CN111636866B - Reservoir analysis method, system and device for carbonate hydrocarbon reservoir and storage medium - Google Patents
Reservoir analysis method, system and device for carbonate hydrocarbon reservoir and storage medium Download PDFInfo
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- CN111636866B CN111636866B CN202010386229.9A CN202010386229A CN111636866B CN 111636866 B CN111636866 B CN 111636866B CN 202010386229 A CN202010386229 A CN 202010386229A CN 111636866 B CN111636866 B CN 111636866B
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- E—FIXED CONSTRUCTIONS
- E21—EARTH DRILLING; MINING
- E21B—EARTH DRILLING, e.g. DEEP 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
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- E—FIXED CONSTRUCTIONS
- E21—EARTH DRILLING; MINING
- E21B—EARTH DRILLING, e.g. DEEP DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS
- E21B47/00—Survey of boreholes or wells
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V9/00—Prospecting or detecting by methods not provided for in groups G01V1/00 - G01V8/00
Abstract
The invention provides a reservoir analysis method, a system, a device and a storage medium for carbonate rock oil and gas reservoirs. The method comprises the following steps: acquiring basic data and production data of a well drilled in a work area, and establishing a first data set; forming a single well classification scheme based on the first dataset capacity data and/or the fluid geochemical parameter data; combining the single well classification scheme with geological and geophysical interpretation results, analyzing the relation among the wells in the single well classification scheme, mining the hidden relation of different types of wells, and reversely pushing the oil and gas reservoir process to form a mapping relation between the oil and gas reservoir period and the single well drilling result; and further determining the area with oil gas development potential in the favorable trap distribution according to the mapping relation between the oil gas reservoir period and the single well drilling result. The method integrates geological, geophysical and production data by adopting a data driving technology, carries out reservoir analysis of the carbonate hydrocarbon reservoir based on facts rather than previous experience, and provides basis for exploration decision-making.
Description
Technical Field
The invention relates to the technical field of petroleum exploration, in particular to a method, a system, a device and a storage medium for carrying out reservoir analysis on a complex overlapped basin carbonate reservoir by utilizing a data driving method.
Background
In recent years, deep water and deep oil and gas exploration activities are very active, and more than 1290 oil and gas reservoirs are found in deep basins worldwide and are mainly located in North America, russia, italy and other areas. US snow Buddha dragonJack and st.mallo hydrocarbons found by companies in the gulf of mexico "the ancient system area" are reservoirs that have been found to be the greatest in burial depths. The deep reservoirs have been found to be predominantly gas reservoirs and oil reservoirs worldwide, with 42% of the natural gas reservoirs accounting for 51% of 1477 deep, ultra-deep reservoirs found. In the oil-gas field with global burial depth greater than 6000m, the residual recoverable oil reserve of 105X 10 is detected 8 t, 4.45% of total petroleum recoverable reserves; determination of the residual recoverable reserves of Natural gas 70×10 8 t oil equivalent, accounting for 4.71% of the total recoverable reserves of natural gas.
Searching oil gas in the ultra-deep carbonate rock stratum of the China sea basin is one of the trends of the future oil gas exploration in China. In recent years, significant progress has been made in the exploration of oil and gas in deep and ultra-deep layers of Tarim, sichuan and Erdos basins. However, the deep carbonate reservoir in China is old in age (mainly in ancient kingdom), has strong heterogeneity and poor medium pore permeability, and is complex in oil and gas distribution due to multi-stage oil and gas reservoir formation caused by multi-stage structural movement. Even if a dessert area is found, whether there is oil or gas in the trap is still a fan. Therefore, it is necessary to conduct analysis of the oil and gas reservoir process.
In order to solve the problem of deep carbonate reservoir heterogeneity and multi-stage oil and gas mixed source reservoir formation, the invention provides a new workflow, adopts a data driving technology to integrate geological, geophysical and production data, and provides exploration decisions based on facts rather than previous experience.
Disclosure of Invention
The invention aims to provide a reservoir formation analysis method of a carbonate rock oil-gas reservoir, which is used for solving the problem of strong heterogeneity of a deep carbonate rock reservoir and reservoir formation of a multi-stage oil-gas mixed source. The method integrates geological, geophysical and production data by adopting a data driving technology, carries out reservoir analysis of the carbonate hydrocarbon reservoir based on facts rather than previous experience, and provides basis for exploration decision-making.
In order to achieve the above object, the present invention provides a reservoir formation analysis method for a carbonate rock hydrocarbon reservoir, wherein the method comprises:
and (3) data acquisition: acquiring data of a well drilled in a work area, wherein the data comprises basic data of the well drilled and production data, and establishing a first data set; the basic data comprise coordinate data, elevation data, drilling horizon data and well depth data; the production data includes at least one of production data including oil production data, gas production data, and water production data, and fluid geochemical parameter data including oil geochemical parameter data, natural gas geochemical parameter data, and water geochemical parameter data;
Establishing a classification scheme: forming a single well classification scheme based on production data in the first dataset;
geological interpretation of classification results: obtaining geological and geophysical interpretation results, combining the single well classification scheme with the geological and geophysical interpretation results, analyzing the relation among the wells in the single well classification scheme so as to mine the hidden relation of the wells of different types, and reversely pushing the oil and gas reservoir process to form the mapping relation between the reservoir period and the single well drilling result in the oil and gas reservoir process, so that a reliable geological interpretation conclusion of the classification result is obtained;
oil and gas exploration decision: and further determining the area with oil gas development potential in the favorable trap distribution according to the mapping relation between the time of the reservoir formation and the drilling result of the single well in the oil gas reservoir formation process.
In the above reservoir analysis method of a carbonate hydrocarbon reservoir, preferably, the data acquisition process further includes a data cleaning step of: and cleaning the drilled well data, removing the disfavored well caused by engineering problems in the drilled well, and discarding the data of the disfavored well caused by engineering problems in the drilled well.
