Expanding role of borehole image logs in reservoir fracture and heterogeneity characterization: A review
Abstract view|260|times PDF download|139|times Supplements download|72|times
Abstract
Borehole imaging well-log datasets provide a wide range of valuable information for various aspects of petroleum reservoir characterization. In particular, electrical borehole images make it possible to detect and quantify the distributions, orientations, and forms of fractures at high resolution. Acoustic borehole images are extensively used for breakout detection and width measurements to determine horizontal principal stress magnitudes and orientations. However, by combining information from different types of borehole imaging tools more comprehensive reservoir characterization can be achieved. Data from the dipole shear-wave imager can be used to provide anisotropy insights that are of complementary value for lithofacies, poro-permeability, and seismic dataset interpretations of heterogeneous reservoirs. Cases are made to incorporate data from both electrical and acoustic borehole imaging datasets into integrated reservoir characterization analysis. Moreover expanding the reach of borehole imaging data is becoming increasingly possible with the aid of machine learning models configured to predict key borehole imaging metrics from standard suites of petrophysical well-log and drilling mud-log datasets.
Document Type: Invited review
Cite as: Wood, D. A. Expanding role of borehole image logs in reservoir fracture and heterogeneity characterization: A review. Advances in Geo-Energy Research, 2024, 12(3): 194-204. https://doi.org/10.46690/ager.2024.06.04
Keywords
References
Ajami, M., Davoodi, S., Asgari, K., et al. The impact of fractures and planar structures on the quality of the Upper Jurassic Mozduran reservoir, Kopet Dagh Basin (Northeast Iran). Journal of Asian Earth Sciences, 2024, 267: 106167.
Azadivash, A., Soleymania, H., Seifirad, A., et al. Robust fracture intensity estimation from petrophysical logs and mud loss data: A multi-level ensemble modeling approach. Journal of Petroleum Exploration and Production Technology, 2024, in press, https://doi.org/10.1007/s13202- 024-01820-9.
Babasafari, A. A., Chinelatto, G. F., Vidal, A. C. Fault and fracture study by incorporating borehole image logs and supervised neural network applied to the 3D seismic attributes: A case study of pre-salt carbonate reservoir, Santos Basin, Brazil. Petroleum Science and Technology, 2022, 40(12): 1492-1511.
Baraian, A., Kellokumpu, V., Tomi, R., et al. Automatic fracture detection and characterization in borehole images using deep learning-based semantic segmentation. Paper Presented at the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP), Lisbon, Portugal, 19-21 February, 2023.
Barton, C. A., Zoback, M. D., Burns, K. L. In-situ stress orientation and magnitude at the Fenton Geothermal Site, New Mexico, determined from wellbore breakouts. Geophysical Research Letters, 1988, 15(5): 467-470.
Boro, H., Rosero, E., Bertotti, G. Fracture-network analysis of the Latemar Platform (northern Italy): Integrating outcrop studies to constrain the hydraulic properties of fractures in reservoir models. Petroleum Geoscience, 2014, 20: 79-92.
Bourke, L. T., Delfiner, P., Trouiller, J. C., et al. Using formation microscanner images. The Technical Review (Schlumberger), 1989, 37(1): 16-40.
Brown, J., Davis, B., Gawanker, K, et al. Imaging: Getting the picture downhole. Schlumberger Oilfield Review (September), 2015, 27(2): 4-21.
Chongqing Gold Mechanical & Electrical Equipment Co., Ltd. Geophysical wireline borehole imaging equipment. Chongqing Gold Mechanical & Electrical Equipment Co., Ltd., 2024.
Columbia University. Dipole Sonic Imager Tool (DSI-2; SLB). Columbia University, 2024.
Davarpanah, A., Kakoli, M., Ahmadi, H. Analysis of fractured reservoir structure by interpretafion of FMI and VSP logs. Journal of Marine Science: Research & Development, 2016, 6: 216.
