Pressure diagnostics in hydraulic fracturing for unconventional completion optimization
Abstract
The accurate evaluation of hydraulic fracturing performance is essential for the iterative optimization of unconventional reservoir development. In this aspect, fracturing pressure diagnostics has been recognized as a non-invasive technique that significantly reduces operational time and cost. However, pressure-based diagnostics lack a unified workflow for the evaluation of fracture complexity and area and cannot provide sufficient guidance for design optimization. Thus, this paper proposes an integrated diagnostic framework, constructed by pressure interpretation and data mining, from which the hydraulic fracture complexity and fracture area can be quantified. The normalized fracture complexity index is defined by propagation events and energy intensity extracted from wavelet-transformed pressure signals, and the fracture area is evaluated from pressure falloff analysis. Data mining is then used to optimize the fracturing parameters based on these two indices. The results show that the proposed framework effectively characterizes the stimulated fracture area and complexity and reveals their relationships with fracturing parameters and geological factors on the basis of multi-stage data from three horizontal coalbed methane wells. The stimulated fracture area is primarily determined by the fracturing fluid volume and pumping rate, while the fracture complexity is strongly regulated by the pumping rate and compressive strength of the rock. A negative correlation was detected between the fracture complexity and the main fracture area. To balance the main area and complexity of fractures, it is necessary to optimize the key fracturing parameters. This study provides a low-cost tool that can diagnose hydraulic fracturing performance and effectively optimize unconventional completion.
Document Type: Original article
Cited as: Wei, Z., Sheng, M., Li, J., Zhang, B., Wang, B., Li, G. Pressure diagnostics in hydraulic fracturing for unconventional completion optimization. Advances in Geo-Energy Research, 2025, 17(3): 196-211. https://doi.org/10.46690/ager.2025.09.03
Keywords:
Fracture diagnostics, pressure analysis, completion optimization, unconventional reservoirs, hydraulic fracturingReferences
Afagwu, C., Mahmoud, M., Alafnan, S., et al. Multiscale storage and transport modeling in unconventional shale gas: A review. Journal of Petroleum Science and Engineering, 2022, 208: 109518.
Akbari, A., Karami, A., Kazemzadeh, Y., et al. Evaluation of hydraulic fracturing using machine learning. Scientific Reports, 2025, 15(1): 26926.
Anikiev, D., Birnie, C., Waheed, U., et al. Machine learning in microseismic monitoring. Earth-Science Reviews, 2023, 239: 104371.
Childers, D., Wu, X. Fracture diagnostic technologies with process workflow for implementation. Journal of Petroleum Science and Engineering, 2022, 208: 109778.
Cui, Q., Zhao, Y., Zhang, L., et al. A semianalytical model of fractured horizontal well with hydraulic fracture network in shale gas reservoir for pressure transient analysis. Advances in Geo-Energy Research, 2023, 8(3): 193-205.
Dewinter, J. C., Gosling, S. D., Potter, J. Comparing the Pearson and Spearman correlation coefficients across distributions and sample sizes: A tutorial using simulations and empirical data. Psychological Methods, 2016, 21(3): 273-290.
Ekechukwu, G. K., Sharma, J. Well-scale demonstration of distributed pressure sensing using fiber-optic DAS and DTS. Scientific Reports, 2021, 11(1): 12505.
Eltaleb, I., Soliman, M. Y., Ali, S. F., et al. Estimation of permeability from pump-in/flowback tests: An afterclosure analysis approach. Fuel, 2025, 381: 133020.
Eyinla, D., Henderson, S. K., Emadi, H., et al. Optimization of hydraulic fracture monitoring approach: A perspective on integrated fiber optics and sonic tools. Geoenergy Science and Engineering, 2023, 231: 212441.
Hazlett, R., Farooq, U., Babu, D. A. A complement to decline curve analysis. SPE Journal, 2021, 26(4): 2468-2478.
Hu, X., Huang, G., Zhou, F., et al. Pressure response using wavelet analysis in the process of hydraulic fracturing: Numerical simulation and field case. Journal of Petroleum Science and Engineering, 2022, 217: 110837.
Hu, X., Tu, Z., Zhou, F., et al. A hydraulic fracture geometry inversion model based on distributed-acoustic-sensing data. SPE Journal, 2023a, 28(3): 1560-1576.
Hu, S., Sheng, M., Shi, S., et al. Optimization of fracturing stages/clusters in horizontal well based on unsupervised clustering of bottomhole mechanical specific energy on the bit. Natural Gas Industry B, 2023b, 10(6): 583-590.
Hudson, T., Baird, A., Kendall, J., et al. Distributed acoustic sensing (DAS) for natural microseismicity studies: A case study from Antarctica. Journal of Geophysical Research: Solid Earth, 2021, 126(7): e2020JB02149.
Ishibashi, T., Asanuma, H., Mukuhira, Y., et al. Laboratory hydraulic shearing of granitic fractures with surface roughness under stress states of EGS: Permeability changes and energy balance. International Journal of Rock Mechanics and Mining Sciences, 2023, 170: 105512.
Lei, Q., Weng, D., Guan, B., et al. A novel approach of tight oil reservoirs stimulation based on fracture controlling optimization and design. Petroleum Exploration and Development, 2020, 47(3): 632-641.
Li, M., Magsipoc, E., Abdelaziz, A., et al. Mapping fracture complexity of fractured shale in laboratory: Three-dimensional reconstruction from serial-section images. Rock Mechanics and Rock Engineering, 2022a, 55(5): 2937-2948.
Li, G., Song, X., Tian, S., et al. Intelligent drilling and completion: A review. Engineering, 2022b, 18: 33-48.