In the reservoir analysis method of a carbonate hydrocarbon reservoir, preferably, the forming a single well classification scheme based on the capacity data and/or the fluid geochemical parameter data in the first data set includes:
Analyzing production data in the first data set, determining an attribute according to which a single well classification scheme classifies as a classification attribute, and determining classification attribute distribution of each single well in the first data set;
acquiring the hydrocarbon source rock position, hydrocarbon generation history, hydrocarbon discharge history and main geological background analysis parameters formed in the oil and gas accumulation period of a target area;
based on the geological background analysis parameters, according to the matching condition of the classification attribute distribution of each single well and the geological background analysis parameters, adopting a parameter discriminant analysis method to optimize the classification types (for example, at least 5 types) and the classification standards in the single well classification scheme, and classifying each single well to form the single well classification scheme. The single well classification scheme is obtained by adopting the data driving method according to the preferred scheme, and the formed single well classification scheme is more reliable.
In the above reservoir analysis method of a carbonate hydrocarbon reservoir, preferably, forming a single well classification scheme based on the production data in the first data set includes: the drilled wells are divided into dry wells, gas wells, water wells, oil and gas wells based on the capacity data in the first dataset. More preferably, forming a single well classification scheme based on production data in the first dataset comprises: and completing the casting on the oil-gas-water separation trigonometric graph based on the productivity data in the first data set, and dividing the drilled well into a dry well, a gas well, a water well, an oil well and a gas-oil well according to the distribution condition of the casting points of each well on the oil-gas-water separation trigonometric graph. Wherein the capacity data based on the first data set preferably refers to earlier test capacity data (e.g., the first 10 days test capacity data) among the capacity data based on the first data set. The early test productivity data can reflect the original geological condition.
In the above reservoir formation analysis method of a carbonate hydrocarbon reservoir, preferably, the formation of the single well classification scheme based on the production data in the first data set is achieved by: and dividing the energy production data and/or the fluid geochemical parameter data by taking a single well as a minimum research unit and adopting an unsupervised machine learning algorithm to form a single well classification scheme.
In the above reservoir formation analysis method of a carbonate hydrocarbon reservoir, preferably, in a geological interpretation process of a classification result, the obtaining of geological and geophysical interpretation results, combining the single well classification scheme with the geological and geophysical interpretation results, analyzing relationships between wells in the single well classification scheme to further mine hidden relationships of different types of wells, and reversely pushing the hydrocarbon reservoir formation process to form a mapping relationship between a reservoir formation period and a single well drilling result in the hydrocarbon reservoir formation process includes:
obtaining geological and geophysical interpretation results to form a key horizon top surface structure diagram, a section structure diagram and an ancient structure diagram of each key hiding period;
the method comprises the steps of (1) carrying out relation analysis on each type of well in the single well classification scheme on a key horizon top surface structural diagram and a profile structural diagram, wherein the relation between each well and each geological structure is excavated, and the relation between each well and each geological structure comprises the main control fault of each well and the corresponding relation between produced fluid of each well and reservoir layer structural units so as to realize the excavation of hidden relations of different types of wells;
And throwing each well in the single well classification scheme to the ancient structural diagram of each key reservoir period, and reversely pushing the oil and gas reservoir process according to the main control fault of each well and the corresponding relation between the produced fluid of each well and the reservoir structural unit to form the mapping relation between the reservoir period and the single well drilling result in the oil and gas reservoir process.
In the reservoir formation analysis method of the carbonate hydrocarbon reservoir, preferably, after geological and geophysical interpretation results are obtained, faults are further classified according to the geological and geophysical interpretation results, and the fault classification results are used for subsequent analysis of relations among wells in a single well classification scheme so as to mine hidden relations of different types of wells, and the hydrocarbon reservoir formation process is reversely pushed to form a mapping relation between reservoir formation period times in the hydrocarbon reservoir formation process and a single well drilling result. More preferably, the classifying of faults into three categories of faults including primary faults, secondary faults and tertiary faults; the first-level fault is a work area main control fault, the second-level fault is a fault connected with the main control fault, and the third-level fault is a relatively isolated fault.
In the reservoir analysis method of a carbonate hydrocarbon reservoir, preferably, the hydrocarbon exploration decision step further includes: and further determining well position deployment of the next oil gas exploratory well in the favorable trap distribution according to the mapping relation between the time of the oil gas reservoir formation and the drilling result of the single well.
The invention also provides a reservoir analysis system of the carbonate rock oil and gas reservoir, wherein the system comprises:
and a data acquisition module: the method comprises the steps of obtaining drilled basic data and production data of a work area, and establishing a first data set; the basic data comprise coordinate data, elevation data, drilling horizon data and well depth data; the production data includes at least one of production data including oil production data, gas production data, and water production data, and fluid geochemical parameter data including oil geochemical parameter data, natural gas geochemical parameter data, and water geochemical parameter data;
the classification scheme establishment module: the production data are used for the first data set to form a single well classification scheme;
the classification result geological interpretation module: the classification result geological interpretation module comprises a first acquisition sub-module and a first interpretation sub-module; the first acquisition submodule is used for acquiring geology and geophysical interpretation results; the first interpretation submodule is used for combining the single well classification scheme with geological and geophysical interpretation results, analyzing the relation among the wells in the single well classification scheme so as to mine the hidden relation of different types of wells, and reversely pushing the oil gas reservoir forming process to form the mapping relation between the reservoir forming period and the single well drilling result in the oil gas reservoir forming process, so that a reliable geological interpretation conclusion of the classification result is obtained;
The oil gas exploration decision module: the method is used for further determining the area with oil gas development potential in the favorable trap distribution according to the mapping relation between the time of the reservoir formation and the drilling result of the single well in the oil gas reservoir formation process.
In the reservoir analysis system of a carbonate hydrocarbon reservoir, preferably, the data acquisition module further includes a data cleaning sub-module: and cleaning the drilled well data, removing the disfavored well caused by engineering problems in the drilled well, and discarding the data of the disfavored well caused by engineering problems in the drilled well.
