评价区的页岩有效厚度分布，非等边距内插方法网格间距采用预设值0.1-10km，被评价区内页岩有效厚度大于有效厚度预设值3-15米时，采用5米作为页岩有效厚度分布区边界，页岩有效厚度大于5米的区域为有效页岩分布区。
在一实施例中，所述有效厚度层段内的可采油资源丰度值和可采气资源丰度值模 型建立模块具体用于根据单位质量岩石可采油气量、测井间距、岩石密度和有效厚度层段，按照单位面积的有效厚度层段内岩石可采油量、可采气量，分别建立有效页岩层段内的可采油资源丰度值和可采气资源丰度值模型。
在一实施例中，所述有效厚度层段内的可采油资源丰度值和可采气资源丰度值模型建立模块进一步用于按照以下公式分别建立有效页岩层段内的可采油资源丰度值和可采气资源丰度值模型：
Figure PCTCN2021104637-appb-000033
Figure PCTCN2021104637-appb-000034
其中，AOR为待评价区的有效页岩层段内的可采油资源丰度，万吨/km 2；AGR为待评价区的有效页岩层段内的可采气资源丰度，亿立方米/km 2；Q po_i为待评价区的有效厚度层段内第i测井点的单位质量岩石可采油量，mg/g·rock；Q pg_i为待评价区的有效厚度层段内第i测井点的单位质量岩石可采气量，m 3/t·rock；ρ i为待评价区的有效厚度层段内第i测井点的岩石密度值，g/cm 3；L int er为被评价井的测井间距，m；n为有效厚度层段内的测井点总数，n为整数。
在一实施例中，所述有效厚度层段内的可采油资源丰度值和可采气资源丰度值模型建立模块包括测井解释点的单位质量岩石的可采油量和单位质量岩石的可采气量获取单元，用于：
根据待评价区的测井解释的总有机碳含量，获取有效页岩层段内测井解释点的总有机碳含量、岩石密度值、测量间距值，再根据有效页岩层段内测井解释点的总有机碳含量、岩石密度值、测量间距值及目的层井点的镜质体反射率，利用页岩原位转化的可采油量预测模型及页岩原位转化的可采气量预测模型，获取测井解释点的单位质量岩石的可采油量和单位质量岩石的可采气量。
在一实施例中，所述可采油资源量和可采气资源量预测模型建立模块具体用于
根据有效页岩分布区网格点的可采油气资源丰度和有效页岩分布区面积，按照以下公式分别建立可采油资源量和可采气资源量预测模型：
Figure PCTCN2021104637-appb-000035
Figure PCTCN2021104637-appb-000036
其中，NO为待评价区可采油资源量，万吨；NG为待评价区可采气资源量，亿立方米；AOR j为有效页岩分布区内第j个网格可采油资源丰度，万吨/km 2；AGR j为有效页岩分布区内第j个网格可采气资源丰度，亿立方米/km 2；A j为有效页岩分布区内第j个网格的面积，km 2；m为有效页岩分布区内的网格数，m为整数。
以上所述，仅为本发明的具体实施例，不能以其限定发明实施的范围，所以其等同组件的置换，或依本发明专利保护范围所作的等同变化与修饰，都应仍属于本专利涵盖的范畴。另外，本发明中的技术特征与技术特征之间、技术特征与技术发明之间、技术发明与技术发明之间均可以自由组合使用。

Claims (26)

  1. 一种页岩原位转化可采油气资源量的预测方法，其中，所述页岩原位转化可采油气资源量的预测方法包括：
    获取待评价区待测页岩的总有机碳含量和镜质体反射率；
    建立页岩原位转化的可采油量预测模型，并根据待测页岩的总有机碳含量和镜质体反射率利用页岩原位转化的可采油量预测模型，获取待测页岩的可采油量；
    建立页岩原位转化的可采气量预测模型，并根据待测页岩的总有机碳含量和镜质体反射率利用页岩原位转化的可采气量预测模型，获取待测页岩的可采气量；
