Translating Petrophysics to Engineering Economics
Authors: Altunbay M. Mehmet , Ismail Shukri B , Fadzil Nurul Aula , Das Saikat 
Published: October 2012

Abstract
Identification and evaluation of quasi-wet pay zones (QWPZ) comprised of low-resistivity low-contrast (LRLC), low porosity-low-permeability sands and thin-beds are inadequate to decide if the cost of well testing/completion/stimulation is justifiable or not. The objective of this study is setting up methodologies for translating petrophysical analysis of QWPZs to PI/rate profiles for hypothetical scenarios (when crucial data are unavailable) and OOIP/OGIP estimates. The outcome of estimated PI/rate profiles and probabilistic OOIP/OGIP values for a well/field makes financial decisions easier for furthering or terminating costly well activities such as, well testing, sampling, completion and stimulations.
In this study we used NMR, directional resistivity and Image logs in addition to the conventional log data. Results from traditional petrophysical analysis (sand-silt-clay model) were compared against Thomas-Steiber technique together with NMR DT2int maps. Co-existence of resistivity-anisotropy from directional resistivity tool and movable porosity from NMR log is commonly perceived as pay-indicator if electrical anisotropy is not due to bioturbation. We used image logs to understand and to screen the possible causes of apparent anisotropy, and DT2int maps to differentiate the oil-based mud-filtrate from formation oil. A prolific oil producer that was previously thought to be a water-sand was identified by NMR DT2int maps. NMR permeability was calibrated using mobility-driven permeability values from formation tester. Synthetic capillary pressure, Swirr from NMR and relative-permeability by Pirson, Brooks-Corey, and Mohamad-Koederitz correlations with resistivity-based Sw produced the effective permeability profiles leading to Productivity Index (PI) and production rate estimations for every sand package for given sets of hypothetical conditions (skin factor, drainage radius and drawdown pressure). Based on the findings, sampling and well test were conducted. Oil samples were fingerprinted and compared against OBM-filtrate confirming the acquired sample was formation oil. Drillstem test (DST) reported high and sustainable oil production rates with no water-cut that agreed with what was computed from our integrated analysis. Original-oil-in-place (OOIP) and recoverable OIP (Rec-OIP) are initially computed based on hypothetical lateral-extents of the sand packages for economic justification of furthering or terminating the well activities (testing/sampling). Later on, the OOIP and Rec-OIP figures were re-calculated with the actual areal coverage data driven from the geological model.
The study revealed and quantified a highly productive oil-sand by strict reservoir engineering treatment of advanced petrophysical data. Sampling and testing of the zone verified the accuracy of methodology and value-added nature of translating Petrophysics to economics. Deriving Swirr profile was also explained for cases with no NMR log data. The early prediction of OOIP and recoverable OIP, even with assumptions on the lateral extent of the sands, has proven to provide assistance during the decision making of expensive well activities.
In this study, we, firstly, established our reasoning for the arrived conclusions, and then, demonstrated the evidence/results from our approach before we translated petrophysics into engineering economics. It is our main intention to show that strict reservoir engineering treatment of petrophysical and geological data provides a crucial linkage between major disciplines in the very early life of a well(s) and field activities while serving/helping for the betterment of economic decisions. Additionally, this crucial linkage may provide enhancing total return on assets by controlling and justifying the expenses from well/field activities.