In the reservoir analysis system of a carbonate hydrocarbon reservoir described above, preferably, the classification scheme establishment module includes:
the single well classification attribute distribution forms a sub-module: the method comprises the steps of analyzing production data in a first data set, determining an attribute according to which a single well classification scheme classifies as a classification attribute, and determining classification attribute distribution of each single well in the first data set;
the geologic background analysis parameters form a sub-module: the method comprises the steps of obtaining a hydrocarbon source rock position, a hydrocarbon generation history, a hydrocarbon discharge history and a main hydrocarbon accumulation period of a hydrocarbon reservoir of a target area to form geological background analysis parameters;
the classification scheme forms a sub-module: based on the geological background analysis parameters, according to the matching condition of the classification attribute distribution of each single well and the geological background analysis parameters, adopting a parameter discriminant analysis method to optimize the classification types (at least 5 types for example) and the classification standards in the single well classification scheme and classifying each single well to form the single well classification scheme.
In the reservoir analysis system of a carbonate hydrocarbon reservoir described above, preferably, forming the single well classification scheme based on the production data in the first dataset comprises: the drilled wells are divided into dry wells, gas wells, water wells, oil and gas wells based on the capacity data in the first dataset. More preferably, forming a single well classification scheme based on production data in the first dataset comprises: and completing the casting on the oil-gas-water separation trigonometric graph based on the productivity data in the first data set, and dividing the drilled well into a dry well, a gas well, a water well, an oil well and a gas-oil well according to the distribution condition of the casting points of each well on the oil-gas-water separation trigonometric graph. Wherein the capacity data based on the first data set preferably refers to earlier test capacity data (e.g., the first 10 days test capacity data) among the capacity data based on the first data set. The early test productivity data can reflect the original geological condition.
In the reservoir analysis system of a carbonate hydrocarbon reservoir described above, preferably, the formation of the single well classification scheme based on the production data in the first data set is achieved by: and dividing the energy production data and/or the fluid geochemical parameter data by taking a single well as a minimum research unit and adopting an unsupervised machine learning algorithm to form a single well classification scheme.
In the reservoir analysis system of a carbonate hydrocarbon reservoir as described above, preferably, the first interpretation submodule includes:
and (3) constructing a graph forming unit: the method is used for forming a key horizon top surface structural diagram, a section structural diagram and an ancient structural diagram of each key hiding period based on geological and geophysical interpretation results;
hidden relation mining unit: the method is used for carrying out the analysis of the relation between the wells in the single well classification scheme on the top surface structural diagram and the section structural diagram of the key layer from the well throwing points of the various types in the single well classification scheme, and the relation between the wells and the geological structures is excavated, wherein the excavation of the hidden relation of the various types of wells is realized by the main control fault of the wells and the corresponding relation between the produced fluid of the wells and the reservoir layer structural unit;
the mapping relation forming unit: and the method is used for throwing each well to the ancient structure diagram of each key reservoir period in the single well classification scheme, and reversely pushing the oil and gas reservoir process according to the main control fault of each well and the corresponding relation between the produced fluid of each well and the reservoir structure unit to form the mapping relation between the reservoir period and the single well drilling result in the oil and gas reservoir process.
In the reservoir analysis system of a carbonate hydrocarbon reservoir described above, preferably, the classification result geological interpretation module further includes:
Fault classification sub-module: the method is used for classifying faults according to geological and geophysical interpretation results, and using the fault classification results in the process of subsequently analyzing the relations among the wells in the single well classification scheme so as to mine the hidden relations of different types of wells, and reversely pushing the oil and gas reservoir process to form the mapping relation between the reservoir period and the single well drilling result in the oil and gas reservoir process.
More preferably, the classifying of faults into three categories of faults including primary faults, secondary faults and tertiary faults; the first-level fault is a work area main control fault, the second-level fault is a fault connected with the main control fault, and the third-level fault is a relatively isolated fault.
In the reservoir analysis system of a carbonate hydrocarbon reservoir, preferably, the hydrocarbon exploration decision module further includes:
a well position deployment submodule of the oil gas exploratory well: the method is used for further determining well position deployment of the next oil gas exploratory well in favorable trap distribution according to the mapping relation between the time of the oil gas reservoir formation and the drilling result of the single well.
The invention also provides a reservoir analysis device of the carbonate rock oil and gas reservoir, which comprises a processor and a memory; wherein, the liquid crystal display device comprises a liquid crystal display device,
A memory for storing a computer program;
and the processor is used for realizing the steps of the reservoir analysis method of the carbonate rock oil and gas reservoir when executing the program stored in the memory.
The present invention also provides a computer readable storage medium storing one or more programs executable by one or more processors to perform the steps of reservoir analysis of a carbonate hydrocarbon reservoir described above.
The above-described solution provided by the present invention integrates geological, geophysical and production data using data-driven techniques to provide exploration decisions based on facts rather than previous experience. Solves the problem of difficult reservoir analysis caused by reservoir formation of complex overlapped basin deep carbonate reservoirs due to strong heterogeneity and multi-period oil-gas mixed sources.