    建立有效页岩的总有机碳含量下限值预测模型，并根据页岩原位转化的单位质量岩石的可采油量下限值及待测页岩的镜质体反射率，获取有效页岩的总有机碳含量下限值；
    根据待评价区的测井解释的总有机碳含量和所述有效页岩的总有机碳含量下限值，确定页岩原位转化的页岩有效厚度、有效厚度层段及有效页岩分布区；
    分别建立有效厚度层段内的可采油资源丰度值和可采气资源丰度值模型，并根据测井解释点的单位质量岩石的可采油量和单位质量岩石的可采气量分别获取被评价井有效厚度层段内的可采油资源丰度值和可采气资源丰度值；
    分别建立可采油资源量和可采气资源量预测模型，并根据可采油资源量和可采气资源量预测模型获取可采油资源量和可采气资源量。
  2. 根据权利要求1所述的预测方法，其中，建立页岩原位转化的可采油量预测模型，包括：
    根据对多个不同页岩样品进行热模拟实验获得的产出油量数据，以及页岩样品的总有机碳含量和镜质体反射率，建立产出油量与总有机碳含量之间的关系模型，再提取模型中的经验参数与镜质体反射率建立模型，从而建立所述页岩原位转化的可采油量预测模型。
  3. 根据权利要求2所述的预测方法，其中，按照以下公式建立所述页岩原位转化的可采油量预测模型：
    Figure PCTCN2021104637-appb-100001
    其中，Q po为待测页岩的可采油量，mg/g·rock；Ro为待测页岩的镜质体反射率，％；TOC为待测页岩的总有机碳含量，wt％；a 1、a 2、a 3、a 4、a 5、a 6为经验参数。
  4. 根据权利要求1所述的预测方法，其中，建立页岩原位转化的可采气量预测模型，包括：
    根据对多个不同页岩样品进行热模拟实验获得的产出气量数据，以及页岩样品的总有机碳含量和镜质体反射率，建立产出气量与总有机碳含量之间的关系模型，再提取模型中的经验参数与镜质体反射率建立模型，从而建立所述页岩原位转化的可采气量预测模型。
  5. 根据权利要求4所述的预测方法，其中，按照以下公式建立所述页岩原位转化的可采气量预测模型：
    Figure PCTCN2021104637-appb-100002
    其中，Q pg为待测页岩的可采气量，m 3/t·rock；Ro为待测页岩的镜质体反射率，％；TOC为待测页岩的总有机碳含量，wt％；b 1、b 2、b 3、b 4、b 5、b 6、b 7、b 8、b 9、b 10、b 11、b 12、b 13、b 14、b 15为经验参数；w 1为0.5％-1.0％，w 2为1.0％-1.4％。
  6. 根据权利要求1所述的预测方法，其中，所述页岩原位转化的单位质量岩石的可采油量下限值是根据页岩原位转化的同一开发区域内的任一个生产井组的累积产出油量下限值和该生产井组控制的有效加热区的岩石质量按照以下公式获取得到的：
    Figure PCTCN2021104637-appb-100003
    其中，Q po_lim t为页岩原位转化的单位质量岩石可采油量下限值，mg/g·rock；Q oil_lim t为页岩原位转化的一个生产井组的累计产出油量下限值，mg；Wt rock为页岩原位转化的该生产井组控制的有效加热区的岩石质量，g。
  7. 根据权利要求1或6所述的预测方法，其中，建立有效页岩的总有机碳含量下限值预测模型，包括：根据页岩原位转化的可采油量预测模型及页岩原位转化的单位质量岩石的可采油量下限值，按照以下公式建立所述有效页岩的总有机碳含量下限值预测模型：
    Figure PCTCN2021104637-appb-100004
