US2026055699A1PendingUtilityA1
Shale gas well type classification method
Est. expiryAug 26, 2044(~18.1 yrs left)· nominal 20-yr term from priority
Inventors:HE XINYANGZHANG KUNYIN LEIJIANG SHULIN YANHUAZHANG YUNBOWANG XUEYINGNIU HULINLIU WEIWEICHENG SIHONGWan SongyangZhi TianyouWu DaiyuSONG YANJIANG ZHENXUEJIANG LINDING XIONGLIU PEISU JIECHEN YUXIANGZHANG YIQiao YitingLIU JIAYIPENG JUNLI BINLIU JINHUAZheng BinsongCHEN LEIYANG XUEFEIHAN FENGLITANG WEISHIRuan JingruGOU HENGFENGXIAO YIYANG ZILONGWANG SHOUQIANPENG YANCHENLI LINTAOLIU YIPENGLIU PING
E21B 43/00E21B 2200/22E21B 2200/20E21B 49/008G06Q 50/02G06F 18/2337G06F 18/2431
60
PatentIndex Score
0
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Claims
Abstract
A shale gas well type classification method includes: S1, acquiring raw data of evaluation parameters for stable production wells and trial production wells; S2, performing standardization on the raw data; S3, calculating distance coefficients; S4, classifying the stable production wells; S5, after determining a class number of the stable production wells, calculating comprehensive evaluation parameters S of the stable production wells based on standardized data; S6, for each class of the stable production wells, calculating average values of standardized data of the evaluation parameters for the stable production wells to construct a standard fuzzy set A, and constructing a to-be-identified fuzzy set B for each of the trial production wells, S7, calculating a closeness degree between each to-be-identified fuzzy set and each standard fuzzy set, and classifying a trial production well corresponding to the to-be-identified fuzzy set into a class of the stable production wells with a highest closeness degree.
Claims
exact text as granted — not AI-modifiedWhat is claimed is:
1 . A shale gas well type classification method, comprising the following steps:
S1, acquiring raw data of evaluation parameters for production wells and trial production wells, wherein the evaluation parameters comprise six parameters: an effective thickness, a gas saturation, a formation pressure, an open flow rate, a gas production per unit casing pressure drop, and a peak daily gas production; S2, performing standardization on the raw data of the evaluation parameters to obtain standardized data of the evaluation parameters for the production wells and the trial production wells; S3, calculating, based on the standardized data of the evaluation parameters for the production wells, a distance coefficient d ij between every two production wells of the production wells as per the following formula:
d
i
j
=
∑
k
=
1
u
(
x
i
k
-
x
j
k
)
2
,
i
,
j
=
1
,
2
,
3
,
…
,
m
where x ik represents a parameter value at an i-th row and a k-th column in the standardized data for the evaluation parameters of the production wells, x jk represents a parameter value at a j-th row and the k-th column in the standardized data for the evaluation parameters of the production wells, m represents a number of the production wells, and u represents a number of the evaluation parameters;
S4, classifying, based on a principle that a correlation between two wells will be stronger when a distance coefficient between the two wells becomes small, the production wells, comprising the following steps:
S41, sorting the distance coefficient between every two production wells of the production wells except for 0 in an ascending order to obtain sorted distance coefficients, merging two production wells of the production wells corresponding to a distance coefficient ranked first in the sorted distance coefficients into one class to form a first new entity to thereby obtain first-merged production wells comprising the first new entity and remaining production wells of the production wells for subsequent merging and classifying;
S42, merging two of the first-merged production wells corresponding to a distance coefficient ranked second in the sorted distance coefficients into one class to form a second new entity to thereby obtain second-merged production wells comprising the second new entity and remaining production wells of the first-merged production wells for subsequent merging and classifying; and
S43, performing, according to the above steps, a merging and classification operation on two of the second-merged production wells corresponding to a distance coefficient ranked third in the sorted distance coefficients, and repeating the merging and classification operation until a class number of the production wells is q as required for production, thereby stopping the merging and classification operation to obtain q classes of the production wells, where 1≤q≤m, and q and m are positive integers;
