4D QUANTITATIVE AND INTELLIGENT DIAGNOSIS METHOD AND SYSTEM FOR SPATIO-TEMPORAL EVOLUTION OF OIL-GAS RESERVOIR DAMAGE TYPES AND EXTENT
The invention relates to the technical field of oilfield exploration, and discloses a 4D quantitative and intelligent diagnosis method and system for spatio-temporal evolution of oil-gas reservoir damage types and extent. The method includes: determining a characteristic parameter characterizing res...
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Main Authors | , , , , , , , , , , , , , , , , , , , , |
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Format | Patent |
Language | English |
Published |
26.01.2023
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Subjects | |
Online Access | Get full text |
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Summary: | The invention relates to the technical field of oilfield exploration, and discloses a 4D quantitative and intelligent diagnosis method and system for spatio-temporal evolution of oil-gas reservoir damage types and extent. The method includes: determining a characteristic parameter characterizing reservoir damage by each of a plurality of factors based on a spatio-temporal evolution simulation equation of reservoir damage by each of the plurality of factors; and determining an effective characteristic parameter characterizing the damage extent of the reservoir based on the characteristic parameter characterizing reservoir damage rby each of the plurality of factors. The invention can quantitatively simulate the characteristic parameters of reservoir damage caused by the various factors and a total characteristic parameter of the reservoir damage. Therefore for a well without reservoir damage, performing quantitative prediction of reservoir damage and spatio-temporal deduction of damage laws is of scientific guidance significance for preventing reservoir damage, and formulating development plans for oil pools and subsequent well stimulation measures, and for a well with reservoir damage, also performing quantitative diagnosis of reservoir damage and spatio-temporal deduction of damage laws achieves optimal design of a declogging measure and improvement or restoration of oil-gas well production and water well injection capacity. |
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Bibliography: | Application Number: US202217864224 |