NL2030500B1 - System and method for dynamically predicting carbon dioxide geological storage potential - Google Patents
System and method for dynamically predicting carbon dioxide geological storage potential Download PDFInfo
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- CURLTUGMZLYLDI-UHFFFAOYSA-N Carbon dioxide Chemical compound O=C=O CURLTUGMZLYLDI-UHFFFAOYSA-N 0.000 title claims abstract description 187
- 238000003860 storage Methods 0.000 title claims abstract description 113
- 229910002092 carbon dioxide Inorganic materials 0.000 title claims abstract description 92
- 239000001569 carbon dioxide Substances 0.000 title claims abstract description 92
- 238000000034 method Methods 0.000 title claims abstract description 28
- 230000003068 static effect Effects 0.000 claims abstract description 56
- 238000002347 injection Methods 0.000 claims abstract description 33
- 239000007924 injection Substances 0.000 claims abstract description 33
- 238000012937 correction Methods 0.000 claims abstract description 4
- 238000000605 extraction Methods 0.000 claims abstract description 4
- 239000000126 substance Substances 0.000 claims description 20
- 238000004458 analytical method Methods 0.000 claims description 9
- OKTJSMMVPCPJKN-UHFFFAOYSA-N Carbon Chemical compound [C] OKTJSMMVPCPJKN-UHFFFAOYSA-N 0.000 claims description 8
- 230000015572 biosynthetic process Effects 0.000 claims description 8
- 229910052799 carbon Inorganic materials 0.000 claims description 8
- 238000011084 recovery Methods 0.000 claims description 4
- 230000007704 transition Effects 0.000 claims description 4
- 230000004927 fusion Effects 0.000 claims description 3
- 238000000491 multivariate analysis Methods 0.000 claims description 3
- 239000011159 matrix material Substances 0.000 claims description 2
- 238000012517 data analytics Methods 0.000 claims 1
- 229960004424 carbon dioxide Drugs 0.000 description 71
- 238000011156 evaluation Methods 0.000 description 30
- 229940090044 injection Drugs 0.000 description 27
- 239000004215 Carbon black (E152) Substances 0.000 description 10
- 239000003245 coal Substances 0.000 description 10
- 229930195733 hydrocarbon Natural products 0.000 description 10
- 150000002430 hydrocarbons Chemical class 0.000 description 10
- FAPWRFPIFSIZLT-UHFFFAOYSA-M Sodium chloride Chemical compound [Na+].[Cl-] FAPWRFPIFSIZLT-UHFFFAOYSA-M 0.000 description 9
- 239000011780 sodium chloride Substances 0.000 description 9
- 239000011435 rock Substances 0.000 description 7
- 101710099060 Tectonic Proteins 0.000 description 6
- 238000005755 formation reaction Methods 0.000 description 6
- 230000000694 effects Effects 0.000 description 4
- 230000004044 response Effects 0.000 description 4
- 230000008878 coupling Effects 0.000 description 3
- 238000010168 coupling process Methods 0.000 description 3
- 238000005859 coupling reaction Methods 0.000 description 3
- 230000014759 maintenance of location Effects 0.000 description 3
- 230000003334 potential effect Effects 0.000 description 3
- 230000008569 process Effects 0.000 description 3
- 239000000243 solution Substances 0.000 description 3
- 238000004364 calculation method Methods 0.000 description 2
- 238000010276 construction Methods 0.000 description 2
- 238000007405 data analysis Methods 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 229910052500 inorganic mineral Inorganic materials 0.000 description 2
- 230000007246 mechanism Effects 0.000 description 2
- 239000011707 mineral Substances 0.000 description 2
- 101100345589 Mus musculus Mical1 gene Proteins 0.000 description 1
- 238000013459 approach Methods 0.000 description 1
- 229910002090 carbon oxide Inorganic materials 0.000 description 1
- 238000001311 chemical methods and process Methods 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000009792 diffusion process Methods 0.000 description 1
- 238000004090 dissolution Methods 0.000 description 1
- 238000005243 fluidization Methods 0.000 description 1
- 239000008398 formation water Substances 0.000 description 1
- 239000007788 liquid Substances 0.000 description 1
- 238000010297 mechanical methods and process Methods 0.000 description 1
- 230000005226 mechanical processes and functions Effects 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 238000005457 optimization Methods 0.000 description 1
- 230000035699 permeability Effects 0.000 description 1
- 230000000704 physical effect Effects 0.000 description 1
- 230000000750 progressive effect Effects 0.000 description 1
- 230000035945 sensitivity Effects 0.000 description 1
- 239000007787 solid Substances 0.000 description 1
