Quantitative prediction method for gas content of deep marine shale

Patent metadata

Field	Value
Publication number	US-12338732-B2
Application number	US-202418918078-A
Country	US
Kind code	B2
Filing date	Oct 17, 2024
Priority date	Oct 24, 2023
Publication date	Jun 24, 2025
Grant date	Jun 24, 2025

Abstract

A quantitative prediction method for gas content of deep marine shale includes: obtaining raw data of known wells; establishing relationship formulas between pore specific surface areas and adsorbed gas contents of a known well in an area as an adsorbed gas content quantitative prediction model; establishing relationship formulas between pore volumes and free gas contents of the known well as a free gas content quantitative prediction model; summing the adsorbed gas contents and corresponding free gas contents to obtain total gas contents; calculating adsorbed gas contents, free gas contents and total gas contents of the known wells; drawing a predicted adsorbed gas content contour map, a predicted free gas content contour map and a predicted total gas content contour map; and reading an adsorbed gas content, a free gas content and a total gas content of an unknown well in the area from the above contour maps.

First claim

What is claimed is:

1. A quantitative prediction method for shale gas content, comprising:
S1, obtaining raw data; wherein the raw data comprises adsorbed gas contents, a free gas contents, pore specific surface areas and pore volumes of shale samples at different sampling depths of a known well in an area; and a depth difference between two adjacent sampling depths h i-1 and h i of the different sampling depths is 10 m, i≥2, and i is a natural number;
S2, establishing, based on the raw data, relationship formulas between the pore specific surface areas and the adsorbed gas contents of the known well as an adsorbed gas content quantitative prediction model; wherein the step S2 comprises:
S21, expressing the pore specific surface areas as x, and expressing the adsorbed gas contents as y, to form a first discrete series [x i , y i ]; wherein x i represents a pore specific surface area of a shale sample at an i th sampling depth h i of the known well, and y i represents an adsorbed gas content of the shale sample at the i th sampling depth h i of the known well;
S22, obtaining linear equations of straight lines passing through every two adjacent points (x i-1 , y i-1 ) and (x i , y i ) as adsorbed gas content prediction formulas corresponding to different burial depths; wherein the step S22 specifically comprises:
(1) expressing a first linear equation of a first straight line passing through two points (x 1 , y 1 ) and (x 2 , y 2 ) as y−y 1 =k 1 (x−x 1 ), substituting the two points (x 1 , y 1 ) and (x 2 , y 2 ) into the first linear equation y−y 1 =k 1 (x−x 1 ) to obtain a first slope k 1 , and obtaining the first linear equation of the first straight line passing through the two points (x 1 , y 1 ) and (x 2 , y 2 ) based on the first slope, expressed as a formula 1 as follows:

y
=

k
1

(

x
-

x
1

)

+

y
1

;

(

formula
⁢

1

)

 wherein the formula 1 is an adsorbed gas content prediction formula corresponding to a first burial depth range of h 1 to h 2 ;
(2) expressing a second linear equation of a second straight line passing through two points (x 2 , y 2 ) and (x 3 , y 3 ) as y−y 2 =k 2 (x−x 2 ), substituting the two points (x 2 , y 2 ) and (x 3 , y 3 ) into the second linear equation y−y 2 =k 2 (x−x 2 ) to obtain a second slope k 2 , and obtaining the second linear equation of the second straight line passing through the two points (x 2 , y 2 ) and (x 3 , y 3 ) based on the second slope, expressed as a formula 2 as follows:

y
=

k
2

(

x
-

x
2

)

+

y
2

;

(

formula
⁢

2

)

 wherein the formula 2 is an adsorbed gas content prediction formula corresponding to a second burial depth range of h 2 to h 3 ;
(3) expressing a third linear equation of a third straight line passing through two points (x 3 , y 3 ) and (x 4 , y 4 ) as y−y 3 =k 3 (x−x 3 ), substituting the two points (x 3 , y 3 ) and (x 4 , y 4 ) into the third linear equation y−y 3 =k 3 (x−x 3 ) to obtain a third slope k 3 , and obtaining the third linear equation of the third straight line passing through the two points (x 3 , y 3 ) and (x 4 , y 4 ) based on the third slope, expressed as a formula 3 as follows:

y
=

k
3

(

x
-

x
3

)

+

y
3

;

(

formula
⁢

3

)

 wherein the formula 3 is an adsorbed gas content prediction formula corresponding to a third burial depth range of h 3 to h 4 ; and
(4) expressing a (i−1) th linear equation of a (i−1) th straight line passing through every two adjacent points (x i-1 , y i-1 ) and (x, y i ) as y−y i-1 =k i-1 (x−x i-1 ), wherein i≥5, substituting the two points (x i-1 , y i-1 ) and (x i , y i ) into the (i−1) th linear equation y−y i-1 =k i-1 (x−x i-1 ) to obtain a (i−1) th slope k i-1 , and obtaining the (i−1) th linear equation of the (i−1) th straight line passing through the two adjacent points (x i-1 , y i-1 ) and (x i , y i ) based on the (i−1) th slope, expressed as follows:

y
=

k

i

Assignees

• Univ Southwest Petroleum
• Sinopec Southwest Petroleum Bureau Co Ltd
• Petrochina Zhejiang Oilfield Company

Inventors

• He Xinyang
• Zhang Kun
• Niu Hulin
• Jia Chengzao
• Song Yan
• Jiang Zhenxue
• Jiang Shu
• Wang Xueying
• Zhang Nanxi
• Dong Xiaoxia
• Dong Jun
• Li Ruisong
• Wang Tong
• Huang Pu
• Ouyang Jiasui
• Wang Xingmeng
• Xu Shoucheng
• Zhang Hanbing
• Ji Yubing
• Chen Lei
• Yang Xuefei
• Han Fengli
• Tang Weishi
• Ruan Jingru
• Gou Hengfeng
• Li Lintao
• Liu Yipeng
• Liu Ping

Classifications

• E21B2200/22

  Fuzzy logic, artificial intelligence, neural networks or the like · CPC title

• G01N15/0886

  Mercury porosimetry · CPC title

• G01N15/0893

  by measuring weight or volume of sorbed fluid, e.g. B.E.T. method · CPC title

• G01N15/088

  Investigating volume, surface area, size or distribution of pores; Porosimetry · CPC title

• G01N7/04

  by absorption or adsorption alone · CPC title