Abstract
Abstract Dolphin field is a mature gas field located in the East Coast Marine Area, offshore Trinidad. One of the methods to estimate gas initially in place (GIIP) of the field is material balance; however, this approach presents some particular challenges which include: sands are not well consolidated and exhibit very high rock compressibilities, communicating reservoir compartmentalization and wells are produced at very high rates. These three factors don't allow for a straight-forward understanding of the aquifer size, normally assessed with a deterministic Cole Plot analysis. As a result of these complexities, analysis demands a more in-depth understanding of the uncertainties of the reservoirs and their implications on fluid in place estimation to avoid bias and anchoring. This paper presents a case study of the workflow used in determining probabilistic material balance models for one sand in the Dolphin Field. Initially, an uncertainty analysis was conducted to determine the appropriate ranges of petrophysical data and aquifer properties that were used as input information for the material balance models. Experimental Design was then successfully applied to generate probabilistic material balance models: Placket-Burman design of experiment was used to identify the key uncertainties in a linear model. Monte Carlo simulation was used with the resultant response surface equation to determine probabilistic volumes of the field. This project successfully achieved a probabilistic GIIP range for a single method testing sand of the field, ultimately yielding a better understanding of the significant uncertainties and their implications. The resulting probabilistic material balance models also enable the use of an integrated asset model to generate fit for purpose forecasts and a provides a more rigorous quality checking method on reservoir simulation results. This paper will discuss a simple workflow used in probabilistically determining GIIP for one producing horizon in Dolphin field. Given the high confidence results encountered on the single sand, this approach will be applied to all Dolphin sand horizons to provide higher confidence GIIP estimates for the entire portfolio.
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