- 230000009897 systematic effect Effects 0.000 description 1
- 239000002699 waste material Substances 0.000 description 1
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/02—Agriculture; Fishing; Forestry; Mining
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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
- E21B2200/00—Special features related to earth drilling for obtaining oil, gas or water
- E21B2200/20—Computer models or simulations, e.g. for reservoirs under production, drill bits
-
- 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
- E21B41/00—Equipment or details not covered by groups E21B15/00 - E21B40/00
- E21B41/005—Waste disposal systems
- E21B41/0057—Disposal of a fluid by injection into a subterranean formation
- E21B41/0064—Carbon dioxide sequestration
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Abstract
The invention relates to a system. and method for dynamically predicting carbon dioxide geological storage potential. The system includes an index acquisition module for acquiring static indexes and dynamic indexes; a key index extraction module for extracting key static indexes among static indexes and key dynamic indexes among dynamic indexes; a static storage potential determination module for determining different grades of static storage potential of carbon dioxide geological storage sites using key static indexes prior to carbon dioxide injection; a calibration and correction module for calibrating and correcting key dynamic indexes after carbon dioxide injection; a potential threshold determination module for determining different grades of dynamic storage potential of carbon dioxide geological storage sites in three types of reservoirs using calibrated and corrected key dynamic indexes and determining potential threshold values; and a dynamic storage potential prediction module for dynamically predicting storage potential of carbon dioxide geological storage sites.
Description
P980/NLpd
SYSTEM AND METHOD FOR DYNAMICALLY PREDICTING CARBON DIOXIDE
GEOLOGICAL STORAGE POTENTIAL
The present disclosure relates to the field of geclogical storage of carbon dioxide, and particularly to a system and method for dynamically predicting carbon dioxide geological storage po- tential.
Some innovative achievements have been made in evaluation on prediction and presumption of region-grade and basin-grade carbon dioxide geological storage potential. However, existing methods for predicting the region-grade and basin-grade carbon dioxide ge- ological storage potential lacks theoretical support, and do not involve accurate evaluation indexes of multi-scale three- dimensional engineering geological structures and hydrogeclogical structures. At the same time, exiting evaluation indexes of carbon dioxide geological storage potential include static evaluation in- dexes only, and do not include dynamic evaluation indexes of the multi-field coupling and feedback as well as space-time evaluation of multi-scale structures and multiphase substances in physical, chemical and mechanical processes. Moreover, systematic methods for predicting the region-grade control potential, field-grade basic reservoir and injection-grade engineering reservoir of tar- get carbon dioxide geological storage sites are not found yet, so that it fails to predict different grades (from the basin grade to the injection grade) of three types of reservoirs (saline aquifer, hydrocarbon reservoir and coal seam).
Therefore, existing evaluation indexes of the carbon dioxide geological storage potential remain inaccurate and cannot be used for prediction of the carbon dioxide geological storage potential, evaluation of geological appropriateness and site selection. It is urgent to develop a method for dynamically predicting different grades (from the basin grade to the injection grade) of carbon di-
oxide geological storage potential of three types of reservoirs (saline aquifer, hydrocarbon reservoir and coal seam). The method needs to combine static indexes of the multi-scale three- dimensional engineering geological structures and hydrogeclogical structure of storage sites and dynamic indexes of the multi-scale geological structures responding to carbon dioxide injection. The method also needs to provide a scientific basis for study on sys- tematically theoretical methods for geological appropriateness evaluation and selection of carbon dioxide storage sites.
An objective of the present disclosure provides a system and method for dynamically predicting carbon dioxide geological stor- age potential to improve the prediction accuracy of the carbon di- oxide geological storage potential.