Drawings
For a clearer description of the technical solutions of the embodiments of the present invention, the following description will briefly explain the drawings needed in the embodiments, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and other drawings can be obtained according to these drawings without inventive effort for a person skilled in the art:
FIG. 1 is a schematic flow chart of a reservoir analysis method for a carbonate hydrocarbon reservoir according to an embodiment of the present invention;
FIG. 2 is an optimized schematic diagram of the steps for creating a classification scheme in a reservoir analysis method for a carbonate hydrocarbon reservoir according to an embodiment of the present invention;
FIG. 3 is an optimized schematic diagram of the steps for creating a classification scheme in a reservoir analysis method for a carbonate hydrocarbon reservoir according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of a reservoir analysis system for a carbonate hydrocarbon reservoir according to one embodiment of the present invention;
FIG. 5 is a schematic diagram of an optimized structure of a classification scheme setup module in a reservoir analysis system for carbonate reservoirs according to an embodiment of the present invention;
FIG. 6 is a schematic diagram of an optimized structure of a first interpretation sub-module in a reservoir analysis system for a carbonate hydrocarbon reservoir according to an embodiment of the present invention;
FIG. 7 is a schematic diagram of a reservoir analysis device for a carbonate hydrocarbon reservoir according to an embodiment of the present invention;
fig. 8 is an effect diagram of each type of well throwing point to a construction diagram in a reservoir formation analysis method of a carbonate hydrocarbon reservoir according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention more clear, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. It will be apparent that the described embodiments are some, but not all, embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to fall within the scope of the invention.
The principles and spirit of the present invention are described in detail below with reference to several representative embodiments thereof.
Referring to fig. 1, an embodiment of the present invention provides a method for analyzing a bead space development rule, the method comprising:
step S1, data acquisition: acquiring data of a well drilled in a work area, wherein the data comprises basic data of the well drilled and production data, and establishing a first data set; the basic data comprise coordinate data, elevation data, drilling horizon data and well depth data; the production data includes at least one of production data including oil production data, gas production data, and water production data, and fluid geochemical parameter data including oil geochemical parameter data, natural gas geochemical parameter data, and water geochemical parameter data;
step S2, establishing a classification scheme: forming a single well classification scheme based on production data in the first dataset;
step S3, geological interpretation of the classification result: obtaining geological and geophysical interpretation results, combining the single well classification scheme with the geological and geophysical interpretation results, analyzing the relation among the wells in the single well classification scheme so as to mine the hidden relation of the wells of different types, and reversely pushing the oil and gas reservoir process to form the mapping relation between the reservoir period and the single well drilling result in the oil and gas reservoir process, so that a reliable geological interpretation conclusion of the classification result is obtained;
Step S4, oil and gas exploration decision: and further determining the area with oil gas development potential in the favorable trap distribution according to the mapping relation between the time of the reservoir formation and the drilling result of the single well in the oil gas reservoir formation process.
The elevation data is used for determining the elevation of the drilled well, and can comprise ground elevation data and heart tonifying elevation data.
The oil production data can comprise single-well daily oil production data, single-well accumulated oil production data and/or single-well initial oil production data.
The gas production data can comprise single well daily gas production data, single well accumulated gas production data and/or single well initial gas production data.
The water yield data can comprise single-well daily water yield data, single-well accumulated water yield data and/or single-well initial water yield data.
Further, the data acquisition process in step S1 may further include a data cleansing step: and cleaning the drilled well data, removing the disfavored well caused by engineering problems in the drilled well, and discarding the data of the disfavored well caused by engineering problems in the drilled well.
Further, referring to fig. 2, in step S2, the establishing a classification scheme may include:
step S21: analyzing production data in the first data set, determining an attribute according to which a single well classification scheme classifies as a classification attribute, and determining classification attribute distribution of each single well in the first data set;
Step S22: acquiring the hydrocarbon source rock position, hydrocarbon generation history, hydrocarbon discharge history and main geological background analysis parameters formed in the oil and gas accumulation period of a target area;
step S23: based on the geological background analysis parameters, according to the matching condition of the classification attribute distribution of each single well and the geological background analysis parameters, adopting a parameter discriminant analysis method (such as a K-means algorithm) to optimize the classification types (such as classification into at least 5 types) and the classification standards in the single well classification scheme, and classifying each single well to form the single well classification scheme. The single well classification scheme is obtained by adopting the data driving method according to the preferred scheme, and the formed single well classification scheme is more reliable.
Further, in step S2, the forming a single well classification scheme based on the production data in the first dataset may include: and (3) taking a single well as a minimum research unit, and dividing productivity data and/or fluid geochemical parameter data in the first data set established in the step (S1) by adopting an unsupervised machine learning algorithm to form at least one well-drilled single well classification scheme. The unsupervised machine learning algorithm may be selected from a random forest, a decision tree, a neural network, or the like, but is not limited thereto.
In an embodiment, in step S2, the forming a single well classification scheme based on the production data in the first dataset may include: the drilled wells are divided into dry wells, gas wells, water wells, oil and gas wells based on the capacity data in the first dataset. Specifically, forming a single well classification scheme based on production data in the first dataset includes: and completing the casting on the oil-gas-water separation trigonometric graph based on the productivity data in the first data set, and dividing the drilled well into a dry well, a gas well, a water well, an oil well and a gas-oil well according to the distribution condition of the casting points of each well on the oil-gas-water separation trigonometric graph. Wherein the capacity data based on the first data set preferably refers to earlier test capacity data (e.g., the first 10 days test capacity data) among the capacity data based on the first data set. The early test productivity data can reflect the original geological condition.
Further referring to fig. 3, in step S3, the obtaining a geological and geophysical interpretation result, combining the single-well classification scheme with the geological and geophysical interpretation result, analyzing the relationship between the wells in the single-well classification scheme to further mine the hidden relationship of the wells of different types, and reversely pushing the oil and gas reservoir process to form the mapping relationship between the reservoir period and the single-well drilling result in the oil and gas reservoir process may include:
Step S31: obtaining geological and geophysical interpretation results to form a key horizon top surface structure diagram, a section structure diagram and an ancient structure diagram of each key hiding period;
step S32: the method comprises the steps of (1) carrying out relation analysis on each type of well in the single well classification scheme on a key horizon top surface structural diagram and a profile structural diagram, wherein the relation between each well and each geological structure is excavated, and the relation between each well and each geological structure comprises the main control fault of each well and the corresponding relation between produced fluid of each well and reservoir layer structural units so as to realize the excavation of hidden relations of different types of wells;
step S33: and throwing each well in the single well classification scheme to the ancient structural diagram of each key reservoir period, and reversely pushing the oil and gas reservoir process according to the main control fault of each well and the corresponding relation between the produced fluid of each well and the reservoir structural unit to form the mapping relation between the reservoir period and the single well drilling result in the oil and gas reservoir process.