Dias, L. O., Bom, C. R., Faria, E. L., et al. Automatic detection of fractures and breakouts patterns in acoustic borehole image logs using fast-region convolutional neural networks. Journal of Petroleum Science and Engineering, 2020, 191: 107099.
Du, L., Lu, X., Li, H. Automatic fracture detection from the images of electrical image logs using Mask R-CNN. Fuel, 2023, 351: 128992.
Ekstrom, M. P., Dahan, C. A., Chen, M. Y., et al. Formation imaging with microelectrical scanning arrays. Paper SPWLA 1986 Presented at the SPWLA 27th Annual Logging Symposium, Houston, Texas, 9-13 June, 1986.
Esmersoy, C., Kane, M., Boyd, A., et al. Fracture and stress evaluation using dipole-shear anisotropy logs. Paper SPWLA 1995 Presented at the SPWLA 36th Annual Logging Symposium, Paris, France, 26-29 June, 1995.
Fanchi, J. R. Fracture and shale systems, in Principles of Applied Reservoir Simulation, edited by John R. Fanchi, Elsevier, USA, pp. 241-256, 2018.
Faraji, M., Rezagholilou, A., Ghanavati, M., et al. Breakouts derived from image logs as an aid in estimation of the magnitude of maximum horizontal stress: A case study from Perth Basin, Western Australia. Advances in Geo Energy Research, 2020, 5(1): 8-24.
Gillespie, P. A., Johnston, J. D., Loriga, M. A., et al. Influence of layering on vein systematics in line samples, in Fractures, Fluid Flow and Mineralization, edited by McCaffrey, K. J. W., Lonergan, L., Wilkinson, J. J. Geological Society, London, pp. 35-56, 1999.
Goswami, D., Hazarika, P., Roy, S. In situ stress orientation from 3 km borehole image logs in the Koyna Seismogenic Zone, Western India: Implications for transitional faulting environment. Tectonics, 2020, 39: e2019TC005647.
Haldorsen, J. B. U., Johson, D. L., Plona, T., et al. Borehole acoustic waves. Schlumberger Oilfield Review, 2006, 18(1): 34-43.
Halliburton. X-tended Range Micro Imaging (XRMITM) tool, 2024.
Hawez, H. K., Sanaee, R., Faisal, N. H. A critical review on coupled geomechanics and fluid flow in naturally fractured reservoirs. Journal of Natural Gas Science and Engineering, 2021, 95: 104150.
Heidbach, O., Rajabi, M., Cui, X., et al. The World Stress Map database release 2016: Crustal stress pattern across scales. Tectonophysics, 2018, 744: 484-498.
Hooker, J. N., Laubach, S. E., Marrett, R. Fracture-aperture size- frequency, spatial distribution, and growth processes in strata-bounded and non-strata-bounded fractures, Cambrian Meson Group, NW Argentina. Journal of Structural Geology, 2013, 54: 54-71.
Hosseinzadeh, S., Kadkhodaie, A., Wood, D. A., et al. Discrete fracture modeling by integrating image logs, seismic attributes, and production data: A case study from Ilam and Sarvak Formations, Danan Oilfield, southwest of Iran. Petroleum Exploration and Production Technology, 2023, 13(4): 1053-1083.
Huffman, K. A., Saffer, D. M., Dugan, B. In situ stress magnitude and rock strength in the Nankai accretionary complex: a novel approach using paired constraints from downhole data in two wells. Earth, Planets and Space, 2016: 68(1): 123.
Ibrahim, A. F., Gowida, A., Ali, A., et al. Machine learning application to predict in-situ stresses from logging data. Scientific Reports, 2021, 11(1): 23445.
IODP. Ultrasonic Borehole Imager (UBI; SLB trademark). International ocean drilling program, 2024. Ismail, A., Farshid, T., Azadbakht, S., et al. Identification of natural fractures in shale gas reservoirs using fracture signature function and machine learning models. Unconventional Resources, 2024, 4: 100069.
Katterbauer, K., Al Qasim, A., Al Shehri, A., et al. Smart detection of fractures in formation image logs for enhanced CO2 storage. Science and Technology for Energy Transition, 2022, 77(21): 1-7.
