In all exploration processes, the evaluation of basins, permits, and individual prospects changes over time with incremental availability and quality of data, technical effort expended, and knowledge gained. The NU prospect, located in the Mahakam Hilir PSC (East Kalimantan), is an example in which geologic chance of success (GCOS) predictions can change over time with increasing acquisition and availability of geophysical and geologic data and the studies done on them. We show how studies done on any one prospect or group of prospects can progressively increase/decrease the chance of at least one success in an exploration campaign of several wells. After a series of four wells was drilled in the PSC, which did not deliver commercial success, a change in approach was required to continue exploration. This included the acquisition of airborne gravity gradiometry data, initial trial prestack depth migration (PSDM) reprocessing of two key 1989 vintage 2D lines, acquisition of vintage well data from four Sambutan Field wells, acquisition of nine vintage 2D seismic lines over the field, and PSDM reprocessing of the nine 2D seismic lines. All data were then integrated to build a new geologic model. As a result, the NU prospect GCOS progressively moved from less than 10% to nearly 40%.
Corrosion models and the laboratory testing they are based on, give a measure of corrosion rate but not the spatial distribution of corrosion. Corrosion risk assessments can include information on areas that are more susceptible to corrosion and can give a measure of the probability of corrosion occurring, but when the corrosion is localized rather than general, they do not indicate whether the corrosion is evenly spaced or clustered or how the corrosion will develop in extent over time. To deliver inspection, which is both effective and efficient, requires an understanding of the spatial distribution of corrosion along with the fraction of wall area affected by corrosion. Historically low level sampling using Manual Ultrasonic Techniques (MUT) has formed the primary basis for inspection of pipework on offshore oil and gas assets. For extensive corrosion, low level sampling can be effective and cost efficient but for less extensive corrosion, higher coverage is required to reliably reflect the nature of the corrosion.Simulation of different spatial and depth distributions of corrosion, to reflect a range of base case scenarios, have been carried out in conjunction with simulations of different inspection strategies. Metrics have been developed to compare the effectiveness of different inspection strategies. This paper discusses the aims of inspection and how efficient and cost effective the different inspection strategies, such as sampling or screening, are in meeting these aims. A range of different corrosion base cases including general uniform, random localized and preferential locations will be examined in relation to the most appropriate inspection strategy, defined primarily in terms of coverage. Recognizing these different corrosion cases from previous inspection results and the optimum time to change inspection strategy will also be covered. This paper quantifies the relationship between spatial distribution of corrosion in pipework and the effectiveness of different inspection strategies.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2025 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.