The reverse thrust oil and gas reservoir process according to the main control fault of each well and the corresponding relation between the produced fluid of each well and the reservoir formation unit can be performed by the existing means, but is not limited to the method. For example, based on the main control fault of each well and the corresponding relation between the produced fluid of each well and the reservoir formation unit, the openness and the closure of each fault are specifically analyzed, and the oil and gas reservoir process is reversely pushed by combining the fluid mixing effect.
The geological and geophysical interpretation results specifically comprise: geological achievements: the horizon of the reservoir, the elevation of the horizon, the hierarchical classification of fractures, etc.; geophysical interpretation effort: the seismic data identifies a variety of fractures including strike, dip, etc. of the fracture.
Further, in step S3, after the geological and geophysical interpretation results are obtained, the fault may be further classified according to the geological and geophysical interpretation results, and the fault classification result may be used in a process of subsequently analyzing the relationships between the wells in the single well classification scheme to further mine the hidden relationships of the wells of different types, and the oil and gas reservoir process is reversely pushed to form a mapping relationship between the reservoir period and the single well drilling result in the oil and gas reservoir process. In an embodiment, the classifying the faults may be classifying the faults into three types of primary faults, secondary faults and tertiary faults; the first-level fault is a work area main control fault, the second-level fault is a fault connected with the main control fault, and the third-level fault is a relatively isolated fault.
Further, in step S4, the hydrocarbon exploration decision step may further comprise: and further determining well position deployment of the next oil gas exploratory well in the favorable trap distribution according to the mapping relation between the time of the oil gas reservoir formation and the drilling result of the single well. In a specific embodiment, a mapping method is used for carrying out favorable trap distribution and superposition of mapping relations between the reservoir formation period and the single well drilling result in the oil and gas reservoir formation process, an oil and gas production advantage area is divided, and well position deployment of the oil and gas exploration well in the next step is determined.
Further, the mapping relationship between the reservoir formation times and the single well drilling results in the oil and gas reservoir formation process may specifically refer to the mapping relationship between the reservoir formation times and the single well oil and gas water production ratio drilling results in the oil and gas reservoir formation process.
The hydrocarbon in the hole-type hydrocarbon reservoir of the otto carbonate rock in the bulge area in the tower of the Tarim basin is mainly from the hydrocarbon source rocks of the lower middling system (epsilon 1+2) and the middle-upper otto (O2+3); it undergoes three main hydrocarbon elimination phases in the late california stage, the late westernly stage and the himalayan stage. Because of the presence of two sets of source rocks and three main hydrocarbon removal phases, hydrocarbon migration and accumulation in the region of the column is very complex.
Still another embodiment of the present invention provides a reservoir formation analysis method for a carbonate hydrocarbon reservoir for performing a reservoir formation analysis on an otto carbonate fracture-cavity hydrocarbon reservoir in a bulge area in a tower of a basin of a talus, the method specifically comprising:
(1) And (3) data acquisition:
acquiring data of a well drilled in a work area, wherein the data comprise basic data and production data of the well drilled; the basic data comprise coordinate data, ground elevation data, heart tonifying elevation data, drilling horizon data and well depth data; the production data comprises production data and fluid geochemical parameter data, the production data comprises oil production data, gas production data and water production data, and the fluid geochemical parameter data comprises oil geochemical parameter data, natural gas geochemical parameter data and water geochemical parameter data; the oil production data comprises single well daily oil production, single well accumulated oil production and single well early test oil production (first 5 days test oil production), the gas production data comprises single well daily gas production, single well accumulated gas production and single well early test gas production (first 5 days test gas production), and the water production data comprises single well daily water production, single well accumulated water production and single well early test water production (first 5 days test gas production);
Data cleaning: cleaning the obtained data of the drilled well, removing the disfavored well caused by engineering problems in the drilled well, and discarding the data of the disfavored well caused by engineering problems in the drilled well
Establishing a first data set based on the data, wherein the first data set comprises a single well data subset (consisting of the well numbers of the wells) and a parameter data subset (production data and basic data of the wells corresponding to the well numbers in the single well data subset);
(2) Establishing a classification scheme:
analyzing production data in the first data set by using an unsupervised machine learning algorithm, determining the basis of classification of a single well classification scheme as classification attribute, determining the proportion of oil, water and gas produced by a single well early test (the data produced in the first 10 days), determining the proportion of oil, water and gas produced by each single well early test (the data produced in the first 10 days) based on the oil production, the gas production and the water production of the single well early test, and determining the classification attribute distribution of each single well by completing the point throwing on an oil-gas-water distribution triangular diagram;
acquiring the hydrocarbon source rock position, hydrocarbon generation history, hydrocarbon discharge history and main geological background analysis parameters formed in the oil and gas accumulation period of a target area;
Based on the geological background analysis parameters, according to the coincidence condition of the classification attribute distribution of each single well and the geological background analysis parameters, adopting a parameter discriminant analysis method to optimize the classification types and the classification standards in the single well classification scheme and classify each single well to form a single well classification scheme, and in the embodiment, classifying each single well into 5 types of dry wells, gas wells, water wells, oil wells and condensate gas wells;
(3) Geological interpretation of classification results:
obtaining geological and geophysical interpretation results;
classifying faults in a work area according to geological and geophysical interpretation results, and particularly dividing the faults into three types, namely a primary fault, a secondary fault and a tertiary fault, wherein the primary fault is a main control fault of the work area, the secondary fault is a fault connected with the main control fault, and the tertiary fault is a relatively isolated fault;
forming a key horizon top surface structure diagram, a section structure diagram and an ancient structure diagram of each key hiding period (late in the Jia-Lidong period, late in the He-West period and Himalayan period) based on geology, geophysical interpretation results and fault classification results;
the method comprises the steps of (1) throwing points of all types of wells in the single-well classification scheme to a key horizon top surface structural diagram and a profile structural diagram (shown in fig. 8) to realize analysis of relations among all the wells in the single-well classification scheme, wherein the excavation of relations between all the wells and geological structures comprises excavation of hidden relations among different types of wells, wherein the excavation comprises main control faults of all the wells and the corresponding relations between produced fluids of all the wells and reservoir structural units;
The method comprises the steps of throwing each well in the single well classification scheme to an ancient structural diagram of each key reservoir period, and reversely pushing the oil gas reservoir process according to the main control fault of each well and the corresponding relation between produced fluid of each well and reservoir layer structural units to form a mapping relation between reservoir period times and single well drilling results in the oil gas reservoir process;
(4) Oil and gas exploration decision:
according to the mapping relation between the reservoir period and the single well drilling result in the reservoir process of the oil gas, the area with the oil gas development potential is further determined in the favorable trap distribution, and the well position deployment of the oil gas exploratory well in the next step is determined.