    其中，TOC lim t为有效页岩的总有机碳含量下限值，wt％；Q po_lim t为页岩原位转化的单位质量岩石的可采油量下限值，mg/g·rock；Ro为待测页岩的镜质体反射率，％；c 1、c 2、c 3、c 4、c 5、c 6为经验参数。
  8. 根据权利要求1或7所述的预测方法，其中，根据待评价区的测井解释的总有机碳含量和所述有效页岩的总有机碳含量下限值，根据以下原则确定页岩原位转化的页岩有效厚度、有效厚度层段及有效页岩分布区：
    当页岩的测井解释的总有机碳含量大于有效页岩的总有机碳含量下限值的连续厚度大于设定值1-15米时，采用设定值5米作为视页岩有效厚度，视页岩有效厚度对应的深度段为视有效厚度层段；相邻两个视有效厚度层段之间，当页岩的测井解释的总有机碳含量小于有效页岩的总有机碳含量下限值的连续厚度小于设定值0.5-5米时，将所述设定值确定为2米，并将该层段计算到视页岩有效厚度中；当页岩的测井解释的总有机碳含量小于有效页岩的总有机碳含量下限值的连续厚度大于设定值0.5-5米时，将所述设定值确定为2米，且该层段不计算到视有效页岩厚度中；
    当视页岩有效厚度大于设定值3-15米时，采用设定值5米作为视页岩有效厚度，所述视页岩有效厚度即为页岩有效厚度，页岩有效厚度顶底对应的层段为有效厚度层段；
    当视页岩有效厚度小于等于设定值3-15米时，采用设定值5米作为视页岩有效厚度，但视页岩有效厚度不能作为页岩有效厚度，进而不能作为独立开发层段，该层段不计算可采资源量；当两个或多个有效厚度层段之间纵向距离超过预设厚度值0.5-5米时，每个有效厚度层段将分别作为单独的页岩有效厚度段处理，即作为独立开发层系处理；
    根据获得的被评价区井点的页岩有效厚度，采用非等边距内插方法获得被评价区的页岩有效厚度分布，非等边距内插方法网格间距采用预设值0.1-10km，被评价区内页岩有效厚度大于有效厚度预设值3-15米时，采用5米作为页岩有效厚度分布区边界，页岩有效厚度大于5米的区域为有效页岩分布区。
  9. 根据权利要求1所述的预测方法，其中，分别建立有效页岩层段内的可采油资源丰度值和可采气资源丰度值模型，包括：
    根据单位质量岩石可采油气量、测井间距、岩石密度和有效厚度层段，按照单位面积的有效厚度层段内岩石可采油量、可采气量，分别建立有效页岩层段内的可采油资源丰度值和可采气资源丰度值模型。
  10. 根据权利要求9所述的预测方法，其中，按照以下公式分别建立有效页岩层段内的可采油资源丰度值和可采气资源丰度值模型：
    Figure PCTCN2021104637-appb-100005
    Figure PCTCN2021104637-appb-100006
    其中，AOR为待评价区的有效页岩层段内的可采油资源丰度，万吨/km 2；AGR为待评价区的有效页岩层段内的可采气资源丰度，亿立方米/km 2；Q po_i为待评价区的有效厚度层段内第i测井点的单位质量岩石可采油量，mg/g·rock；Q pg_i为待评价区的有效厚度层段内第i测井点的单位质量岩石可采气量，m 3/t·rock；ρ i为待评价区的有效厚度层段内第i测井点的岩石密度值，g/cm 3；L int er为被评价井的测井间距，m；n为有效厚度层段内的测井点总数，n为整数。
  11. 根据权利要求1，9-10任一项所述的预测方法，其中，测井解释点的单位质量岩石的可采油量和单位质量岩石的可采气量按照以下步骤获取：
    根据待评价区的测井解释的总有机碳含量，获取有效页岩层段内测井解释点的总有机碳含量、岩石密度值、测量间距值，再根据有效页岩层段内测井解释点的总有机碳含量、岩石密度值、测量间距值及目的层井点的镜质体反射率，利用页岩原位转化的可采油量预测模型及页岩原位转化的可采气量预测模型，获取测井解释点的单位质量岩石的可采油量和单位质量岩石的可采气量。
