Authors :
Chinweike Okeke O.; Robert Nkpado
Volume/Issue :
Volume 11 - 2026, Issue 6 - June
Google Scholar :
https://tinyurl.com/2v2hwz9j
Scribd :
https://tinyurl.com/38p7mek2
DOI :
https://doi.org/10.38124/ijisrt/26jun1781
Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.
Abstract :
Accurate estimation of hydrocarbon volumes is fundamental to field development planning, reserves booking,
investment decisions, and corporate valuation. At every stage of reservoir maturation, subsurface uncertainty influences
estimate of Original Oil in Place (OOIP), Gas Initially in Place (GIIP), and recoverable reserves. Probabilistic volumetric
distributions, particularly P10, P50, and P90 estimates, commonly represent this uncertainty. A key indicator of uncertainty
reduction throughout the reservoir lifecycle is the narrowing of the gap between P10 and P90 volumetric estimates. During
exploration, this gap may exceed several hundred per cent due to limited geological and petrophysical information. As
appraisal, development, and production data become available, uncertainty progressively decreases, and volumetric
outcomes converge. This paper argues that the P10–P90 spread is a practical measure of reservoir uncertainty and that it
should narrow as field knowledge increases. It examines how uncertainty evolves from exploration through mature
production, identifies the principal drivers of reduction, quantifies expected changes in spread, and presents a case study
illustrating the evolution of uncertainty within a typical clastic oil reservoir. The paper further proposes a framework for
tracking uncertainty maturity, using the P10–P90 ratio as a reservoir management metric.
Keywords :
Volumetric Uncertainty, P10, P50, P90, Reserves Estimation, Reservoir Lifecycle, Uncertainty Quantification, Monte Carlo Simulation, Reservoir Characterisation.
References :
- Society of Petroleum Engineers (SPE), Petroleum Resources Management System (PRMS), latest edition.
- Dake, L.P., Fundamentals of Reservoir Engineering, Elsevier.
- Rose, P.R., Risk Analysis and Management of Petroleum Exploration Ventures.
- McCain, W.D., Reservoir Fluid Property Correlations.
- Ahmed, T., Reservoir Engineering Handbook, 5th Edition.
- Haldorsen, H.H., and Damsleth, E., “Challenges in Reservoir Characterisation,” SPE Journal.
- Cosentino, L., Integrated Reservoir Studies.
- Deutsch, C.V., Geostatistical Reservoir Modelling.
- Caers, J., Modelling Uncertainty in the Earth Sciences.
- SPEE Monograph Series on Reserves and Resources Estimation.
Accurate estimation of hydrocarbon volumes is fundamental to field development planning, reserves booking,
investment decisions, and corporate valuation. At every stage of reservoir maturation, subsurface uncertainty influences
estimate of Original Oil in Place (OOIP), Gas Initially in Place (GIIP), and recoverable reserves. Probabilistic volumetric
distributions, particularly P10, P50, and P90 estimates, commonly represent this uncertainty. A key indicator of uncertainty
reduction throughout the reservoir lifecycle is the narrowing of the gap between P10 and P90 volumetric estimates. During
exploration, this gap may exceed several hundred per cent due to limited geological and petrophysical information. As
appraisal, development, and production data become available, uncertainty progressively decreases, and volumetric
outcomes converge. This paper argues that the P10–P90 spread is a practical measure of reservoir uncertainty and that it
should narrow as field knowledge increases. It examines how uncertainty evolves from exploration through mature
production, identifies the principal drivers of reduction, quantifies expected changes in spread, and presents a case study
illustrating the evolution of uncertainty within a typical clastic oil reservoir. The paper further proposes a framework for
tracking uncertainty maturity, using the P10–P90 ratio as a reservoir management metric.
Keywords :
Volumetric Uncertainty, P10, P50, P90, Reserves Estimation, Reservoir Lifecycle, Uncertainty Quantification, Monte Carlo Simulation, Reservoir Characterisation.