The embodiment of the invention also provides a reservoir analysis system of the carbonate rock oil and gas reservoir, and preferably the system is used for realizing the method embodiment.
Fig. 4 is a block diagram of a reservoir analysis system of a carbonate hydrocarbon reservoir according to an embodiment of the present invention, as shown in fig. 4, the apparatus including:
data acquisition module 41: the method comprises the steps of obtaining drilled basic data and production data of a work area, and establishing a first data set; the basic data comprise coordinate data, elevation data, drilling horizon data and well depth data; the production data includes at least one of production data including oil production data, gas production data, and water production data, and fluid geochemical parameter data including oil geochemical parameter data, natural gas geochemical parameter data, and water geochemical parameter data;
Classification scheme establishment module 42: the production data are used for the first data set to form a single well classification scheme;
classification result geological interpretation module 43: the classification result geological interpretation module comprises a first acquisition sub-module 431 and a first interpretation sub-module 432; wherein, the first obtaining sub-module 431 is used for obtaining geology and geophysical interpretation results; the first interpretation submodule 432 is configured to combine the single well classification scheme with geological and geophysical interpretation results, analyze relationships between wells in the single well classification scheme, and further mine hidden relationships of different types of wells, and reversely push the oil and gas reservoir process to form a mapping relationship between the reservoir period and the single well drilling result in the oil and gas reservoir process, so as to obtain a reliable geological interpretation conclusion of the classification result;
the hydrocarbon exploration decision module 44: the method is used for further determining the area with oil gas development potential in the favorable trap distribution according to the mapping relation between the time of the reservoir formation and the drilling result of the single well in the oil gas reservoir formation process.
Further, the data acquisition module 41 further includes a data cleansing sub-module: and cleaning the drilled well data, removing the disfavored well caused by engineering problems in the drilled well, and discarding the data of the disfavored well caused by engineering problems in the drilled well.
With continued reference to fig. 5, the classification scheme establishment module 42 may include:
the single well classification attribute distribution forms sub-module 421: the method comprises the steps of analyzing production data in a first data set, determining an attribute according to which a single well classification scheme classifies as a classification attribute, and determining classification attribute distribution of each single well in the first data set;
the geologic background analysis parameters form sub-module 422: the method comprises the steps of obtaining a hydrocarbon source rock position, a hydrocarbon generation history, a hydrocarbon discharge history and a main hydrocarbon accumulation period of a hydrocarbon reservoir of a target area to form geological background analysis parameters;
the classification scheme forms sub-module 423: based on the geological background analysis parameters, according to the matching condition of the classification attribute distribution of each single well and the geological background analysis parameters, adopting a parameter discriminant analysis method to optimize the classification types (at least 5 types for example) and the classification standards in the single well classification scheme and classifying each single well to form the single well classification scheme.
Further, forming a single well classification scheme based on the production data in the first dataset may include: forming a single well classification scheme based on production data in the first dataset includes: the drilled wells are divided into dry wells, gas wells, water wells, oil and gas wells based on the capacity data in the first dataset. In an embodiment, forming a single well classification scheme based on production data in the first dataset comprises: and completing the casting on the oil-gas-water separation trigonometric graph based on the productivity data in the first data set, and dividing the drilled well into a dry well, a gas well, a water well, an oil well and a gas-oil well according to the distribution condition of the casting points of each well on the oil-gas-water separation trigonometric graph. Wherein the capacity data based on the first data set preferably refers to earlier test capacity data (e.g., the first 10 days test capacity data) among the capacity data based on the first data set. The early test productivity data can reflect the original geological condition.
Further, forming a single well classification scheme based on production data in the first dataset may be accomplished by: and dividing the energy production data and/or the fluid geochemical parameter data by taking a single well as a minimum research unit and adopting an unsupervised machine learning algorithm to form a single well classification scheme.
With continued reference to fig. 6, the first interpretation sub-module 432 described above may include:
construction diagram forming unit 4321: the method is used for forming a key horizon top surface structural diagram, a section structural diagram and an ancient structural diagram of each key hiding period based on geological and geophysical interpretation results;
hidden relation mining unit 4322: the method is used for carrying out the analysis of the relation between the wells in the single well classification scheme on the top surface structural diagram and the section structural diagram of the key layer from the well throwing points of the various types in the single well classification scheme, and the relation between the wells and the geological structures is excavated, wherein the excavation of the hidden relation of the various types of wells is realized by the main control fault of the wells and the corresponding relation between the produced fluid of the wells and the reservoir layer structural unit;
mapping relation forming unit 4323: and the method is used for throwing each well to the ancient structure diagram of each key reservoir period in the single well classification scheme, and reversely pushing the oil and gas reservoir process according to the main control fault of each well and the corresponding relation between the produced fluid of each well and the reservoir structure unit to form the mapping relation between the reservoir period and the single well drilling result in the oil and gas reservoir process.