  12. 根据权利要求1所述的预测方法，其中，根据有效页岩分布区网格点的可采油气资源丰度和有效页岩分布区面积，按照以下公式分别建立可采油资源量和可采气资源量预测模型：
    Figure PCTCN2021104637-appb-100007
    Figure PCTCN2021104637-appb-100008
    其中，NO为待评价区可采油资源量，万吨；NG为待评价区可采气资源量，亿立 方米；AOR j为有效页岩分布区内第j个网格可采油资源丰度，万吨/km 2；AGR j为有效页岩分布区内第j个网格可采气资源丰度，亿立方米/km 2；A j为有效页岩分布区内第j个网格的面积，km 2；m为有效页岩分布区内的网格数，m为整数。
  13. 一种页岩原位转化可采油气资源量的预测装置，其中，所述页岩原位转化可采油气资源量的预测装置包括：
    数据获取模块，用于获取待评价区待测页岩的总有机碳含量和镜质体反射率；
    页岩原位转化的可采油量预测模型建立模块，用于建立页岩原位转化的可采油量预测模型，并根据待测页岩的总有机碳含量和镜质体反射率利用页岩原位转化的可采油量预测模型，获取待测页岩的可采油量；
    页岩原位转化的可采气量预测模型建立模块，用于建立页岩原位转化的可采气量预测模型，并根据待测页岩的总有机碳含量和镜质体反射率利用页岩原位转化的可采气量预测模型，获取待测页岩的可采气量；
    有效页岩的总有机碳含量下限值预测模型建立模块，用于建立有效页岩的总有机碳含量下限值预测模型，并根据页岩原位转化的单位质量岩石的可采油量下限值及待测页岩的镜质体反射率，获取有效页岩的总有机碳含量下限值；
    页岩原位转化的页岩有效厚度、有效厚度层段及有效页岩分布区确定模块，用于根据待评价区的测井解释的总有机碳含量和所述有效页岩的总有机碳含量下限值，确定页岩原位转化的页岩有效厚度、有效厚度层段及有效页岩分布区；
    有效厚度层段内的可采油资源丰度值和可采气资源丰度值模型建立模块，用于分别建立有效厚度层段内的可采油资源丰度值和可采气资源丰度值模型，并根据测井解释点的单位质量岩石的可采油量和单位质量岩石的可采气量分别获取被评价井有效厚度层段内的可采油资源丰度值和可采气资源丰度值；
    可采油资源量和可采气资源量预测模型建立模块，用于分别建立可采油资源量和可采气资源量预测模型，并根据可采油资源量和可采气资源量预测模型获取可采油资源量和可采气资源量。
  14. 根据权利要求13所述的预测装置，其中，所述页岩原位转化的可采油量预测模型建立模块具体用于根据对多个不同页岩样品进行热模拟实验获得的产出油量数据，以及页岩样品的总有机碳含量和镜质体反射率，建立产出油量与总有机碳含量之间的关系模型，再提取模型中的经验参数与镜质体反射率建立模型，从而建立所述 页岩原位转化的可采油量预测模型。
  15. 根据权利要求14所述的预测装置，其中，所述页岩原位转化的可采油量预测模型建立模块进一步用于按照以下公式建立所述页岩原位转化的可采油量预测模型：
    Figure PCTCN2021104637-appb-100009
    其中，Q po为待测页岩的可采油量，mg/g·rock；Ro为待测页岩的镜质体反射率，％；TOC为待测页岩的总有机碳含量，wt％；a 1、a 2、a 3、a 4、a 5、a 6为经验参数。
  16. 根据权利要求13所述的预测装置，其中，所述页岩原位转化的可采气量预测模型建立模块具体用于根据对多个不同页岩样品进行热模拟实验获得的产出气量数据，以及页岩样品的总有机碳含量和镜质体反射率，建立产出气量与总有机碳含量之间的关系模型，再提取模型中的经验参数与镜质体反射率建立模型，从而建立所述页岩原位转化的可采气量预测模型。
