US2016145994A1PendingUtilityA1
Evaluation Method and Evaluation Device for Water Breakthrough Risk of Production Wells in Aquifer Drive Gas Reservoirs
Est. expiryNov 20, 2034(~8.3 yrs left)· nominal 20-yr term from priority
E21B 2200/22E21B 49/00E21B 44/00G06Q 50/06E21B 47/00G06Q 10/0635E21B 41/00
34
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Claims
Abstract
The present invention provides an evaluation method and an evaluation device for water breakthrough risk of gas wells in gas reservoirs with aquifers, the method comprising the following steps: building evaluation factors that influence water breakthrough risk of gas wells in gas reservoirs with aquifers; acquiring weight vectors of the evaluation factors based on an analytic hierarchy process; building a fuzzy relationship matrix between the water breakthrough risk of gas wells in gas reservoirs with aquifers and its evaluation factors; and synthesizing the fuzzy relationship matrix and the weight vectors according to a weighted average fuzzy synthesis operator, to acquire a comprehensive evaluation result of water breakthrough risk of gas wells in gas reservoirs with aquifers. The present invention improves the accuracy of the evaluation result of water breakthrough risk of the gas wells, and is able to obtain an evaluation result that is more consistent with the case of actual water breakthrough of gas wells in gas reservoirs with aquifers.
Claims
exact text as granted — not AI-modified1 . An evaluation method for water breakthrough risk of gas wells in gas reservoirs with aquifers, comprising:
building evaluation factors that influence water breakthrough risk of gas wells in gas reservoirs with aquifers; acquiring weight vectors of the evaluation factors based on an analytic hierarchy process; building a fuzzy relationship matrix between the water breakthrough risk of gas wells in gas reservoirs with aquifers and its evaluation factors; and synthesizing the fuzzy relationship matrix and the weight vectors according to a weighted average fuzzy synthesis operator, to acquire a comprehensive evaluation result of water breakthrough risk of gas wells in gas reservoirs with aquifers.
2 . The evaluation method for evaluating water breakthrough risk of gas wells in gas reservoirs with aquifers according to claim 1 , characterized in that, the evaluation factors that influence water breakthrough risk of gas wells in gas reservoirs with aquifers include the following features of gas wells in gas reservoirs with aquifers:
structure and sedimentary facies features, including structure and trap feature, fracture feature, fracture development condition and rock type and sedimentary facies; reservoir features, including interlayer feature, reservoir type, sand body connectivity and reservoir heterogeneity; drilling and completion information, including drilling quality, cementing quality and distance between a perforation and the edge-bottom water; production performance and monitoring data, including gas production profile testing result, saturation logging result and transient well testing analysis result; and dynamic evaluation and prediction result, including production rate and pressure variation characteristics, production rate transient analysis result, reserve controlled by a single well, water coning critical production rate and water breakthrough time prediction result.
3 . The evaluation method for water breakthrough risk of gas wells in gas reservoirs with aquifers according to claim 1 , characterized in that, the acquiring weight vectors of the evaluation factors based on an analytic hierarchy process specifically comprises:
performing pairwise comparison among the evaluation factors under the same hierarchy to obtain a quantized judgment matrix M;
M
=
(
m
11
m
12
…
m
1
j
m
21
m
22
…
m
2
j
⋮
⋮
⋮
⋮
m
i
1
m
i
2
…
m
ij
)
wherein, m ij represents the weight of an evaluation factor i to an evaluation factor j;
calculating the largest eigenvalue λ max of the judgment matrix M and corresponding feature vector, the feature vector being weight coefficient distribution of the evaluation factors under the same hierarchy;
performing consistency verification on the feature vector;
if the feature vector goes through the consistency verification, calculating a product Q i of each row of elements of the judgment matrix M, wherein
Q
i
=
∏
j
=
1
n
m
ij
;
calculating a n-th root
ω
_
i
=
Q
i
n
of Q i to acquire a vector ω =[ ω 1 ω 2 . . . ω n ], performing a normalization process to the vector to obtain the weight vector of the evaluation factors.
4 . The evaluation method for evaluating water breakthrough risk of gas wells in gas reservoirs with aquifers according to claim 1 , characterized in that, the fuzzy relationship matrix between the water breakthrough risk of gas wells in gas reservoirs with aquifers and its evaluation factors is:
R
=
[
R
|
u
1
R
|
u
1
…
R
|
u
p
]
=
[
r
11
r
12
…
r
1
m
r
21
r
22
…
r
2
m
⋮
⋮
⋮
⋮
r
p
1
r
p
2
…
r
pm
]
p
,
m
wherein, in the fuzzy relationship matrix, the element r pm in row p column m represents a degree of membership of water breakthrough risk of gas wells in gas reservoirs with aquifers as for the feature vector from the aspect of the evaluation factor u p .
