A Fuzzy-Logic Theoretic Approach to Modelling Marginal Oilfield Risks

Abstract

Risk has remained a debilitating enigma against the full realization of marginal oilfield potentials and lack of its contribution to the economy. This stems from the inability on the part of the operators to identify, quantify and apply the risk profile to correctly adjust the return on investments in marginal fields. This study provides a veritable tool that systematically transforms the qualitative risk variables from its linguistic expressions to quantitative functions using fuzzy logic in combination with conventional risk analysis techniques. Accordingly a total of six risk attributes were isolated using Delphi technique. And, in all, 53 risk variables were identified and used to craft a questionnaire scaled with RensisLikerts 5-point attitudinal scale which were subsequently administered to 42 respondents. A computed Kendall Coefficient of Concordance of W = 0.75 and chi-squared value (x²) of 546 which is greater than 27.69 recorded in the statistical table showed an incontrovertible level of agreement among the judges in ranking the variables, hence, a null hypothesis of disconcordance among the judges was rejected at a p-value of 0.01. Again, the study was able to establish that an investment risk level of 0.71 on a scale of 0 to 1 is associated with this Isiekenesi field in the Nigeria Niger Delta, whereupon signifying a snag in the overall return on investment. Further, our results indicate that security of property and personnel pose the greatest challenge to investment in the marginal field of Niger Delta.