San Joaquin Valley SPE General Section Meeting
Portfolio Management and Optimization
An Extra 45 Minutes Can Provide
a World of Knowledge
Thursday, February 20th @ 11:30 AM
Petroleum Club, 12th Floor
5060 California Ave, Bakersfield, CA 93309
Speaker: Cedric Fraces, Director at Tenokonda
Reservations: RSVP by Feb. 17th to avoid walk-in fee
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- SPE member (early birds): $30
- non-SPE member (early birds): $35
- Students: FREE (if RSVP'd before walk-in deadline or normal walk-in charge will apply.
- Walk-in/registrations past Feb. 17th 2020: Add $5 ($35/$40)
Portfolio management and optimization theory emerged as a field of research in Economics in the 1950s. Original work by Harry Markowitz* investigated the theory and methodology that lead to a good trade-off between expected return and risk when picking within a set of investment alternatives. The mathematical formulation and the algorithms can be applied to the Oil and Gas industry where portfolio optimization is a central component of decision analysis under uncertainty. The goal is to determine the set of operational decisions that maximize the value of an asset subject to a series of constraints. This problem can be cast as a multi-objective optimization under non-linear constraints with correlated variables. The potentially very large number of possible scenarios to explore requires a sound quantitative method supported by a robust implementation.
Due to the complexity of subsurface risk factors modeling, optimizing investment portfolios for Oil & Gas exploration projects is a particularly challenging task. Traditional approaches typically suffer the following shortcomings:
- Over-simplify exploration events distributions.
- Ignore co-dependency on risk.
- Are computationally intensive preventing what-if analysis
The presentation will introduce portfolio theory and demonstrate an application of Tenokonda’s portfolio optimization library applied to exploration. The python library provides a unified framework for optimal decision making, incorporating joint modeling of geological risk factors and enabling drill down at various levels (asset, reservoir, prospect,…). The framework and derived workflows (see figure) are used by E&P companies for decision making and shows practical added value:
- accelerated investment decision making
- quantifies co-dependency risk
- what-if analysis
- drill-down capabilities
Cedric Fraces is a reservoir engineer with over 14 years of experience in the energy industry working as a field engineer, production engineer and data scientist. He has a proven record of designing industrial artificial intelligence solutions for international E&P companies (Chevron, TOTAL, Conoco Philips, CNPC, PEMEX, KOC, Ecopetrol).
Cedric has worked on major oilfields in the US, Canada, China, Iraq, Kuwait, Kazakhstan, Brazil, Mexico and Colombia and been involved in executive decisions concerning the development and management of corresponding assets. Cedric holds a master's degree in Energy Resources Engineering from Stanford University and is currently a Ph.D. candidate in Energy Resources Engineering at Stanford.