Use of Risk-Based Criteria for Characterization of Environmental Remediation Liabilities in Upstream Oil and Gas Production Facilities. 13th Annual International Petroleum Environmental Conference, San Antonio, TX
Authors: J. Connor, R. Bowers, S. Maberti, J. Mejia, K. Ravishankar, S. Alvarez
This paper describes a unique approach for use of the ASTM Risk-Based Corrective Action (RBCA) process to establish baseline environmental conditions, classify environmental risks, and predict the potential remediation costs associated with historical oilfield operations, as part of an environmental due diligence performed for upstream oil and gas production facilities in Colombia. This risk-based due diligence process allowed prioritization and characterization of sites based on key risk and cost drivers. The methodology facilitated identification of remedial action strategies and development of an appropriate remedial action schedule, based upon inspection and review of a representative sample of the oilfield facilities, for an oilfield consisting of 1710 well sites, 7 active production stations, 76 abandoned substations, 2 crude oil dehydration plants, and a gas processing plant distributed over an area of 190 square kilometers. Within the limited time available for the due diligence, the approach facilitated completion of the property transaction and allocation of reserves as escrows in project negotiations to the satisfaction of all parties involved.
For this due diligence effort, site inspections were conducted at a representative percentage of each type of oilfield facility to identify site conditions posing concern in terms of “primary risk factors” (human health or safety) or “secondary risk factors” (i.e., impacts on ecological resources, water resources, land use, or regulatory compliance issues). Observed conditions were then characterized according to the RBCA classification system to define the relative magnitude of the risk posed and the relative urgency of need for a response action. For each type of oilfield installation, these data comprised a “risk distribution,” defining the key risk drivers and the frequency of occurrence of higher risk (Class 1) vs. lower risk (Class 2, 3, or 4) conditions. These risk distributions were then used to predict the probability of encountering similar conditions within the balance of sites not inspected during the due diligence process, as well as to establish an overall schedule and budget for remedial actions (i.e., addressing high-priority conditions in the near-term and lower-priority conditions at a later time).