To achieve the above objective, the present disclosure pro- vides the following solution:
A system for dynamically predicting carbon dioxide geological storage potential includes: an index acquisition module, configured to acquire static in- dexes and dynamic indexes; a key index extraction module, configured to extract key static indexes among static indexes and key dynamic indexes among dynamic indexes; a static storage potential determination module, configured to determine different grades of static storage potential of car- bon dioxide geological storage sites using key static indexes pri- or to carbon dioxide injection; a calibration and correction module, configured to calibrate and correct key dynamic indexes after carbon dioxide injection; a potential threshold determination module, configured to de- termine different grades of dynamic storage potential of carbon dioxide geological storage sites in three types of reservoirs us- ing calibrated and corrected key dynamic indexes, and to determine potential threshold values; and a dynamic storage potential prediction module, configured to predict different grades of dynamic storage potential of carbon dioxide geological storage sites in three types of reservoirs us- ing a big data prediction and analysis model and using the poten- tial threshold values as constraints.
Based on the above system in the present disclosure, the pre- sent disclosure further provides a method for dynamically predict- ing carbon dioxide geological storage potential, including: acquiring static indexes and dynamic indexes; extracting key static indexes among static indexes and key dynamic indexes among dynamic indexes; determining different grades of static storage potential of carbon dioxide geological storage sites using key static indexes prior to carbon dioxide injection; calibrating and correcting key dynamic indexes after carbon dioxide injection; determining different grades of dynamic storage potential of carbon dioxide geological storage sites in three types of reser- voirs using calibrated and corrected key dynamic indexes, and de- termining potential threshold values; and predicting different grades of dynamic storage potential of carbon dioxide geological storage sites in three types of reser- voirs using a big data prediction and analysis model under the constraint of the potential threshold values.
According to specific embodiments provided by the present disclosure, the present disclosure discloses the following tech- nical effects.
According to the above-mentioned system and method provided by the present disclosure, based on the multi-scale three- dimensional geological structures and their physical, chemical and mechanical parameters of response to disturbance during carbon di- oxide injection, and after consideration of the space-time effect, the present disclosure provides a dynamic evaluation index system of different grades (from the basin grade to the injection grade) of carbon dioxide geological storage potential of three types of reservoirs (saline aquifer, hydrocarbon reservoir and coal seam) and a method for dynamically predicting the storage potential. The present disclosure greatly improves previous study only on static evaluation index system of region-grade and basin-grade carbon di-
oxide geological storage potential and the static prediction meth- od, fully considers response of the multi-scale geological struc- tures to disturbance in the construction and running stages of the carbon dioxide geological storage process and disturbance during carbon dioxide injection. The index system is complete, and the prediction method is advanced. The present disclosure apparently improves the prediction accuracy of the carbon dioxide geological storage prediction.
To more clearly describe the technical solution of the embod- iment of the present disclosure or the prior art, accompanying drawings used in the embodiments are simply described below. It is apparent that the accompanying drawings described below are merely some embodiments of the present disclosure. Other drawings may further be obtained by those of ordinary skill in the art accord- ing to these drawings without creative work.
FIG. 1 is a schematic structural diagram of a system for dy- namically predicting carbon dioxide geological storage potential according to the present disclosure;
FIG. 2 is a flowchart of a method for dynamically predicting carbon dioxide geological storage potential according to the pre- sent disclosure.
The technical solution in the embodiments of the present dis- closure will be described clearly and completely with reference to accompanying drawings in the embodiments of the present disclo- sure. It is apparent that the described embodiments are not all but part of embodiments of the present disclosure. Based on the embodiments in the present disclosure, all other embodiments ob- tained by those ordinarily skilled in the art without creative la- bor should fall within the scope of protection of the present dis- closure.
An objective of the present disclosure provides a system and method for dynamically predicting carbon dioxide geological stor- age potential to improve the prediction accuracy of the carbon di-
oxide geological storage potential.
To facilitate understanding of the above objects, features and advantages of the present disclosure, the present disclosure is described in further detail below with reference to the accom- 5 panying drawings and specific embodiments.
