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Method for identification and abundance prediction of coalbed methane reservoirs

A technology for abundance prediction and reservoir identification, applied in the field of oil and gas geophysical exploration

Active Publication Date: 2015-04-15
BC P INC CHINA NAT PETROLEUM CORP +1
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Problems solved by technology

Moreover, there is no literature so far that has published a variety of geophysical logging data, combined with laboratory test data for the calculation of reservoir gas content, reservoir identification and abundance prediction

Method used

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  • Method for identification and abundance prediction of coalbed methane reservoirs
  • Method for identification and abundance prediction of coalbed methane reservoirs
  • Method for identification and abundance prediction of coalbed methane reservoirs

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Embodiment Construction

[0064] According to the special petrophysical properties of the coal seam and the unique storage method of coal bed gas, the present invention utilizes the change law of the coal seam on the conventional logging data, eliminates the influence of geological factors such as buried depth and lithology on the logging data, and conducts coal seam gas near the wellbore. Division of gas-bearing layers. Combined with the test results of the gas content in the laboratory, the gas content of the coal seam is semi-quantitatively predicted by using the multiple linear regression analysis method, and a more objective and relatively accurate gas content evaluation method is provided for the exploration of coal bed methane.

[0065] The specific embodiment of the present invention is:

[0066] 1) Drill wells and collect conventional geophysical logging data in the wells; logging data include well diameter, acoustic time difference, spontaneous potential, density, resistivity and natural gamm...

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Abstract

The invention discloses a method for identification and abundance prediction of coalbed methane reservoirs by using comprehensive logging data of gas exploration of unconventional gas reservoirs; the method comprises the steps: reading the depth and thickness of a special lithologic stratum on a rock core and deleting the stratum section with the corresponding depth on a logging curve; calculating the logging data in a working zone to obtain the mean value and the variance of the physical property data of a coalbed, establishing a multi-parameter abundance prediction formula for the coalbed methane after being subjected to standardization treatment, and obtaining a stratum gas content changing curve; and performing the identification and abundance prediction of the coalbed methane reservoirs according to the stratum gas content changing curve. The method is simple and easy in operation, low in cost and high in operating efficiency; the thin coalbeds can be identified accurately and the abundance prediction results of reservoirs of coalbed methane are reliable.

Description

technical field [0001] The invention relates to oil and gas geophysical exploration technology, belongs to the field of gas exploration and development of unconventional gas reservoirs, and is a method for identifying and predicting the abundance of coalbed gas reservoirs by comprehensive logging data. Background technique [0002] At present, the development of coalbed methane industry has gradually entered the stage of commercialization, and has become an important direction of unconventional gas reservoir exploration. Coalbed methane, commonly known as "gas", also known as "coalbed methane" or "coalbed gas", refers to the natural gas mainly composed of methane that is generated by biochemistry and pyrolysis during the formation and evolution of coal and stored in coalbeds. The occurrence state of coalbed methane is mainly in the adsorption state, which is very unique. It is quite different from the storage mechanism of natural gas in conventional reservoirs, and its influ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): E21B49/00
CPCE21B49/00
Inventor 张红英孙鹏远钱忠平赵剑马光凯万忠宏
Owner BC P INC CHINA NAT PETROLEUM CORP
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