Liu, G., Ehlig-Economides, C. Practical considerations for diagnostic fracture injection test (DFIT) analysis. Journal of Petroleum Science and Engineering, 2018, 171: 1133-1140.
Liu, G., Ehlig-Economides, C. Comprehensive before-closure model and analysis for fracture calibration injection falloff test. Journal of Petroleum Science and Engineering, 2019, 172: 911-933.
Liu, L., Guo, X., Wang, X., et al. Integrated wellbore-reservoir-geomechanics modeling for enhanced interpretation of distributed fiber-optic strain sensing data in hydraulic-fracture analysis. Journal of Rock Mechanics and Geotechnical Engineering, 2024, 16(8): 3136-3148.
Liu, Y., Jin, G., Wu, K., et al. Hydraulic-fracture-width inversion using low-frequency distributed-acoustic-sensing strain data – Part I: Algorithm and sensitivity analysis. SPE Journal, 2021, 26(1): 359-371.
Maxwell, S. Microseismic Imaging of Hydraulic Fracturing: Improved Engineering of Unconventional Shale Reservoirs. Houston, USA, Society of Exploration Geophysicists, 2014.
Manjunath, G. L., Liu, Z., Jha, B. Multi-stage hydraulic fracture monitoring at the lab scale. Engineering Fracture Mechanics, 2023, 289: 109448.
McCormack, K. L., Zoback, M. D., Kuang, W. A case study of vertical hydraulic fracture growth, stress variations with depth and shear stimulation in the Niobrara Shale and Codell Sand, Denver-Julesburg Basin, Colorado. Interpretation, 2021, 9(4): SG59-SG69.
Mondal, S., Zhang, M., Huckabee, P., et al. Advancements in step down tests to guide perforation cluster design and limited entry pressure intensities – Learnings from field tests in multiple basins. Paper SPE 204147 Presented at SPE Hydraulic Fracturing Technology Conference and Exhibition, Virtual, 3-5 May, 2021.
Nayak, A., Correa, J., Ajo-Franklin, J. Seismic magnitude estimation using low-frequency strain amplitudes recorded by DAS arrays at far-field distances. Bulletin of the Seismological Society of America, 2024, 114(4): 1818-1838.
Nguyen, K., Zhang, M., Ayala, L. Transient pressure behavior for unconventional gas wells with finite-conductivity fractures. Fuel, 2020, 266: 117119.
Nolte, K. Determination of fracture parameters from fracturing pressure decline. Paper SPE 8341 Presented at SPE Annual Technical Conference and Exhibition, Las Vegas, Nevada, 23-26 September, 1979.
Parisio, F., Yoshioka, K., Sakaguchi, K., et al. A laboratory study of hydraulic fracturing at the brittle-ductile transition. Scientific Reports, 2021, 11(1): 22300.
Pei, Y., Sepehrnoori, K. Investigation of parent-well production induced stress interference in multilayer unconventional reservoirs. Rock Mechanics and Rock Engineering, 2022, 55: 2965-2986.
Ren, Z., Yan, R., Huang, X., et al. The transient pressure behavior model of multiple horizontal wells with complex fracture networks in tight oil reservoir. Journal of Petroleum Science and Engineering, 2019, 173: 650-665.
Sun, Z., Zhao, Y., Gao, Y., et al. Effects of bedding characteristics on crack propagation of coal under mode II loading: Laboratory experiment and numerical simulation. Journal of Rock Mechanics and Geotechnical Engineering, 2025, 17(2): 1037-1052.
Tripoppoom, S., Wang, X., Liu, Z., et al. Characterizing hydraulic and natural fractures properties in shale oil well in Permian basin using assisted history matching. Fuel, 2020, 275: 117950.
Unal, E., Rezaei, A., Siddiqui, F., et al. Improved understanding of dynamic fracture behavior in unconventional horizontal wells using wavelet transformation. Paper SPE 195889-MS Presented at SPE Annual Technical Conference and Exhibition, Calgary, Alberta, Canada, 30 September-2 October, 2019.
Wang, Z., Cai, Y., Liu, D., et al. Characterization of natural fracture development in coal reservoirs using logging machine learning inversion, well test data and simulated geostress analyses. Engineering Geology, 2024, 341: 107696.
Wang, Y., Hu, X., Zhou, F., et al. Comparing different segments in shut-in pressure signals: New insights into frequency range and energy distribution. Petroleum Science, 2025, 22(1): 442-456.
Wei, Z., Sheng, M., Hu, Z., et al. Identification of nearly pure leak-off phase from pressure falloff curve and its interpretation on fracture areas. SPE Journal, 2024, 29(11): 6185-6197.
Wei, Z., Sheng, M., Hu, Z., et al. Acoustic signatures of sonar-based fracture diagnostics in horizontal wells. Physics of Fluids, 2025, 37(8): 083116.
Wu, K., Liu, Y., Jin, G., et al. Fracture hits and hydraulic-fracture geometry characterization using low-frequency distributed acoustic sensing strain data. Journal of Petroleum Technology, 2021, 73(7): 39-42.
You, S., Liao, Q., Yue, Y., et al. Enhancing fracture geometry monitoring in hydraulic fracturing using radial basis functions and distributed acoustic sensing. Advances in Geo-Energy Research, 2025, 16(3): 260-275.
Zhang, R., Chen, M., Zhao, Y., et al. Production performance simulation of the fractured horizontal well considering reservoir and wellbore coupled flow in shale gas reservoirs. Energy & Fuels, 2022, 36(22): 13637-13651.
Zoback, M., Kohli, A. Unconventional Reservoir Geomechanics. Cambridge, UK, Cambridge University Press, 2019.
Downloads
Downloads
Published
Issue
Section
License
Copyright (c) 2025 Author(s)
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.