CN-121995520-A - Inter-coal oil-bearing reservoir prediction method, inter-coal oil-bearing reservoir prediction device, medium and computing equipment

CN121995520ACN 121995520 ACN121995520 ACN 121995520ACN-121995520-A

Abstract

The invention relates to the technical field of petroleum exploration, and discloses a method, a device, a medium and computing equipment for predicting an inter-coal oil-bearing reservoir. The method comprises the steps of carrying out single well curve characteristic analysis, carrying out qualitative analysis on curves of sound waves, resistivity, porosity and natural potential to determine characteristics of an oil-containing reservoir, carrying out quantitative analysis on density and gamma curves, carrying out curve fitting, optimizing fitted curves to eliminate coal seam influence, establishing a favorable reservoir indication curve and a sound wave time difference intersection map, carrying out quantitative analysis on the oil-containing reservoir, dividing oil-containing reservoir intervals to distinguish the oil-containing reservoir, carrying out well shock calibration, establishing an initial model of the oil-containing reservoir of the coal removal layer based on the favorable reservoir indication curve, carrying out oil-containing reservoir prediction based on the initial model of the oil-containing reservoir of the coal removal layer, and drawing a plan view and a section view of the oil-containing reservoir. The method eliminates the influence of coal beds, improves the applicability to the oil-bearing reservoirs among the coals, and is convenient for accurately predicting the distribution condition of the oil-bearing reservoirs.

Inventors

YU SHAOHUI
ZHOU LIANG
WANG JING
Madina Mawuti Khan
LIU YONG
JIANG TAO
Zhi Wendong
CHEN FANGHONG
ZHANG XIAOHONG
Dan Shunhua
WANG SHICHANG
WANG ZE

Assignees

中国石油天然气股份有限公司

Dates

Publication Date: 20260508
Application Date: 20241107

Claims (9)

1. A method for predicting an inter-coal oil-bearing reservoir, the method comprising: step S10, carrying out single well curve characteristic analysis, carrying out qualitative analysis on curves of sound waves, resistivity, porosity and natural potential, and determining characteristics of an oil-containing reservoir; s20, carrying out quantitative analysis on the density and gamma curves and carrying out curve fitting; step S30, optimizing a fitting curve to eliminate the influence of a coal seam; Step S40, establishing an advantageous reservoir indication curve and a sound wave time difference intersection chart, quantitatively analyzing the oil-containing reservoirs, and dividing oil-containing reservoir intervals to distinguish the oil-containing reservoirs; S50, performing well shock calibration, and establishing an initial model of the coalbed-removed oil-bearing reservoir based on the favorable reservoir indication curve; And step S60, based on the initial model of the coalbed-removed oil-bearing reservoir, carrying out oil-bearing reservoir prediction, and drawing a plan view and a section view of the oil-bearing reservoir.
2. The method for predicting an oil-bearing reservoir between coals according to claim 1, characterized in that said step S10 includes: Step S110, acquiring data and carrying out single well curve characteristic analysis; Step S120, carrying out qualitative analysis on sound waves, resistivity, porosity and natural potential; Step S130, determining the oil-bearing reservoir characteristics.
3. The method for predicting an oil-bearing reservoir between coals according to claim 1, characterized by comprising the following step S20: Step S210, aiming at the problem of density distortion of the oil-containing reservoir among coals, based on response conditions of the indication curve of the favorable reservoir, acquiring a sensitive curve of which the density and gamma accord with characteristics of the oil-containing reservoir; step S220, quantitatively analyzing the density and gamma curve; step S230, curve fitting is performed.
4. A method for predicting an oil-bearing reservoir between coals as claimed in claim 3, characterized by the step S230 comprising: Step S2301, normalizing and fitting a logging curve, and converting a gamma curve into density dimension gamma; step S2302, performing curve fitting based on the following formula: oil-containing curve value n=a density curve+b density dimension gamma Wherein a and b are weight values, which are mainly determined by data statistical analysis, a plate is built by using the analysis porosity of the core of the research area and the gamma values of density and density dimension respectively, a slope k 1 is determined by fitting a relation between the porosity and density, a slope k 2 is determined by fitting a relation between the porosity and the gamma values of density dimension, a and b are calculated by the slopes, wherein a=k 1 /(k 1 +k 2 ),b=k 2 /(k 1 +k 2 ), and a+b=1.
5. The method for predicting an oil-bearing reservoir between coals according to claim 1, characterized by the step S40 comprising: Step S410, based on drilling oil test data, establishing an advantageous reservoir indication curve and a sound wave time difference intersection map; Step S420, quantitatively analyzing the oil-bearing reservoir based on the favorable reservoir indication curve and the sound wave time difference intersection map; step S430, dividing the oil-bearing reservoir interval by quantitative analysis results to distinguish the oil-bearing reservoir.
6. The method for predicting an oil-bearing reservoir between coals according to claim 1, characterized by the step S50 comprising: Step S510, performing well shock calibration; and step S520, establishing an initial model of the oil-bearing reservoir of the coal removal layer based on the beneficial reservoir indication curve.
7. An inter-coal oil reservoir prediction apparatus, comprising: the analysis module is used for carrying out single well curve characteristic analysis, carrying out qualitative analysis on curves of sound waves, resistivity, porosity and natural potential, and determining the characteristics of the oil-containing reservoir; the curve fitting module is used for carrying out quantitative analysis on the density and gamma curve and carrying out curve fitting; the optimizing module is used for optimizing the fitting curve and eliminating the influence of the coal seam; The oil-containing reservoir distinguishing module is used for establishing an advantageous reservoir indication curve and a sound wave time difference intersection graph, quantitatively analyzing the oil-containing reservoir and dividing oil-containing reservoir intervals so as to distinguish the oil-containing reservoir; the model building module is used for performing well earthquake calibration and building an initial model of the oil-bearing reservoir of the coal removal layer based on the favorable reservoir indication curve; And the drawing module is used for carrying out oil reservoir prediction based on the initial model of the coalbed-removed oil reservoir and drawing a plan view and a section view of the oil reservoir.
8. A computer readable storage medium comprising instructions which, when run on a computer, cause the computer to perform the inter-coal oil reservoir prediction method of any one of claims 1 to 6.
9. A computing device, the computing device comprising: At least one processor, memory, and input output unit; Wherein the memory is configured to store a computer program and the processor is configured to invoke the computer program stored in the memory to perform the inter-coal oil reservoir prediction method of any of claims 1-6.