S5, after determining the class number of the production wells, calculating, based on the standardized data of the evaluation parameters for the production wells, comprehensive evaluation parameters S of the production wells, wherein each of the comprehensive evaluation parameters S is a sum of standardized values of the six evaluation parameters; and calculating an average value of the comprehensive evaluation parameters S of the production wells in each of the q classes, and designating the q classes of the production wells sequentially in a descending order of the average value of the comprehensive evaluation parameters S as Class I gas wells, Class II gas wells, Class III gas wells, . . . , Class q gas wells;
S6, for each of the q classes of the production wells, calculating average values of the standardized data of the evaluation parameters for the production wells to construct a standard fuzzy set A, thereby obtaining standard fuzzy sets A 1 , A 2 , A 3 , . . . ,A q , where A=(an average effective thickness value, an average gas saturation value, an average formation pressure value, an average open flow rate value, an average gas production value per unit casing pressure drop, an average peak daily gas production value); and for each of the trial production wells, calculating average values of the standardized data of the evaluation parameters for the trial production wells to construct a to-be-identified fuzzy set B, thereby obtaining to-be-identified fuzzy sets B 1 , B 2 , B 3 , . . . ,B n , where n represents a number of the trial production wells; and
S7, calculating a closeness degree between one of the to-be-identified fuzzy sets and each of the standard fuzzy sets, and classifying, based on a principle that a similarity between the standard fuzzy set and the to-be-identified fuzzy set will be higher when the closeness degree becomes greater, one of the trial production wells corresponding to the one of the to-be-identified fuzzy sets into one of the q classes of the production wells corresponding to a highest closeness degree, wherein a formula for calculating the closeness degree is expressed as follows:
σ
(
A
,
B
)
=
def
∑
k
=
1
z
[
A
(
x
c
)
∧
B
(
x
c
)
]
∑
k
=
1
z
[
A
(
x
c
)
∨
B
(
x
c
)
]
where σ(A,B) represents the closeness degree between A and B, A represents the standard fuzzy set, B represents the to-be-identified fuzzy set, z represents one of a total number of elements in the standard fuzzy set and a total number of elements in the to-be-identified fuzzy set, x c represents a c-th element of the elements in one of the standard fuzzy set and the to-be-identified fuzzy set, Λ represents taking an infimum between two elements respectively in the standard fuzzy set and the to-be-identified fuzzy set, and V represents taking a supremum between the two elements respectively in the standard fuzzy set and the to-be-identified fuzzy set.
2 . The shale gas well type classification method as claimed in claim 1 , wherein the step S4 comprises: during the merging and classification operation, for the distance coefficient d ij , merging one of the production wells corresponding to the i-th row with another one of the production wells corresponding to a j-th column into a same class, and removing a row and a column corresponding to a larger number between i and j; and then repeating the merging and classification operation on remaining data.
3 . The shale gas well type classification method as claimed in claim 1 , wherein the step S1 comprises: acquiring, based on geological data, the raw data for the effective thickness, the gas saturation and the formation pressure of the evaluation parameters, and acquiring, based on production data, the raw data for the open flow rate, the unit casing pressure drop gas production and the peak daily gas production of the evaluation parameters.
4 . The shale gas well type classification method as claimed in claim 3 , wherein in the step S1, the number of the production wells is at least 10.
5 . The shale gas well type classification method as claimed in claim 1 , wherein in the step S2, the standardization is performed as per the following formula:
Z
x
i
j
=
x
i
j
-
min
[
x
i
j
]
max
[
x
i
j
]
-
min
[
x
i
j
]
where Zx ij represents a standardized value at the i-th row and a j-th column, x ij represents a parameter value at the i-th row and the j-th column in the raw data, max [x ij ] represents a maximum value in the raw data, and min [x ij ] represents a minimum value in the raw data.
6 . The shale gas well type classification method as claimed in claim 1 , wherein the step S43 comprises: stopping the merging and classification operation when a distance coefficient ranked in the sorted distance coefficients reaches a maximum value satisfying d ij ≤0.100 to thereby obtain the q classes of the production wells.Join the waitlist — get patent alerts
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