FIG. 1 is a schematic structural diagram of a system for dy- namically predicting carbon dioxide geological storage potential according to Embodiment 1 of the present disclosure. A shown in
FIG. 1, the system includes: an index acquisition module 201, configured to acquire static indexes and dynamic indexes, wherein the static indexes include: carbon dioxide density parameters, recovery factor parameters, tectonic parameters, tectonic evolution parameters, ground motion parameters, formation lithology parameters, sedimentary phase transition parameters, physical, chemical and mechanical parame- ters of a geologic structure, temperature field parameters, seep- age field parameters and formation pressure parameters; the dynamic indexes include: physical, chemical and mechani- cal parameters of multiphase substances such as a supercritical carbon dioxide-water-oil-gas-rock matrix-fracture system, and dy- namic space-time evolution parameters thereof; a key index extraction module 202, configured to extract key static indexes among static indexes and key dynamic indexes among dynamic indexes; a static storage potential determination module 203, config- ured to determine different grades of static storage potential of carbon dioxide geological storage sites using key static indexes prior to carbon dioxide injection; a calibration and correction module 204, configured to cali- brate and correct key dynamic indexes after carbon dioxide injec- tion; a potential threshold determination module 205, configured to determine different grades of dynamic storage potential of carbon dioxide geological storage sites in three types of reservoirs us- ing calibrated and corrected key dynamic indexes, and to determine potential threshold values; and a dynamic storage potential prediction module 206, configured to predict different grades of dynamic storage potential of carbon dioxide geological storage sites in three types of reservoirs us- ing a big data prediction and analysis model under the constraint of the potential threshold values.
In this embodiment, the key static indexes are extracted by a method, for example, multivariate statistics, hierarchical analy- sis, multi-source heterogeneous data fusion or big data analysis.
As shown in FIG. 2, the method includes.
At step 101, static indexes and dynamic indexes are acquired.
At step 102, key static indexes among static indexes and key dynamic indexes among dynamic indexes are extracted.
At step 103, different grades of static storage potential of carbon dioxide geological storage sites are determined by using key static indexes prior to carbon dioxide injection.
At step 104, key dynamic indexes are calibrated and corrected after carbon dioxide injection.
At step 105, different grades of dynamic storage potential of carbon dioxide geological storage sites in three types of reser- voirs is determined by using calibrated and corrected key dynamic indexes, and potential threshold values are determined; and
At step 106, different grades of dynamic storage potential of carbon dioxide geological storage sites in three types of reser- voirs is predicted by using a big data prediction and analysis model under the constraint of the potential threshold values.
The method provided by the present disclosure is approximate- ly divided into two parts:
First, key static indexes and key dynamic indexes are deter- mined to form dynamic evaluation index systems of different grades of carbon dioxide geological storage potential.
Static evaluation indexes include: carbon dioxide density pa- rameters, recovery factor parameters, tectonic parameters, tecton- ic evolution parameters, ground motion parameters, formation 1li- thology parameters, sedimentary phase transition parameters, phys- ical, chemical and mechanical parameters of a geologic structure, temperature field parameters, seepage field parameters and for- mation pressure parameters.
Dynamic evaluation indexes include: physical, chemical and mechanical parameters of multiphase substances such as a super- critical carbon dioxide-water-oil-gas-rock matrix-fracture system, and dynamic space-time evolution thereof.
Aiming at different grades (from a basin grade to an injec- tion grade) of multi-scale three-dimensional geological structures and multiphase substances, and after consideration of carbon diox- ide geological storage sites in three types of reservoirs (saline aquifer, hydrocarbon reservoir and coal seam), background static evaluation indexes are concluded, including carbon dioxide density parameters, recovery factor parameters, tectonic parameters, tec- tonic evolution parameters, ground motion parameters, formation lithology parameters, sedimentary phase transition parameters, physical, chemical and mechanical parameters of a geologic struc- ture, temperature field parameters, seepage field parameters, for- mation pressure parameters, etc.
Taking the multi-scale structures and multiphase substances of the storage sites of the injection grade as an example, dynamic evaluation indexes of the space-time evolution thereof under the effect of multi-field coupling are taken into comprehensive con- sideration, including: physical, chemical and mechanical parame- ters of multiphase substances such as a supercritical carbon diox- ide-water-oil-gas-rock matrix-fracture system, and space-time evo- lution parameters thereof.