Khoshbakht, F., Azizzadeh, M., Memarian, H., et al. Comparison of electrical image log with core in a fractured carbonate reservoir. Journal of Petroleum Science and Engineering, 2012, 86: 289-296.
Krizhevsky, A., Sutskever, I., Hinton G. E. ImageNet classification with deep convolutional neural networks. Communications of the ACM, 2017, 60(6): 84-90.
LandSea. Circumferential Borehole Imaging Logging Tool (CBITTM), 2024.
Lin, H., Oh, J., Canbulat, I., et al. Experimental and analytical investigations of the effect of hole size on borehole breakout geometries for estimation of in situ stresses. Rock Mechanics and Rock Engineering, 2020, 53(2): 781-798.
Liu, J., Yang, H., Bai, J., et al. Numerical simulation to determine the fracture aperture in a typical basin of China. Fuel, 2021, 283: 118952.
Liu, Y., Liao, G., Xiao, L., et al. Automatic fracture segmentation and detection from image logging using Mask RCNN. Paper SPWLA 2022 0115 Presented at the SPWLA 63rd Annual Logging Symposium, Stavanger, Norway, 11-15 June, 2022.
Luthi, S. M., Souhaite, P. Fracture apertures from electrical ´ borehole scans. Geophysics, 1990, 55(7): 821-833.
Mazdarani, A., Kadkhodaie, A., Wood, D. A., et al. Natural fractures characterization by integration of FMI logs, well logs and core data: A case study from the Sarvak Formation (Iran). Journal of Petroleum Exploration and Production Technology, 2023, 13(5): 1247-1263.
Nabiei, M., Yazdjerdi, K., Soleimany, B., et al. Analysis of fractures in the Dalan and Kangan carbonate reservoirs using FMI logs: Sefid-Zakhur gas field in the Fars Province, Iran. Carbonates and Evaporites, 2021, 36(2): 28.
Nelson, R. A. Evaluating fractured reservoirs, in Geologic Analysis of Naturally Fractured Reservoirs, edited by R. A. Nelson, Elsevier, Houston, pp. 1-100, 2001.
Nian, T., Wang, G., Tan, C., et al. Hydraulic apertures of barren fractures in tight-gas sandstones at depth: Image-core calibration in the Lower Cretaceous Bashijiqike Formation, Tarim Basin. Journal of Petroleum Science and Engineering, 2021, 196: 108016.
Nian, T., Wang, G., Xiao, C., et al. The in situ stress determination from borehole image logs in the Kuqa Depression. Journal of Natural Gas Science and Engineering, 2016, 34: 1077-1084.
Nie, X., Zou, C., Pan, L., et al. Fracture analysis and determination of in-situ stress direction from resistivity and acoustic image logs and core data in the Wenchuan Earthquake Fault Scientific Drilling Borehole-2 (50-1,370 m). Tectonophysics, 2013, 593: 161-171.
Ng, C. S. W., Amar, M. N., Ghahfarokhi, A. J., et al. A survey on the application of machine learning and metaheuristic algorithms for intelligent proxy modeling in reservoir simulation. Computers & Chemical Engineering, 2023, 170: 108107.
Olya, B. A. M., Mohebian, R., Bagheri, H., et al. Toward real-time fracture detection on image logs using deep convolutional neural network YOLOv5. Interpretation, 2024, 12(2): SB9-SB18.
Pachineelam, S., Paluri, B. S., Mudigonda, A. S. K., et al. Evaluation of stress anisotropy of the formation by utilizing dipole shear sonic imager (DSI*), formation micro imager (FMI*) and density log-a case study on Kanawara Field, South Cambay Basin, India. Paper Presented at the International Petroleum Technology Conference, Bangkok, Thailand, 15-17 November, 2011.
Ponziani, M., Slob, E., Luthi, S., et al. Experimental validation of fracture aperture determination from borehole electric microresistivity measurements. Geophysics, 2015, 80(3): D175-D181.
