A Stratigraphic Prediction Method Based on Machine Learning
Abstract
:1. Introduction
2. Geostratigraphic Series Simulation Method Based on Machine Learning
2.1. Geostratigraphic Series
2.2. Stratum Data Reconstruction Schemes Based on Machine Learning
2.2.1. Stratum Data Normalization
2.2.2. Drilling Data Segmentation and Equalization
2.2.3. Geostratigraphic Series Filling
2.2.4. Stratum Coding Based on One-Hot Encoding
2.3. Geostratigraphic Series Simulation Based on a Recurrent Neural Network
2.3.1. Establishment of the Sequence Model of the Stratum Type
2.3.2. Establishment of the Series Model of the Stratum Thickness
2.3.3. Establishment of the Geostratigraphic Series Modeling
2.4. Evaluation Method of Stratum Type Series Simulation
- Replace the first “silt” with “sand”;
- Insert “miscellaneous fill” at the beginning of t1;
- Remove the last “clay”;
- Delete the final “silt”.
3. Results and Discussions
3.1. Study of the Regional Geology and Data Reconstruction Schemes
3.2. Machine Learning Simulation Result Analysis
- class CrossLoss(nn.Module):
- def __init__(self,ignore_index = 0):
- super(CrossLoss, self).__init__()
- self.ignore_index = ignore_index
- self.criterion = nn.CrossEntropyLoss(ignore_index = 0)
- def forward(self, input, target):
- ind = (target ! = self.ignore_index).float()
- num_all = torch.sum(ind).data[0]
- #print(target)
- size0 = target.size(0)
- size1 = target.size(1)
- temp = target.cpu().data
- for i in range(size0):
- for j in range(size1):
- temp[i,j] = depthLabel(temp[i,j])
- pred = torch.mul(input,ind).long()
- temp = temp.long()
- loss = self.criterion(pred, temp)
- return loss, num_all
- CPU: Intel Core i7-4790k @ 4.00GHz quad-core;
- Memory: 32 GB;
- VGA card: Nvidia GeForce GTX 770(2GB).
3.2.1. Training and Verification of the Stratum Type Series Model
3.2.2. Training and Verification of the Stratum Thickness Series Model
3.2.3. Verification of the Geostratigraphic Series Model
3.3. Three-Dimensional Geological Modeling and Testing
3.3.1. Three-Dimensional Geological Modeling
3.3.2. Three-Dimensional Geological Model Verification
3.4. Evaluation of 3D Geological Modeling Based on the Geostratigraphic Series Model
4. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Stratum Types | Number | Coding Vector |
---|---|---|
clay | 0 | (1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0) |
silt | 1 | (0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0) |
plain fill | 2 | (0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0) |
miscellaneous fill | 3 | (0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0) |
silty sand | 4 | (0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0) |
silty clay | 5 | (0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0) |
mucky soil | 6 | (0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0) |
mucky clay | 7 | (0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0) |
old city fill | 8 | (0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0) |
clay sand inclusion | 9 | (0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0) |
mud | 10 | (0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0) |
medium sand | 11 | (0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0) |
intermediate fine sand | 12 | (0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0) |
start mark | 13 | (0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0) |
end mark | 14 | (0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1) |