Description

Inter-coal oil-bearing reservoir prediction method, inter-coal oil-bearing reservoir prediction device, medium and computing equipment Technical Field The invention relates to the technical field of petroleum exploration, in particular to a method, a device, a medium and computing equipment for predicting an inter-coal oil reservoir. Background The domestic land clastic rock oil-gas exploration is gradually changed from the structural oil-gas exploration to the lithology oil-gas exploration, and is changed from the conventional oil-gas exploration to the hidden oil-gas exploration or the unconventional oil-gas exploration. The oil-bearing reservoir prediction research is extremely important in the oil-gas exploration process, and the accurate prediction of the oil-bearing reservoir distribution is of great significance in improving the exploration success rate. The coal-line stratum mainly comprises a plurality of rock types such as coal seams, sandstone layers and the like, wherein sandstone between the coal seams is a good reservoir, and is an important field of petroleum exploration. However, the coal-based stratum has complex deposition sequence, changeable lithology and large physical property difference between the coal seam and surrounding rock. The common development carbon chip strips in the oil-containing reservoir and the development carbon mudstone in the mudstone have low density, have great influence on the density curve, and lead the conventional density-sound wave intersection graph to be unable to distinguish the oil-containing reservoir. Meanwhile, the low-speed and low-density characteristics of the coal bed can lead to energy attenuation and speed reduction of seismic waves. The reliability and accuracy of the prediction of the oil-bearing reservoir between coals are reduced by the two factors, the requirement of oil-gas exploration work under the complex geological conditions at present cannot be met, and the depiction of favorable targets and the progress of oil-gas exploration are restricted. At present, oil and gas exploration is mainly carried out by adopting a method which is firstly a well logging-earthquake multi-attribute density curve reconstruction inversion technology and application, wherein the method is used for carrying out inversion on an oil-bearing reservoir by fusing attribute information with higher weight through a convolution factor method by applying conventional well logging data and earthquake attribute information which is not influenced by non-stratum factors to reconstruct a density curve, secondly a coal-based stratum tight gas thin oil-bearing reservoir earthquake prediction method is used for carrying out forward sand oil-bearing reservoir earthquake response change through a one-dimensional model and carrying out 'phase control inversion' by adopting a two-dimensional forward implementation sand earthquake response recognition mode, thirdly a coal-based stratum tight oil-bearing reservoir step-by-step prediction method based on neural network characteristic attributes is used for mainly applying wavelet decomposition and reconstruction to remove coal beds, and distinguishing sandstone (oil-bearing reservoir) from coal bed and mudstone (non-oil-bearing reservoir) by utilizing neutron well logging attributes to improve the identification precision of the tight sandstone oil-bearing reservoir. However, the above methods do not eliminate the influence of the coal bed, have poor applicability to the reservoir between coals, and cannot further distinguish the gas layer, the gas-water layer and the water layer, so that the oil-containing reservoir between coals cannot be accurately predicted. Disclosure of Invention The invention mainly aims to provide a method, a device, a medium and computing equipment for predicting an inter-coal oil-bearing reservoir, and aims to solve the technical problems that the applicability of the prior art to the inter-coal oil-bearing reservoir is poor and the inter-coal oil-bearing reservoir cannot be accurately predicted. The method comprises the steps of S10, conducting single well curve characteristic analysis, conducting qualitative analysis on curves of sound waves, resistivity, porosity and natural potential, determining oil-bearing reservoir characteristics, S20, conducting quantitative analysis on density and gamma curves, conducting curve fitting, S30, optimizing fitted curves, eliminating coal seam influence, S40, establishing an advantageous reservoir indication curve and a sound wave time difference intersection map, conducting quantitative analysis on oil-bearing reservoirs, dividing oil-bearing reservoir intervals to distinguish oil-bearing reservoirs, S50, conducting well shock calibration, establishing an initial model of the coal-bearing layer based on the advantageous reservoir indication curve, S60, conducting oil-bearing reservoir prediction based on the initial model of the coal-bearing layer, and drawing an oi