Finding a Needle in a Rusty Hay Stack… Knowing Where to Start With 30,000kmof Pipelines! (2006)

Finding a Needle in a Rusty Hay Stack... Knowing Where to Start with 30 000 km of Pipelines Simon Webster; Simon Webster JSC TNK-BP Management Search for other works by this author on: This Site Google Scholar Ilia Sivokon; Ilia Sivokon TNK-BP Management Search for other works by this author on: This Site Google Scholar David Lane; David Lane TNK-BP Management Search for other works by this author on: This Site Google Scholar Adam Petersen Adam Petersen OJSC "TNK-BP Management" Search for other works by this author on: This Site Google Scholar Paper presented at the SPE Russian Oil and Gas Technical Conference and Exhibition, Moscow, Russia, October 2006. Paper Number: SPE-101327-MS https://doi.org/10.2118/101327-MS Published: October 03 2006 Cite View This Citation Add to Citation Manager Share Icon Share Twitter LinkedIn Get Permissions Search Site Citation Webster, Simon, Sivokon, Ilia, Lane, David, and Adam Petersen. "Finding a Needle in a Rusty Hay Stack... Knowing Where to Start with 30 000 km of Pipelines." Paper presented at the SPE Russian Oil and Gas Technical Conference and Exhibition, Moscow, Russia, October 2006. doi: https://doi.org/10.2118/101327-MS Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex Search Dropdown Menu nav search search input Search input auto suggest search filter All ContentAll ProceedingsSociety of Petroleum Engineers (SPE)SPE Russian Petroleum Technology Conference Search Advanced Search AbstractTNK-BP plans to invest a significant amount of money in improving the integrity of its pipeline network over the next 5 years. The question that needed to be solved is where do we start? With a pipeline network that consists of over 43,000 individual lines that have a combined length of over 30,000 km selecting the right pipelines to replace, inspect and inhibit is not a trivial task. The task is made even more difficult when it is considered that when TNK-BP was formed it consisted of 600 legal entities, which did not have common processes and ways to store data. To address this problem a risk model was built which used data that could easily be collected for the pipelines in the company. After testing in the Volga-Urals and West Siberian regions the company then undertook a large data collection exercise. Using the risk model all pipelines have been ranked according to their probability and consequence of failure, and the data has been used to ensure that the investment in pipeline replacement, corrosion control and inspection are targeted to the areas where the biggest impact can be made. The exercise has also made it possible to understand how much investment may be required, because there is now a clear picture of the lengths of pipelines that have experienced failures. Pipeline prioritisation has answered the question where do we start, and is also helping us to answer the next question - when will we get there?IntroductionTNK-BP operates a large pipeline network, which on formation of the company was over 30,000 km long with a fairly even spread of ages between less than 5 years to greater than 20 (fig. 1). The company will invest a significant amount of money in this network so that it will comply with the company's goal of "No harm to the environment". This investment will be focused on replacing lines that pose a significant risk of failure, protecting those already installed by inhibition and an inspection program that will help identify corrosion damage before it leads to failure.With such a large network, knowing where to initially focus these activities to have the biggest impact is a difficult task. To solve this problem the authors, in conjunction with the company's Pipeline Integrity Expert Group, developed a risk based pipeline prioritisation model that has classified all the pipelines in terms of probability and consequence of failure.The model is used as a screening tool to quickly sort the thousands of individual lines to support the experts and enable them to spend their time most efficiently; it is not a tool to replace expert judgment.There will always be examples where the criticality assigned by the tool is inappropriate, for example there may be a pipeline that transmits the whole of the production from the BU, but may not go through an environmentally sensitive area or contain H2S. This may not be rated by the tool as the highest criticality, but clearly because the impact on production is so great the expert can identify it as being of the highest criticality and over-ride the prioritisation tool accordingly. It is cases like this where the expert that knows the field in particular is needed to ensure that the correct decisions are made.This data is used by the TNK-BP subsidiaries to identify the pipelines in their fields that have the biggest failure risk and ensure that their activities are focused to mitigate these risks. In addition the data is used by the corporate centre to objectively determine which subsidiaries require larger proportions of funds due to the state and nature of their pipeline systems.It was applied to the following classifications of pipeline:Production wells flowlinesOil gathering linesHigh pressure oil gathering linesLow pressure waterlinesHigh pressure waterlinesLow pressure gas linesHigh pressure gas lines Keywords: flowline corrosion, oilfield chemistry, Corrosion Inhibition, offshore pipeline, materials and corrosion, riser corrosion, Midstream Oil & Gas, well integrity, category, Corrosion Management Subjects: Production Chemistry, Metallurgy and Biology, Pipelines, Flowlines and Risers, Materials and corrosion, Offshore pipelines, Well Integrity, Subsurface corrosion (tubing, casing, completion equipment, conductor), Corrosion inhibition and management (including H2S and CO2) This content is only available via PDF. 2006. 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