Qobi, L., De Kuijper, A., Tang, X. M., et al. Permeability determination from Stoneley waves in the Ara Group carbonates, Oman. GeoArabia. 2001, 6(4): 649-666.
Sadeqi, M., Manaman, N. S., Kadkhodaie, A., et al. The effect of frequency bandwidth on DSI anisotropy evaluation. Journal of Applied Geophysics, 2022, 201: 104641.
SLB. Fullbore formation micro-imager (FMI), 2024
Tabasi, S., Tehrani, P. S., Rajabi, M., et al. Optimized machine learning models for natural fractures prediction using conventional well logs. Fuel, 2022, 326: 124952.
Tóth, E., Hrabovszki, E., Tóth, T. M. Using geophysical log data to predict the fracture density in a claystone host rock for storing high-level nuclear waste. Acta Geodaetica et Geophysica, 2023, 58: 35-51.
Vahle, C., Veselovsky, Z., Ruehlicke, B. Detailed geological reservoir characterisation using an integrated analysis of borehole image logs. Paper Presented at the 1st Geoscience & Engineering in Energy Transition Conference, Strasbourg, France, 16-18 November, 2020.
Van Stappen, J. F., Meftah, R., Boone, M. A., et al. In situ triaxial testing to determine fracture permeability and aperture distribution for CO2 Sequestration in Svalbard, Norway. Environmental Science & Technology, 2018, 52(8): 4546-4554.
Vijouyeh, A. G., Kadkhodaie, A., Sedghi, M. H., et al. Identification of high potential zones for hydrocarbon production based on fracture aperture estimation using hybridised intelligent systems: Datasets and Supplementary Materials, Mendeley Data, 2023.
Wang, Q., Narr, W., Laubach, S. E. Quantitative characterization of fracture spatial arrangement and intensity in a reservoir anticline using horizontal wellbore image logs and an outcrop analogue. Marine and Petroleum Geology, 2023, 152: 106238.
Weatherford. CompactTM Microresistivity Tool, 2024
Wood, D. A. Well integrity for underground gas storage relating to natural gas, carbon dioxide, and hydrogen, in Sustainable Natural Gas Drilling: Technologies and Case Studies for the Energy Transition, edited by D. A. Wood and J. Cai, Elsevier, Amsterdam, pp. 551-576, 2024.
Wood, D. A., Cai, J. Coal-bed methane reservoir characterization using well-log data, in Sustainable Geoscience for Natural Gas Subsurface Systems, edited by D. A. Wood and J. Cai, Elsevier, Huston, pp. 243-274, 2022.
Zampetti, V., Borkhataria, R., Vroon, M. Multi-scale assessment of the Middle Eastern Permo-Triassic Khuff Carbonate: Structural evolution and its impact from reservoir properties. Paper Presented at AAPG GEO Conference, Manama, Bahrain, 7-10 March, 2010.
Zhang, J., Nie, X., Xiao, S., et al. Generating porosity spectrum of carbonate reservoirs using ultrasonic imaging log. Acta Geophysica, 2018, 66: 191-201.
Zhou, F., Oraby, M., Luft, J., et al. Coal seam gas reservoir characterisation based on high-resolution image logs from vertical and horizontal wells: A case study. International Journal of Coal Geology, 2022, 262: 104110. Zhou, S. A program to model the initial shape and extent of borehole breakout. Computers & Geosciences, 1994, 20(7-8): 1143-1160.
Zoback, M. D. Reservoir Geomechanics. Cambridge, United Kingdom, Cambridge University Press, 2009.
Zoback, M. D., Barton, C. A., Brudy, M., et al. Determination of stress orientation and magnitude in deep wells. International Journal of Rock Mechanics Mining Sciences, 2003, 40(7-8): 1049-1076.
DOI: https://doi.org/10.46690/ager.2024.06.04
Refbacks
- There are currently no refbacks.
Copyright (c) 2024 The Author(s)
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.