Interaction between technology and extraction scaling real options in natural gas production

Abstract

This article is the outcome of a research engagement studying questions of technology utilization and production management with managers at EQT Corp., an integrated natural gas production and distribution company. The question of how to best leverage the use of technology is fundamental to almost any industry; this is especially true for those companies operating in the volatile field of commodities production, as does EQT Corp.. This article considers the interaction between two types of real options that arise in natural gas production: The option to scale the production level, through enhanced extraction and communication technologies, and the option to scale the extraction rate, by pausing production. This interaction is studied by applying stochastic dynamic programming to actual operational and financial data. The analysis brings to light data-driven managerial principles pertaining to the valuation and deployment of these three scaling options, the effect of price uncertainty on the option values, how to effectively simplify the optimal deployment policy, and whether these options, or subsets of them, are complements or substitutes. These principles are significant to natural gas production managers and, potentially, to managers of other natural resource production processes, such as the extraction of oil and mining.

A Discussion of Non‐Gaussian Price Processes for Energy and Commodity Operations

“…Work that exemplifies the latter category comprises Deng (1999), Smith and McCardle (1999), Enders et al. (2010), Hu et al. (2015), Aflaki and Netessine (2017), Boyabatli et al.…”

Pathwise Optimization for Merchant Energy Production

“…Our research is potentially relevant for other commodity merchant operations contexts and related real option models (Secomandi andSeppi 2014, 2016), including oil and natural gas extraction fields, liquefied natural gas facilities, copper mines, and renewable energy plant (Brennan and Schwartz 1985, Smith and McCardle 1998, 1999, Smith 2005, Cortazar et al 2008, Rømo et al 2009, Enders et al 2010, Lai et al 2011, Arvesen et al 2013, Denault et al 2013, Hinz and Yee 2018, Zhou et al 2019. The use of PCA as a preconditioning technique may have applicability in mathematical programming beyond our specific application.…”

Comparison of least squares Monte Carlo methods with applications to energy real options

“…Our focus in this paper is on real options, in particular energy real options. Applications include process innovations (Khansa and Liginlal 2009), manufacturing flexibility (Triantis andHodder 1990, Fontes 2008), capital budgeting (Gamba 2003), renewable energy investments (Boomsma et al 2012), and commodity and energy acquisition, disposal, processing, production, storage, and swing assets (Barbieri and Garman 1996, Smith and McCardle 1998, 1999, Maragos 2002, Jaillet et al 2004, Thompson et al 2004, Brandão et al 2005, Smith 2005, Boogert and De Jong 2008, 2011/12, Cortazar et al 2008, Hahn and Dyer 2008, 2011, Carmona and Ludkovski 2010, Enders et al 2010, Lai et al 2010, Secomandi 2010, Wang and Dyer 2010, Adkins and Paxson 2011, Devalkar et al 2011, Felix and Weber 2012, Chandramouli and Haugh 2012, Thompson 2012, Wu et al 2012, Arvesen et al 2013, Denault et al 2013, Mazières and Boogert 2013, Secomandi and Seppi 2014, Chapters 5-7, Bäuerle and Riess 2015, Gyurkó et al 2015, Nadarajah et al 2015.…”