A New Approach to a Fracturing Sweet Spot Evaluation Method Based on Combined Weight Coefficient Method—A Case Study in the BZ Oilfield, China
Abstract
:1. Introduction
2. Geological Settings
3. Analysis of Geology–Engineering Parameters
3.1. Geological Parameters Analysis
3.1.1. Study of the Reservoir’s Physical Property Parameters
3.1.2. Study of In Situ Stress
3.2. Engineering Factors Analysis
3.2.1. Study of the Brittle Index
3.2.2. Pump Rate
3.2.3. Fracturing Scale
4. Construction of Combinatorial Weight Evaluation Model
4.1. Standardized Processing of Raw Data
4.2. Model Construction
4.3. Construction of Combinatorial Weight Model
5. Result Analysis and Discussion
5.1. Application
5.2. Verification
6. Conclusions
- Based on combination weights, the most influential factors on post-frac production, are, successively, permeability, fracturing scale, slurry rate, horizontal principal stress difference, porosity, and brittleness index. The corresponding weight coefficients are 0.33, 0.25, 0.18, 0.16, 0.045 and 0.034.
- The geological factors have a greater impact on production than engineering factors.The average weight of geological factors is 0.18, while that of engineering factors is 0.15.
- There is a strong correlation between production and the dual sweet spot index Z which the correlation coefficient is 0.96. The anastomosis rate is 80% after comparing predicted and actual production from each well.
- To achieve better fracturing effects, it is recommended to select the fracturing spots in formations with good reservoir physical properties. Additionally, the fracturing treatment design should consider the limit of equipment and string performance while increasing fluid and sand volumes for optimal fracturing scale.
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Formation | Member | Bottom Depth (m) | Thickness (m) | Petrographic Summary |
---|---|---|---|---|
Shahejie | Sha 1 | 3717.0/3342.0 | 71.0/69.0 | It is a large set of gray mudstone segments. Two layers of phosphor siltstone are seen below. |
Sha 2 | 3797.0/3420.0 | 80.0/78.0 | Fluorescent fine sandstone and mudstone are interbedded with unequal thickness. | |
Sha 3 | 4134.0/3746.62 | 337.0/326.62 | Mudstone is interbedded with fine sandstone, fluorescent fine sandstone and fluorescent pebbly sandstone with varying thickness. |
Core Group | Lithology | Well | Depth (m) | Maximum Horizontal In Situ Stress (MPa) | Minimum Horizontal In Situ Stress (MPa) | Vertical Principal Stress (MPa) |
---|---|---|---|---|---|---|
1 | sandstone | BZ-B4 | 3725.75 | 67.2 | 58.4 | 86.8 |
2 | 3721.36 | 68.6 | 58.9 | 88.5 | ||
3 | 3738.03 | 69.4 | 59.1 | 89.3 | ||
4 | 3727.23 | 67.5 | 57.9 | 87.5 | ||
5 | 3728.15 | 67.4 | 58.5 | 87.7 | ||
6 | mudstone | 3648.12 | 69.2 | 58.9 | 85.6 | |
7 | 3650.21 | 68.3 | 58.4 | 85.5 | ||
8 | 3710.24 | 67.9 | 59.2 | 86.7 | ||
9 | 3700.54 | 68.4 | 58.7 | 86.1 | ||
10 | 3690.36 | 69.0 | 57.6 | 86.4 |
Influencing Factor | The Weight of Grey Correlation Method | Sort (From Large to Small) | |
---|---|---|---|
Geological factor | Permeability (mD) | 0.153671 | 2 |
Porosity (%) | 0.138636 | 6 | |
Horizontal in situ stress difference (MPa) | 0.140734 | 5 | |
Engineering factor | Brittleness index | 0.15 | 3 |
Slurry rate (m3/min) | 0.148776 | 4 | |
Fracturing scale | 0.268182 | 1 |
Importance Index | Representation | Importance Index | Representation |
---|---|---|---|
1 | Equally important | 1/3 | Slightly unimportant |
3 | Slightly important | 1/5 | Rather unimportant |
5 | Quite important | 1/7 | Obviously not important |
7 | Obvious importance | 1/9 | Absolutely not important |
9 | Absolutely importance | 1/2, 1/4, 1/6, 1/8 | The middle of two adjacent judgments |
2, 4, 6, 8 | The middle of two adjacent judgments | / | / |
Influencing Factor | The Weight of AHP | Sort (From Large to Small) | |
---|---|---|---|
Geological factor | Permeability (md) | 0.313063 | 1 |
Porosity (%) | 0.046778 | 5 | |
Horizontal in situ stress difference (MPa) | 0.162682 | 4 | |
Engineering factor | Brittleness index | 0.032744 | 6 |
Slurry rate (m3/min) | 0.175849 | 3 | |
Fracturing scale | 0.268884 | 2 |
Influencing Factor | Combined Weight | Sort (From Large to Small) | |
---|---|---|---|
Geological factor | Permeability (md) | 0.332922 | 1 |
Porosity (%) | 0.044813 | 5 | |
Horizontal in situ stress difference (MPa) | 0.158257 | 4 | |
Engineering factor | Brittleness index | 0.034051 | 6 |
Slurry rate (m3/min) | 0.18084 | 3 | |
Fracturing scale | 0.249118 | 2 |
Well | C13 | C37H | C38H | A22 | A4 |
---|---|---|---|---|---|
Comprehensive influencing factor Z | 0.3392 | 0.3681 | 0.349626 | 0.359932 | 0.232443 |
Actual production (m3/d) | 97 | 101 | 102 | 115 | 11 |
Well | Actual Production (m3/d) | Forecast Production (m3/d) | Error (%) | Satisfy or Not |
---|---|---|---|---|
C13 | 97 | 99.46969 | 2.55% | √ |
C37H | 101 | 107.0255 | 5.97% | × |
C38H | 102 | 103.0022 | 0.98% | √ |
A22 | 115 | 105.5992 | 8.17% | √ |
A4 | 11 | 10.9034 | 0.88% | √ |
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Jiang, M.; Peng, C.; Wu, J.; Wang, Z.; Liu, Y.; Zhao, B.; Zhang, Y. A New Approach to a Fracturing Sweet Spot Evaluation Method Based on Combined Weight Coefficient Method—A Case Study in the BZ Oilfield, China. Processes 2024, 12, 1830. https://doi.org/10.3390/pr12091830
Jiang M, Peng C, Wu J, Wang Z, Liu Y, Zhao B, Zhang Y. A New Approach to a Fracturing Sweet Spot Evaluation Method Based on Combined Weight Coefficient Method—A Case Study in the BZ Oilfield, China. Processes. 2024; 12(9):1830. https://doi.org/10.3390/pr12091830
Chicago/Turabian StyleJiang, Mao, Chengyong Peng, Jianshu Wu, Zongyong Wang, Yi Liu, Bingjin Zhao, and Yan Zhang. 2024. "A New Approach to a Fracturing Sweet Spot Evaluation Method Based on Combined Weight Coefficient Method—A Case Study in the BZ Oilfield, China" Processes 12, no. 9: 1830. https://doi.org/10.3390/pr12091830