5 . The evaluation method for evaluating water breakthrough risk of gas wells in gas reservoirs with aquifers. according to claim 1 , characterized in that, the synthesizing the fuzzy relationship matrix and the weight vectors according to a weighted average fuzzy synthesis operator specifically comprises:
according to the formula
b
i
=
∑
i
=
1
p
(
a
i
·
r
ij
)
=
min
(
1
,
∑
i
=
1
p
a
i
·
r
ij
)
,
j
=
1
,
2
,
…
,
m
,
synthesizing the fuzzy relationship matrix and the weight vectors;
wherein, b i , a i , r ij represent a degree of membership belonging to the jth level, a weight of the ith evaluation factor, and a degree of membership that the ith evaluation factor belongs to the jth level, respectively.
6 . An evaluation device for water breakthrough risk of gas wells in gas reservoirs with aquifers, comprising:
an evaluation factor building module for building evaluation factors that influence water breakthrough risk of gas wells in gas reservoirs with aquifers; a weight vector acquisition module for acquiring weight vectors of the evaluation factors based on an analytic hierarchy process; a fuzzy matrix building module for building a fuzzy relationship matrix between the water breakthrough risk of gas wells in gas reservoirs with aquifers and its evaluation factors; a matrix and vector synthesizing module for synthesizing the fuzzy relationship matrix and the weight vectors according to a weighted average fuzzy synthesis operator, to acquire a comprehensive evaluation result of water breakthrough risk of gas wells in gas reservoirs with aquifers.
7 . The evaluation device for evaluating water breakthrough risk of gas wells in gas reservoirs with aquifers according to claim 6 , characterized in that, the evaluation factors that influence water breakthrough risk of gas wells in gas reservoirs with aquifers include the following features of gas wells in gas reservoirs with aquifers:
structure and sedimentary facies features, including structure and trap feature, fracture feature, fracture development condition and rock type and sedimentary facies; reservoir features, including interlayer feature, reservoir type, sand body connectivity and reservoir heterogeneity; drilling and completion information, including drilling quality, cementing quality and distance between a perforation and the edge-bottom water; production performance and monitoring data, including gas production profile testing result, saturation logging result and transient well testing analysis result; dynamic evaluation and prediction result, including production rate and pressure variation characteristics, production rate transient analysis result, reserve controlled by a single well, water coning critical production rate and water breakthrough time prediction result.
8 . The evaluation device for water breakthrough risk of gas wells in gas reservoirs with aquifers according to claim 6 , characterized in that, the acquiring weight vectors of the evaluation factors based on an analytic hierarchy process specifically comprises:
performing pairwise comparison among the evaluation factors under the same hierarchy to obtain a quantized judgment matrix M;
M
=
(
m
11
m
12
…
m
1
j
m
21
m
22
…
m
2
j
⋮
⋮
⋮
⋮
m
i
1
m
i
2
…
m
ij
)
wherein, m ij represents the weight of an evaluation factor i to an evaluation factor j;
calculating the largest eigenvalue λ max of the judgment matrix M and corresponding feature vector, the feature vector being weight coefficient distribution of the evaluation factors under the same hierarchy;
performing consistency verification on the feature vector;
if the feature vector goes through the consistency verification, calculating a product Q i of each row of elements of the judgment matrix M, wherein
Q
i
=
∏
j
=
1
n
m
ij
;
calculating a n-th root
ω
_
i
=
Q
i
n
of Q i to acquire a vector ω =[ ω 1 ω 2 . . . ω n ], performing a normalization process to the vector to obtain the weight vector of the evaluation factors.
9 . The evaluation device for evaluating water breakthrough risk of gas wells in gas reservoirs with aquifers according to claim 6 , characterized in that, the fuzzy relationship matrix between the water breakthrough risk of gas wells in gas reservoirs with aquifers and its evaluation factors is:
R
=
[
R
|
u
1
R
|
u
1
…
R
|
u
p
]
=
[
r
11
r
12
…
r
1
m
r
21
r
22
…
r
2
m
⋮
⋮
⋮
⋮
r
p
1
r
p
2
…
r
pm
]
p
,
m
wherein, in the fuzzy relationship matrix R, the element r pm in row p column m represents a degree of membership of water breakthrough risk of gas wells in gas reservoirs with aquifers as for the feature vector from the aspect of the evaluation factor u p .
10 . The evaluation device for evaluating water breakthrough risk of gas wells in gas reservoirs with aquifers according to claim 6 , characterized in that, the synthesizing the fuzzy relationship matrix and the weight vectors according to a weighted average fuzzy synthesis operator specifically comprises:
according to the formula
b
i
=
∑
i
=
1
p
(
a
i
·
r
ij
)
=
min
(
1
,
∑
i
=
1
p
a
i
·
r
ij
)
,
j
=
1
,
2
,
…
,
m
,
synthesizing the fuzzy relationship matrix and the weight vectors;
wherein, b i , a i , r ij represent a degree of membership belonging to the jth level, a weight of the ith evaluation factor, and a degree of membership that the ith evaluation factor belongs to the jth level, respectively.Join the waitlist — get patent alerts
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