Possible evaluation parameter indexes are classified and sorted according to tectonic structures and carbon dioxide storage mechanisms, such as hydrodynamic storage, constraining storage, dissolution storage and mineral storage of different types of res- ervoirs, and carbon dioxide storage objectives of different types of reservoirs, for example, carbon dioxide in original formation water reaches saturation, a reservoir pressure of a waste oil-gas field recovers to an original reservoir pressure, and the reser- voir pressure approaches a breakthrough pressure of cap rock. With reference to geological evaluation index data of domestic and overseas typical demonstration projects of carbon oxide storage, and according to models of multi-scale three-dimensional geologi- cal structures and hydrogeological structures, evaluation on the sensitivity of the static evaluation index parameters of carbon dioxide geological storage sites of different grades (from a basin grade to an injection grade) and in three types (saline aquifer, hydrocarbon reservoir and coal seam) and selection of key static evaluation indexes (matrix, fracture, fault and network systems thereof) are implemented, on the basis of a reliability theory and an optimization theory using methods of multivariate statistics, hierarchical analysis, multi-source heterogeneous data fusion and big data analysis. Key dynamic evaluation indexes are extracted according to response laws of the multi-scale geological struc- tures under disturbance during carbon dioxide injection, wherein the key dynamic evaluation indexes include physical indexes (po- rosity parameters, permeability parameters, diffusion coefficient parameters, capillary force relation parameters, etc.), chemical indexes (mineral component parameters, fluidization parameters, etc.), and mechanical indexes {deformation parameters, strength parameters, etc.). The key dynamic evaluation indexes and the pre- viously selected key static evaluation indexes are used together to establish the dynamic evaluation index systems of carbon diox- ide geological storage potential.
Second, different grades of carbon dioxide geological storage potential are predicted according to the key indexes obtained in the first part, and a method for dynamically predicting of differ- ent grades of carbon dioxide geological storage potential is es- tablished.
On the basis of study on transparency characteristics of the multi-scale three-dimensional engineering geological structures and hydrogeological structures and the response laws of multi- scale geological structures under disturbance during carbon diox- ide injection, and after comprehensive consideration of the evalu- ation objectives of the carbon dioxide geological storage poten- tial, storage demand, geological safety and other factors, differ- ent grades (from the basin grade to the injection grade) of the carbon dioxide geological storage potential of three types of res- ervoirs (saline aquifer, hydrocarbon reservoir and coal seam) is evaluated in a progressive principle from the project planning and design stages (prior to carbon dioxide injection) to projection construction and running stages (after carbon dioxide injection).
The specific steps are as follows:
1) Prior to carbon dioxide injection, calculation principles of the region-grade control potential, field-grade basic reser- voir, injection-grade engineering reservoirs of target carbon di-
oxide geological storage sites in three types of reservoirs (sa- line aquifer, hydrocarbon reservoir and coal seam) are established and calculation methods involving key static evaluation indexes are proposed on the basis of the models of the multi-scale three- dimensional engineering geological structures and hydrogeological structures, the consideration of stability of the regional tecton- ic structures, physical characteristics, storage safety, etc. of a reservoir-cap rock “storage box” system, etc., and according to the carbon dioxide storage mechanisms and objectives of the three types of reservoirs (saline aquifer, hydrocarbon reservoir and coal seam), to evaluate different grades (from the basic grade to the injection grade) of static storage potential of carbon dioxide geological storage sites.
2) After carbon dioxide injection, with consideration of the coupling, feedback and space-time evolution laws of rock of the reservoir-cap rock “storage box” system under the effect of multi- ple fields (temperature field, seepage field, stress field and chemical field), multiphase state (gas state, liquid stage, solid state, etc.) and multiple processes (physical, chemical and me- chanical processes), the dynamic evaluation index system of carbon dioxide geological storage potential is diagnosed, and calibrated and corrected one more time using a big data diagnosing and ana- lyzing model on the basis of a great amount of dynamic monitoring feedback data.
By means of circulating update and iteration, the corrected dynamic evaluation index system of carbon dioxide geo-
logical storage potential is used to re-evaluate the static stor- age potential of the carbon dioxide geological storage sites, de- termine different grades (from the basin grade to the injection grade) of dynamic storage potential of carbon dioxide storage sites in three types of reservoirs (saline aquifer, hydrocarbon reservoir and coal seam), determine the potential threshold val- ues, wherein the threshold values represent the storage potential scope of the carbon dioxide storage sites, namely the maximum storage potential and the minimum storage potential.
A method for dynamically predicting different grades (from the basin grade to the injection grade) of carbon dioxide geological storage poten- tial of three types of reservoirs (saline aquifer, hydrocarbon reservoir and coal seam) is finally achieved using a big data pre- dicting and analyzing model and using the geological storage po- tential threshold values as calibrated values and constrained val- ues.
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