Round Number | 50 | 500 |
---|---|---|
Loss value | 0.483226 | 0.374167 |
Cumulative decline | 0.327009 | 0.436068 |
Cumulative decline | 40.36% | 53.82% |
Expert Ratio | 0 | 1/3 | 1/2 | 2/3 | 1 |
---|---|---|---|---|---|
Maximum value | 61.42% | 63.83% | 64.82% | 63.40% | 64.82% |
Steady value | 59.86% | 60.00% | 62.41% | 61.13% | 60.42% |
Expert Ratio | 0 | 1/3 | 1/2 | 2/3 | 1 | |
---|---|---|---|---|---|---|
Edit Distance = 0 | Maximum value | 37.2% | 39.6% | 39.2% | 39.6% | 36.4% |
Steady value | 35.2% | 38% | 38.4% | 38.4% | 35.6% | |
Edit Distance <= 1 | Maximum value | 76% | 77.2% | 76.4% | 77.2% | 76.4% |
Steady value | 74% | 75.6% | 75.6% | 75.6% | 73.6% |
Expert Ratio | 0 | 1/3 | 1/2 | 2/3 | 1 |
---|---|---|---|---|---|
Maximum value | 71.85% | 73.60% | 73.95% | 73.98% | 72.51% |
Steady value | 70.91% | 72.64% | 73.57% | 73.09% | 71.68% |
Stratum Thickness Interval | Layer Thickness Type Coding Number | Coded Vector |
---|---|---|
<3 m | 0 | [1, 0, 0, 0, 0, 0, 0] |
3–5 m | 1 | [0, 1, 0, 0, 0, 0, 0] |
5–10 m | 2 | [0, 0, 1, 0, 0, 0, 0] |
10–20 m | 3 | [0, 0, 0, 1, 0, 0, 0] |
20–30 m | 4 | [0, 0, 0, 0, 1, 0, 0] |
>30 m | 5 | [0, 0, 0, 0, 0, 1, 0] |
initiation mark | 6 | [0, 0, 0, 0, 0, 0, 1] |
Expert Ratio | 0 | 1/3 | 1/2 | 2/3 | 1 |
---|---|---|---|---|---|
Maximum value | 65.07% | 73.05% | 80.08% | 75.60% | 70.07% |
Steady value | 63.53% | 70.07% | 75.05% | 72.62% | 67.94% |
Number | The Real Borehole Strata | Prediction Results of Machine Learning | ||
---|---|---|---|---|
Stratum Type Sequence | Stratum Thickness Sequence (m) | Stratum Type Sequence | Stratum Thickness Sequence (m) | |
1 | silt, clay | 0.3, 3.9 | floury soil, clay, plain fill | within 3 m, within 3 m, 3–5 m |
2 | clay | 2 | clay | within 3 m |
3 | miscellaneous fill | 0.6 | plain fill | 5–10 m |
4 | plain fill, clay | 3.1, 9.8 | plain fill, clay | within 3 m, 5–10 m |
5 | miscellaneous fill, clay, mucky soil, plain fill, clay | 1.2, 1.3, 1.5, 2.4, 13.3 | miscellaneous fill, plain fill, mucky soil, plain fill, clay | within 3 m, within 3 m, within 3 m, within 3 m, 10–20 m |
6 | floury soil, silty clay, plain fill, clay, plain fill, clay | 1.0, 0.5, 2.5, 1.2, 0.3, 3.6 | floury soil, plain fill, clay, plain fill, clay | within 3 m, within 3 m, within 3 m, within 3 m 5–10 m |
7 | miscellaneous fill, plain fill, clay | 0.7, 3.0, 4.5 | miscellaneous fill, plain fill, clay | within 3 m, within 3 m, 3–5 m |
8 | miscellaneous fill, clay | 0.6, 4.0 | miscellaneous fill | within 3 m |
9 | miscellaneous fill, plain fill, clay | 0.5, 1.0, 11.9 | miscellaneous fill, plain fill, clay | within 3 m, within 3 m, 10–20 m |
10 | miscellaneous fill, clay | 1.0, 9.8 | miscellaneous fill, clay | within 3 m, 5–10 m |
11 | miscellaneous fill, silt, plain fill, clay | 4.1, 11.2, 7.0, 10.0 | miscellaneous fill, plain fill, clay | within 3 m, 10–20 m, 5–10 m |
12 | floury soil, plain fill, mucky soil, clay | 0.5, 6.7, 1.2, 8.6 | floury soil, plain fill, plain fill, clay | within 3 m, within 3 m, within 3 m, 5–10 m |
13 | silt, clay | 0.4, 6.6 | floury soil, clay | within 3 m, 5–10 m |
14 | silt, clay | 0.4, 10.4 | floury soil, clay | within 3 m, 5–10 m |
15 | miscellaneous fill, silt, plain fill, clay | 0.7, 1.9, 3.4, 24.0 | miscellaneous fill, floury soil, plain fill, clay | within 3 m, within 3 m, within 3 m, 20–30 m |
