Integrated Geological and Engineering Uncertainty Analysis Workflow, Lower Permian Carbonate Reservoir, Timan-Pechora Basin, Russia

Abstract

This paper aims to show all the steps involved in a rigorous uncertainty analysis study, completed in 2008, in static and dynamic modeling as well as try to highlight some very key steps for a successful study. Yuzhno Khylchuyu (YK) field is a Permian aged Carbonate reservoir in Timan Pechora basin in European part of Russia. It was discovered in 1981 and has since been appraised by 24 wells. The field is being developed on a regularized waterflood 5-spot pattern with 120-acre well spacing. The productive reservoir is composed of three main zones, A, B, and C. These zones are not in communication based on geo-chemical data and dynamic well test results. Zone A, which is dominantly progradational has good continuity and best reservoir properties containing 90% of the original oil in place (OOIP). Dominantly aggraditional zones B and C are discontinuous, and have poor reservoir properties. The motivation behind a rigorous uncertainty analysis on OOIP and Expected Ultimate Recovery (EUR) was due to the large capital investment required for full field development. Thus, the objective of this study was to quantify the range of uncertainty of OOIP and EUR, to identify the most influential parameters contributing to uncertainties in OOIP and EUR, and quantify the impact of those most influential parameters. Such rigorous uncertainty analysis would thus help mitigate the risks with the investment.

Challenges of a mature Russian field's redevelopment – Advantages and disadvantages of quick-look geologic modeling

“…The workflow followed a common suite of procedures, beginning with fault and horizon modeling, structural modeling, building a 3D grid, populating the 3D grid with facies and petrophysical properties and calculating hydrocarbon in place volumes (Fig. 6) (Adelu et al, 2019;Kaleta et al, 2012;Shirazi et al, 2010;Spagnuolo et al, 2018).…”

“…6. This is a general workflow applied in numerous modeling exercises in simple (Adelu et al, 2019) or in more complex forms (Galindo et al, 2012;Kaleta et al, 2012;Shirazi et al, 2010;Spagnuolo et al, 2018).…”

An Integrated Approach of Uncertainty Assessment for Coalbed Methane Model

“…Limited amount of hard data, lack of well control and scarcity of geology studies are the great challenges in the exploration and development phase of a CBM field. Most of the risks are related to the uncertainty in the static reservoir characterization, which also affects the dynamic response (Shirazi et al 2010;Mohsen et al 2007;Sharma et al 2008). The inability to properly manage subsurface uncertainty is often a key reason for the CBM projects failing to meet their objectives.…”