  17. 根据权利要求16所述的预测装置，其中，所述页岩原位转化的可采气量预测模型建立模块进一步用于按照以下公式建立所述页岩原位转化的可采气量预测模型：
    Figure PCTCN2021104637-appb-100010
    其中，Q pg为待测页岩的可采气量，m 3/t·rock；Ro为待测页岩的镜质体反射率，％；TOC为待测页岩的总有机碳含量，wt％；b 1、b 2、b 3、b 4、b 5、b 6、b 7、b 8、b 9、b 10、b 11、b 12、b 13、b 14、b 15为经验参数；w 1为0.5％-1.0％，w 2为1.0％-1.4％。
  18. 根据权利要求13所述的预测装置，其中，所述有效页岩的总有机碳含量下限值预测模型建立模块包括页岩原位转化的单位质量岩石的可采油量下限值获取单元，用于根据页岩原位转化的同一开发区域内的任一个生产井组的累积产出油量下限值和该生产井组控制的有效加热区的岩石质量按照以下公式获取得到页岩原位转化的单位质量岩石的可采油量下限值：
    Figure PCTCN2021104637-appb-100011
    其中，Q po_lim t为页岩原位转化的单位质量岩石可采油量下限值，mg/g·rock；Q oil_lim t为页岩原位转化的一个生产井组的累计产出油量下限值，mg；Wt rock为页岩原位转化的该生产井组控制的有效加热区的岩石质量，g。
  19. 根据权利要求13或18所述的预测装置，其中，有效页岩的总有机碳含量下限值预测模型建立模块具体用于根据页岩原位转化的可采油量预测模型及页岩原位转化的单位质量岩石的可采油量下限值，按照以下公式建立所述有效页岩的总有机碳含量下限值预测模型：
    Figure PCTCN2021104637-appb-100012
    其中，TOC lim t为有效页岩的总有机碳含量下限值，wt％；Q po_lim t为页岩原位转化的单位质量岩石的可采油量下限值，mg/g·rock；Ro为待测页岩的镜质体反射率，％；c 1、c 2、c 3、c 4、c 5、c 6为经验参数。
  20. 根据权利要求13所述的预测装置，其中，所述页岩原位转化的页岩有效厚度、有效厚度层段及有效页岩分布区确定模块具体用于根据待评价区的测井解释的总有机碳含量和所述有效页岩的总有机碳含量下限值，根据以下原则确定页岩原位转化的页岩有效厚度、有效厚度层段及有效页岩分布区：
    当页岩的测井解释的总有机碳含量大于有效页岩的总有机碳含量下限值的连续厚度大于设定值1-15米时，采用设定值5米作为视页岩有效厚度，视页岩有效厚度对应的深度段为视有效厚度层段；相邻两个视有效厚度层段之间，当页岩的测井解释的总有机碳含量小于有效页岩的总有机碳含量下限值的连续厚度小于设定值0.5-5米时，将所述设定值确定为2米，并将该层段计算到视页岩有效厚度中；当页岩的测井解释的总有机碳含量小于有效页岩的总有机碳含量下限值的连续厚度大于设定值0.5-5米时，将所述设定值确定为2米，且该层段不计算到视有效页岩厚度中；
    当视页岩有效厚度大于设定值3-15米时，采用设定值5米作为视页岩有效厚度，所述视页岩有效厚度即为页岩有效厚度，页岩有效厚度顶底对应的层段为有效厚度层段；
    当视页岩有效厚度小于等于设定值3-15米时，采用设定值5米作为视页岩有效厚度，但视页岩有效厚度不能作为页岩有效厚度，进而不能作为独立开发层段，该层段不计算可采资源量；当两个或多个有效厚度层段之间纵向距离超过预设厚度值 0.5-5米时，每个有效厚度层段将分别作为单独的页岩有效厚度段处理，即作为独立开发层系处理；