16 | miscellaneous fill soil, plain fill soil, old city miscellaneous fill soil, clay | 1.2, 2.6, 6.5, 13.0 | miscellaneous fill, floury soil, plain fill, old town fill, clay | within 3 m, within 3 m, within 3 m, 5–10 m, 10–20 m |
17 | miscellaneous fill soil, plain fill soil, clay | 0.5, 2.8, 10.2 | miscellaneous fill, plain fill, clay | within 3 m, within 3 m, 10–20 m |
18 | miscellaneous fill soil, plain fill soil, clay | 2.1, 0.8, 12.9 | miscellaneous fill, plain fill, clay | within 3 m, within 3 m, 10–20 m, |
Stratum Type Accuracy | Average Sequence Similarity | Stratum Thickness Accuracy |
---|---|---|
62.98% | 72.16% | 74.04% |
Number | The Real Borehole Strata | Prediction Results of 3D Geological Modeling | ||
---|---|---|---|---|
Stratum Type Sequence | Stratum Thickness Sequence (m) | Stratum Type Sequence | Stratum Thickness Sequence (m) | |
1 | silt, clay | 0.3, 3.9 | clay, silt | 0.3, 3.9 |
2 | clay | 2 | miscellaneous fill | 2.0 |
3 | miscellaneous fill | 0.6 | miscellaneous fill | 0.6 |
4 | plain fill, clay | 3.1, 9.8 | miscellaneous fill | 13.5 |
5 | miscellaneous fill, clay, mucky soil, plain fill, clay | 1.2, 1.3, 1.5, 2.4, 13.3 | miscellaneous fill, clay, mucky soil, silt | 1.2, 1.3, 3.9, 13.3 |
6 | floury soil, silty clay, plain fill, clay, plain fill, clay | 1.0, 0.5, 2.5, 1.2, 0.3, 3.6 | plain fill, silt clay, silt, clay, silt | 1, 0.5, 2.5, 1.2, 3.9 |
7 | miscellaneous fill, plain fill, clay | 0.7, 3.0, 4.5 | miscellaneous fill, silt | 0.7, 8.5 |
8 | miscellaneous fill, clay | 0.6, 4.0 | miscellaneous fill | 4.6 |
9 | miscellaneous fill, plain fill, clay | 0.5, 1.0, 11.9 | miscellaneous fill, silt | 0.5, 0.5 |
10 | miscellaneous fill, clay | 1.0, 9.8 | miscellaneous fill | 12.2 |
11 | miscellaneous fill, silt, plain fill, clay | 4.1, 11.2, 7.0, 10.0 | miscellaneous fill, silt | 2.8, 25.2 |
12 | floury soil, plain fill, mucky soil, clay | 0.5, 6.7, 1.2, 8.6 | plain fill, silt | 0.5, 16.5 |
13 | silt, clay | 0.4, 6.6 | plain fill | 7 |
14 | silt, clay | 0.4, 10.4 | plain fill | 10.9 |
15 | miscellaneous fill, silt, plain fill, clay | 0.7, 1.9, 3.4, 24.0 | miscellaneous fill, plain fill, silt, silt | 0.7, 1.9, 3.4, 24 |
16 | miscellaneous fill soil, plain fill soil, old city miscellaneous fill soil, clay | 1.2, 2.6, 6.5, 13.0 | miscellaneous fill, plain fill, old city miscellaneous fill soil | 1.2, 2.6, 22.5 |
17 | miscellaneous fill soil, plain fill soil, clay | 0.5, 2.8, 10.2 | miscellaneous fill, plain fill | 0.5, 13 |
18 | miscellaneous fill soil, plain fill soil, clay | 2.1, 0.8, 12.9 | miscellaneous fill, silt, clay | 2.1, 0.8, 12.9 |
Stratum Type Accuracy | Average Sequence Similarity | Stratum Thickness Accuracy |
---|---|---|
30.78% | 32.27% | 64.52% |
Test Borehole Data | Three-Dimensional Geological Model | |
---|---|---|
Average reliability | 0.6293 | 0.3205 |
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Share and Cite
Zhou, C.; Ouyang, J.; Ming, W.; Zhang, G.; Du, Z.; Liu, Z. A Stratigraphic Prediction Method Based on Machine Learning. Appl. Sci. 2019, 9, 3553. https://doi.org/10.3390/app9173553
Zhou C, Ouyang J, Ming W, Zhang G, Du Z, Liu Z. A Stratigraphic Prediction Method Based on Machine Learning. Applied Sciences. 2019; 9(17):3553. https://doi.org/10.3390/app9173553
Chicago/Turabian StyleZhou, Cuiying, Jinwu Ouyang, Weihua Ming, Guohao Zhang, Zichun Du, and Zhen Liu. 2019. "A Stratigraphic Prediction Method Based on Machine Learning" Applied Sciences 9, no. 17: 3553. https://doi.org/10.3390/app9173553