--> Predicting the Distribution of Porosity, Pore System Characteristics and Permeability from Openhole Log Datasets: Applications to Rock Typing in the Thamama Reservoir Zones, Haliba Field, UAE

AAPG Middle East Region Geoscience Technology Workshop:
3rd Edition Carbonate Reservoirs of the Middle East

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Predicting the Distribution of Porosity, Pore System Characteristics and Permeability from Openhole Log Datasets: Applications to Rock Typing in the Thamama Reservoir Zones, Haliba Field, UAE

Abstract

Rock types are the building blocks of reservoir models, and, as such, they must capture the key geological and reservoir quality variability, and be populated throughout a reservoir using standard subsurface datasets. Rock-typing studies often utilise openhole log or core data to define rock types, however, the key pre-requisites for a successful rock-typing scheme are rarely achieved unless both datasets are fully integrated. In this research and development study, geological and reservoir quality understanding, gained from detailed core and thin-section observations and laboratory-based petrophysical data, are integrated with openhole log data to define reservoir rock types (RRTs) in the Thamama reservoir zones in the Haliba Field. The RRTs honour the geological variability and provide an understanding of the distribution of porosity and permeability from standard subsurface data alone, therefore fulfilling the key requirements of a rock-typing scheme. Standard petrophysical parameters are calculated from the openhole logs and calibrated with core data, namely the porosity and permeability values, in seven wells. Log porosity, which is calculated from the neutron-density equation, strongly correlates with core porosity, indicating that the openhole logs are comparable in each well across the field, and that porosity can be confidently predicted in uncored wells from the logs. Young's Modulus also strongly correlates with core porosity, and is therefore useful for the same purpose. At high porosities, low Sxo values correspond to high core permeabilities (>10mD), whereas higher Sxo values tend to relate to lower core permeabilities. Log permeability, calculated using Sxo in the Coates equation, is also positively correlated with core permeability, particularly in hydrocarbon-bearing intervals.Lastly, high Young's Modulus values at a given porosity typically correspond to macropore-dominated pore systems with high core permeabilities, whereas low Young's Modulus values at the same porosity are associated with micropore-dominated pore systems. These relationships, relating openhole log data to core porosity and permeability, are used to define core porosity and permeability clusters from the openhole logs, which are called petrophysical rock types (PRTs). 34 PRTs are defined and categorised into 10 PRT clusters, according to their core porosity and permeability values, each cluster is characterised by a unique porosity and/or permeability range. Core-based geological rock types, which are defined according to pore systems characteristics from core, thin-section and laboratory-based petrophysical data, are then integrated to refine the clusters into 11 RRTs. Each RRT has a distinctive porosity and/or permeability range and is characterised by a particular pore system. The RRTs are populated in all wells using standard openhole log data, and thereby provide a prediction of the distribution of reservoir quality throughout the Thamama reservoir intervals.study. The obtained results are valuable information to further rock physics modelling and well placement.