Don’t miss this SPE Distinguished Lecturer!
Two Vital Secrets for Building Better Type Wells
Thursday, November 17, 2016 @ 11:30 AM
San Joaquin Valley Section
Petroleum Club 12th Floor - 5060 California Avenue, Bakersfield
An Extra 45 Minutes Can Provide
a World of Knowledge
Reservations: RSVP by November 14th to avoid walk-in payment
Using the corresponding link below to pay online:
Online Payment Link
Email Jeff Kim at Jeff.Kim@CRC.com
Each year, companies use averaged well production (type wells) to support billion dollar expenditures to buy and develop oil and gas resources. These type wells often have unrepresentative rate-time profiles and recoveries over-stated by as much as 50%. These intolerable errors result from common, but incorrect, assumptions in constructing type well production profiles, and the selection and weighting of analog wells.
Literature related to constructing type wells is sparse and incomplete. This lecture will fill that gap and lead participants to informed decisions for best practices in type well construction. Hind casting examples show that only small errors in recovery result when the type well construction combines historical and predicted production rates. This improvement results from using educated estimates (not intrinsic values) for months with no data to average, and from individual well forecast errors that offset one another. A Monte Carlo method incorporates risk and leads to better well selection and weighting factors, achieving more representative rate-time profiles. The recommended methodology incorporates aggregation and choosing different uncertain parameters. Parameter choice is important because it makes little sense to risk recovery (e.g., P90 for proved reserves) when the application demands a different parameter such as present value.
Type well construction methods are common, but they have errors that are difficult to detect. Evaluators are likely using type wells for financial analysis, facility design, cash flow prediction, reserve estimation and debt financing without knowledge of the inaccuracies and options to improve accuracy.
Randy Freeborn is a subject matter expert in the field of empirical forecasting, type wells and related technology. Currently, he is Chief Research Engineer at Energy Navigator where he is responsible for identifying and inventing engineering technology for inclusion in the company’s reserve management software. He has been a professional engineer for 44 years and is a member of SPEE and SPE. Freeborn has prepared numerous technical papers for presentation at conferences, workshops and industry meetings. He has given guest lectures at the University of Houston and Texas A&M, and has been called as an expert witness.