Further, the classification result geological interpretation module 43 may further include: fault classification sub-module: the method is used for classifying faults according to geological and geophysical interpretation results, and using the fault classification results in the process of subsequently analyzing the relations among the wells in the single well classification scheme so as to mine the hidden relations of different types of wells, and reversely pushing the oil and gas reservoir process to form the mapping relation between the reservoir period and the single well drilling result in the oil and gas reservoir process.
In an embodiment, the classifying the faults may be classifying the faults into three types of primary faults, secondary faults and tertiary faults; the first-level fault is a work area main control fault, the second-level fault is a fault connected with the main control fault, and the third-level fault is a relatively isolated fault.
Further, the hydrocarbon exploration decision module 44 may further include: a well position deployment submodule of the oil gas exploratory well: the method is used for further determining well position deployment of the next oil gas exploratory well in favorable trap distribution according to the mapping relation between the time of the oil gas reservoir formation and the drilling result of the single well.
The specific implementation process of each module, each sub-module, and each unit may refer to the description of the above method embodiment, which is not repeated herein.
Fig. 7 is a schematic view of a reservoir analysis device for a carbonate hydrocarbon reservoir in accordance with an embodiment of the invention. The bead space development rule analysis device shown in fig. 7 is a general data processing device, which includes a general computer hardware structure, and at least includes a processor 1000 and a memory 1111; the processor 1000 is configured to execute the molecular structure generation program stored in the memory, so as to implement the reservoir formation analysis method of the carbonate rock hydrocarbon reservoir according to each method embodiment (the specific method refers to the description of the above method embodiment, and is not repeated here).
The embodiment of the invention also provides a computer readable storage medium, which stores one or more programs, and the one or more programs can be executed by one or more processors, so as to implement the method for analyzing the formation analysis development rule of the carbonate rock hydrocarbon reservoir according to each method embodiment (the specific method refers to the description of the method embodiment and is not repeated here).
Preferred embodiments of the present invention are described above with reference to the accompanying drawings. The many features and advantages of the embodiments are apparent from the detailed specification, and thus, it is intended by the appended claims to cover all such features and advantages of the embodiments which fall within the true spirit and scope thereof. Further, since numerous modifications and changes will readily occur to those skilled in the art, it is not desired to limit the embodiments of the invention to the exact construction and operation illustrated and described, and accordingly, all suitable modifications and equivalents may be resorted to, falling within the scope thereof.
It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The principles and embodiments of the present invention have been described in detail with reference to specific examples, which are provided to facilitate understanding of the method and core ideas of the present invention; meanwhile, as those skilled in the art will have variations in the specific embodiments and application scope in accordance with the ideas of the present invention, the present description should not be construed as limiting the present invention in view of the above.
Claims (16)
1. A reservoir formation analysis method of a carbonate hydrocarbon reservoir, wherein the method comprises:
and (3) data acquisition: acquiring drilled data of a work area, wherein the drilled data comprises drilled basic data and production data, and establishing a first data set; the basic data comprise coordinate data, elevation data, drilling horizon data and well depth data; the production data includes at least one of production data including oil production data, gas production data, and water production data, and fluid geochemical parameter data including oil geochemical parameter data, natural gas geochemical parameter data, and water geochemical parameter data;
establishing a classification scheme: forming a single well classification scheme based on the production data in the first dataset, and dividing the drilled well into a dry well, a gas well, a water well, an oil well, and an oil gas well;
geological interpretation of classification results: obtaining geological and geophysical interpretation results; classifying faults according to geological and geophysical interpretation results, and dividing the faults into three types, namely a primary fault, a secondary fault and a tertiary fault, wherein the primary fault is a main control fault of a work area, the secondary fault is a fault connected with the main control fault, and the tertiary fault is a relatively isolated fault; forming a key horizon top surface structural diagram, a section structural diagram and an ancient structural diagram of each key hiding period based on geology, geophysical interpretation results and fault classification results; casting each type of well in the single well classification scheme to a key horizon top surface structural diagram and a section structural diagram, and excavating the relation between each well and each geological structure, wherein the relation comprises the main control fault of each well and the corresponding relation between produced fluid of each well and reservoir layer structural units; the method comprises the steps of throwing each well in the single well classification scheme to an ancient structural diagram of each key reservoir period, and reversely pushing the oil gas reservoir process according to the main control fault of each well and the corresponding relation between produced fluid of each well and reservoir layer structural units to form a mapping relation between reservoir period times and single well drilling results in the oil gas reservoir process;
Oil and gas exploration decision: and further determining the area with oil gas development potential in the favorable trap distribution according to the mapping relation between the time of the reservoir formation and the drilling result of the single well in the oil gas reservoir formation process.
2. The analysis method according to claim 1, wherein the data acquisition process further includes a data cleansing step: and cleaning the drilled data, removing the disfavored well caused by engineering problems in the drilled process, and discarding the data of the disfavored well caused by engineering problems in the drilled process.
3. The analysis method of claim 1, wherein the establishing a classification scheme comprises:
analyzing production data in the first data set, determining an attribute according to which a single well classification scheme classifies as a classification attribute, and determining classification attribute distribution of each single well in the first data set;
acquiring the hydrocarbon source rock position, hydrocarbon generation history, hydrocarbon discharge history and main geological background analysis parameters formed in the oil and gas accumulation period of a target area;
based on the geological background analysis parameters, according to the matching condition of the classification attribute distribution of each single well and the geological background analysis parameters, adopting a parameter discriminant analysis method to optimize the classification types and the classification standards in the single well classification scheme and classifying each single well to form the single well classification scheme.
4. The analysis method of claim 1, wherein forming a single well classification scheme based on production data in the first dataset comprises: and completing the casting on the oil-gas-water separation trigonometric graph based on the productivity data in the first data set, and dividing the drilled well into a dry well, a gas well, a water well, an oil well and a gas-oil well according to the distribution condition of the casting points of each well on the oil-gas-water separation trigonometric graph.