    根据获得的被评价区井点的页岩有效厚度，采用非等边距内插方法获得被评价区的页岩有效厚度分布，非等边距内插方法网格间距采用预设值0.1-10km，被评价区内页岩有效厚度大于有效厚度预设值3-15米时，采用5米作为页岩有效厚度分布区边界，页岩有效厚度大于5米的区域为有效页岩分布区。
  21. 根据权利要求13所述的预测装置，其中，所述有效厚度层段内的可采油资源丰度值和可采气资源丰度值模型建立模块具体用于根据单位质量岩石可采油气量、测井间距、岩石密度和有效厚度层段，按照单位面积的有效厚度层段内岩石可采油量、可采气量，分别建立有效页岩层段内的可采油资源丰度值和可采气资源丰度值模型。
  22. 根据权利要求21所述的预测装置，其中，所述有效厚度层段内的可采油资源丰度值和可采气资源丰度值模型建立模块进一步用于按照以下公式分别建立有效页岩层段内的可采油资源丰度值和可采气资源丰度值模型：
    Figure PCTCN2021104637-appb-100013
    Figure PCTCN2021104637-appb-100014
    其中，AOR为待评价区的有效页岩层段内的可采油资源丰度，万吨/km 2；AGR为待评价区的有效页岩层段内的可采气资源丰度，亿立方米/km 2；Q po_i为待评价区的有效厚度层段内第i测井点的单位质量岩石可采油量，mg/g·rock；Q pg_i为待评价区的有效厚度层段内第i测井点的单位质量岩石可采气量，m 3/t·rock；ρ i为待评价区的有效厚度层段内第i测井点的岩石密度值，g/cm 3；L int er为被评价井的测井间距，m；n为有效厚度层段内的测井点总数，n为整数。
  23. 根据权利要求13，21-22任一项所述的预测装置，其中，所述有效厚度层段内的可采油资源丰度值和可采气资源丰度值模型建立模块包括测井解释点的单位质量岩石的可采油量和单位质量岩石的可采气量获取单元，用于：
    根据待评价区的测井解释的总有机碳含量，获取有效页岩层段内测井解释点的总有机碳含量、岩石密度值、测量间距值，再根据有效页岩层段内测井解释点的总有机碳含量、岩石密度值、测量间距值及目的层井点的镜质体反射率，利用页岩原位转化 的可采油量预测模型及页岩原位转化的可采气量预测模型，获取测井解释点的单位质量岩石的可采油量和单位质量岩石的可采气量。
  24. 根据权利要求13所述的预测装置，其中，所述可采油资源量和可采气资源量预测模型建立模块具体用于
    根据有效页岩分布区网格点的可采油气资源丰度和有效页岩分布区面积，按照以下公式分别建立可采油资源量和可采气资源量预测模型：
    Figure PCTCN2021104637-appb-100015
    Figure PCTCN2021104637-appb-100016
    其中，NO为待评价区可采油资源量，万吨；NG为待评价区可采气资源量，亿立方米；AOR j为有效页岩分布区内第j个网格可采油资源丰度，万吨/km 2；AGR j为有效页岩分布区内第j个网格可采气资源丰度，亿立方米/km 2；A j为有效页岩分布区内第j个网格的面积，km 2；m为有效页岩分布区内的网格数，m为整数。
  25. 一种计算机设备，包括存储器、处理器及存储在存储器上并可在处理器上运行的计算机程序，其中，所述处理器执行所述计算机程序时实现权利要求1-12任一项所述页岩原位转化可采油气资源量的预测方法的步骤。
  26. 一种计算机可读存储介质，其上存储有计算机程序，其中，所述计算机程序被处理器执行时实现权利要求1-12任一项所述页岩原位转化可采油气资源量的预测方法的步骤。
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