Rock typing and facies identification using fractal theory and conventional petrophysical logs
Roozbeh Koochak A B , Manouchehr Haghighi A , Mohammad Sayyafzadeh A and Mark Bunch AA Australian School of Petroleum, Santos Petroleum Engineering Building, University of Adelaide, SA 5005, Australia.
B Corresponding author. Email: Roozbeh.koochak@adelaide.edu.au
The APPEA Journal 58(1) 102-111 https://doi.org/10.1071/AJ17087
Submitted: 14 December 2017 Accepted: 15 February 2018 Published: 28 May 2018
Abstract
Rock typing or subdivision of a reservoir either vertically or laterally is an important task in reservoir characterisation and production prediction. Different depositional environments and diagenetic effects create rocks with different grain size distribution and grain sorting. Rock typing and zonation is usually made by analysing log data and core data (mercury injection capillary pressure and permeability measurement). In this paper, we introduce a new technique (approach) for rock typing using fractal theory in which resistivity logs are the only required data.
Since resistivity logs are sensitive to rock texture, in this study, deep conventional resistivity logs are used from eight different wells. Fractal theory is applied to our log data to seek any meaningful relationship between the variability of resistivity logs and complexity of rock fabric. Fractal theory has been previously used in many stochastic processes which have common features on multiple scales. The fractal property of a system is usually characterised by a fractal dimension. Therefore, the fractal dimension of all the resistivity logs is obtained.
The results of our case studies in the Cooper Basin of Australia show that the fractal dimension of resistivity logs increases from 1.14 to 1.29 for clean to shaly sand respectively, indicating that the fractal dimension increases with complexity of rock texture. The fractal dimension of resistivity logs is indicative of the complexity of pore fabric, and therefore can be used to define rock types.
Keywords: Cooper Basin, fractal geometry, Higuchi’s fractal dimension method, resistivity well logs, rock typing.
Roozbeh Koochak is an experienced wireline logging engineer with over 10 years of experience in both cased-hole and open-hole services. He joined China National Logging Corp. in 2006 and later Baker Hughes as senior engineer in 2012. During this period he held assignments in the Middle East, Australia and China, and managed operations for two years. He is currently a Master of Philosophy Candidate in Petroleum Engineering at the University of Adelaide, working on identification of rock types using fractal theory. Roozbeh has a Bachelor of Electronics Engineering from Shahid Chamran University of Ahvaz. His research interests are reservoir modelling and simulation, petrophysics, wavelet analysis, fractal theory, uncertainty analysis, production optimisation and history matching. |
Manouchehr (Manny) Haghighi is an Associate Professor of Petroleum Engineering. His research and teaching focus is on unconventional reservoirs, reservoir simulation, well testing and formation evaluation. He has supervised more than 40 MSc and 10 PhD students. Before joining the University of Adelaide in 2009, Manouchehr was Associate Professor of Petroleum Engineering at the University of Tehran. In 2000, Manouchehr established Simtech, a consulting company for integrated reservoir simulation. He has been project director of several full field simulation projects for oil and gas reservoirs. From 1995 to 2000, Manouchehr worked with the National Iranian Oil Company (NIOC) and was the director of a program for training NIOC staff at several universities in the US, UK, Canada, France, Australia and Norway. Manouchehr was a Visiting Professor at the University of Calgary during 2007–2008. Manouchehr has published more than 80 articles in peer-reviewed journals or presented in international conferences. He has served as a reviewer for different journals such as the journal of Petroleum Science and Engineering, and is a member of SPE. |
Mohammad Sayyafzadeh is a lecturer in Petroleum Engineering at the University of Adelaide, where he started in 2013. His research interest is applied and computational mathematics targeting reservoir and production engineering problems. That includes computer-assisted history matching, uncertainty quantification, field development planning and reservoir flooding optimisation, modelling of unconventional resources and data analytics. Mohammad holds a BSc in Chemical Engineering, an MSc in Reservoir Engineering from Tehran Polytechnic and a PhD in Petroleum Engineering from the University of Adelaide. Mohammad has contributed in publishing 23 papers in peer-reviewed journals and conferences, and serves as a reviewer for different journals and EAGE/SPE conferences. He is the lead-investigator of a project on developing a computer-assisted history matching tool sponsored by Santos Ltd and participated as a co-investigator and research fellow in three other industrial projects. |
Mark Bunch is a Senior Lecturer in Petroleum Geoscience at the Australian School of Petroleum, University of Adelaide. His present research activities are concerned with formation evaluation and seismic attribute analysis. Prior to his present role, he spent seven years with the CO2CRC as a Research Associate in reservoir characterisation, during which he worked on geological carbon storage site selection, capacity estimation and geological modelling projects in the onshore Canterbury Basin (NZ), the Gippsland and Otway basins of Victoria, the Surat Basin of Queensland and the Darling Basin of NSW. Mark spent a period of time as acting head of geomodelling for the CO2CRC Otway Basin Pilot Project and led CO2CRC storage research projects for five years. Mark holds degrees in Geology and Geophysics (BSc Hons), Hydrogeology (MSc) and a PhD in Earth Sciences (Stratigraphic Forward Modelling). Mark has also worked for the North Sea Palaeolandscapes Project and as a developer of shallow groundwater flow models to guide excavation planning. |
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