5. The analysis method of claim 4, wherein the capacity data in the first dataset is based on pre-test capacity data in the first dataset.
6. The analysis method of any one of claims 1, 3, 4, and 5, wherein forming a single well classification scheme based on production data in the first dataset is accomplished by: and dividing the energy production data and/or the fluid geochemical parameter data by taking a single well as a minimum research unit and adopting an unsupervised machine learning algorithm to form a single well classification scheme.
7. The method of analysis of claim 1, wherein the hydrocarbon exploration decision step further comprises: and further determining well position deployment of the next oil gas exploratory well in the favorable trap distribution according to the mapping relation between the time of the oil gas reservoir formation and the drilling result of the single well.
8. A reservoir analysis system for a carbonate hydrocarbon reservoir, wherein the system comprises:
and a data acquisition module: the method comprises the steps of obtaining drilled basic data and production data of a work area, and establishing a first data set; the basic data comprise coordinate data, elevation data, drilling horizon data and well depth data; the production data includes at least one of production data including oil production data, gas production data, and water production data, and fluid geochemical parameter data including oil geochemical parameter data, natural gas geochemical parameter data, and water geochemical parameter data;
the classification scheme establishment module: the production data in the first data set are used for forming a single well classification scheme to divide the drilled well into a dry well, a gas well, a water well, an oil well and an oil gas well;
the classification result geological interpretation module: the classification result geological interpretation module comprises a first acquisition sub-module, a fault classification sub-module and a first interpretation sub-module; the first acquisition submodule is used for acquiring geology and geophysical interpretation results; the fault classification submodule is used for classifying faults according to geological and geophysical interpretation results, and dividing the faults into three types, namely a primary fault, a secondary fault and a tertiary fault, wherein the primary fault is a main control fault of a work area, the secondary fault is a fault connected with the main control fault, and the tertiary fault is a relatively isolated fault; the first interpretation submodule comprises a construction diagram forming unit, a hidden relation mining unit and a mapping relation forming unit; the structural diagram forming unit is used for forming an important horizon top surface structural diagram, a section structural diagram and an ancient structural diagram of each key hiding period based on geology, geophysical interpretation results and fault classification results; the hidden relation mining unit is used for throwing all types of wells in the single well classification scheme to the key horizon top surface structural diagram and the section structural diagram, and the relation between each well and each geological structure comprises the main control fault of each well and the corresponding relation between produced fluid of each well and the reservoir layer structural unit; the mapping relation forming unit is used for throwing each well to the ancient structural diagram of each key reservoir forming period in the single well classification scheme, and reversely pushing the oil gas reservoir forming process according to the main control fault of each well and the corresponding relation between the produced fluid of each well and the reservoir layer structural unit to form the mapping relation between the reservoir forming period and the single well drilling result in the oil gas reservoir forming process;
The oil gas exploration decision module: the method is used for further determining the area with oil gas development potential in the favorable trap distribution according to the mapping relation between the time of the reservoir formation and the drilling result of the single well in the oil gas reservoir formation process.
9. The analysis system of claim 8, wherein the data acquisition module further comprises a data cleansing sub-module: and cleaning the drilled well data, removing the disfavored well caused by engineering problems in the drilled well, and discarding the data of the disfavored well caused by engineering problems in the drilled well.
10. The analysis system of claim 8, wherein the classification scheme establishment module comprises:
the single well classification attribute distribution forms a sub-module: the method comprises the steps of analyzing production data in a first data set, determining an attribute according to which a single well classification scheme classifies as a classification attribute, and determining classification attribute distribution of each single well in the first data set;
the geologic background analysis parameters form a sub-module: the method comprises the steps of obtaining a hydrocarbon source rock position, a hydrocarbon generation history, a hydrocarbon discharge history and a main hydrocarbon accumulation period of a hydrocarbon reservoir of a target area to form geological background analysis parameters;
the classification scheme forms a sub-module: the method is used for optimizing the classification types and the classification standards in the single well classification scheme by adopting a parameter discriminant analysis method according to the matching condition of the classification attribute distribution of each single well and the geologic background analysis parameter based on the geologic background analysis parameter, and classifying each single well to form the single well classification scheme.
11. The analysis system of claim 8, wherein forming a single well classification scheme based on production data in the first dataset comprises: and completing the casting on the oil-gas-water separation trigonometric graph based on the productivity data in the first data set, and dividing the drilled well into a dry well, a gas well, a water well, an oil well and a gas-oil well according to the distribution condition of the casting points of each well on the oil-gas-water separation trigonometric graph.
12. The analysis system of claim 11, wherein the capacity data in the first dataset is based on pre-test capacity data in the first dataset.
13. The analysis system of any of claims 8, 10, 11 and 12, wherein forming a single well classification scheme based on production data in the first dataset is achieved by: and dividing the energy production data and/or the fluid geochemical parameter data by taking a single well as a minimum research unit and adopting an unsupervised machine learning algorithm to form a single well classification scheme.
14. The analysis system of claim 8, wherein the hydrocarbon exploration decision module further comprises:
a well position deployment submodule of the oil gas exploratory well: the method is used for further determining well position deployment of the next oil gas exploratory well in favorable trap distribution according to the mapping relation between the time of the oil gas reservoir formation and the drilling result of the single well.
15. A reservoir forming analysis device of a carbonate rock oil and gas reservoir comprises a processor and a memory; wherein, the liquid crystal display device comprises a liquid crystal display device,
a memory for storing a computer program;
a processor for implementing the steps of the carbonate reservoir analysis method of any one of claims 1 to 7 when executing a program stored on a memory.
16. A computer readable storage medium storing one or more programs executable by one or more processors to implement the steps of the carbonate reservoir formation analysis method of any one of claims 1-7.
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