Opportunities and Challenges of Antelope Shale Development in $50 Oil Price Environment - A Case Study

Abstract

The Antelope Shale reservoir, a member of the Monterey Formation in the San Joaquin Valley, offers unique opportunities and challenges. The reservoir comprises three silica phases: Opal A (Diatomite), Opal CT, and Quartz. While the industry has been successful in producing from Opal A (Diatomite) via cyclic steam operations, the resources in the Opal CT and Quartz phases are yet to be commercially established. The recoverable oil estimate from the Monterey was downgraded by the Energy Information Administration (EIA) by 96% from approximately 15 billion barrels to 600 million barrels. Elk Hills and North Shafter have been successfully producing from the Antelope Shale reservoir. However, the reservoir rock and fluid properties are varied such that extrapolation from one field to the other is difficult. The Opal CT and Quartz commingled completion and stimulation in the McKittrick field showed encouraging initial production response followed by steep decline and operational challenges. In general, deep drilling and stimulation is expensive in San Joaquin Valley. Industry learning has been slow, less data is available for quality data analytics, which in turn impacts the learning process. In a brown field dominated heavily by thermal recovery processes, unconventional development gets challenged due to higher cost, longer lead times, and relatively poor economics. A typical unconventional resource field takes 4-5 years for achieving optimal development strategy. In a $50 oil price business environment, incremental progress in not enough. We need breakthroughs. It is imperative to optimize the pilot phase and early economic learning for sustainability of the project In this paper, we discuss the case study of a pilot project wherein four vertical wells were drilled in the McKittrick field. The results showed opportunities for a bigger development plan but were challenged by operational issues, limited analog data set, higher cost, poor economics, and comparison with traditional heavy oil projects. We will also discuss some additional improvement opportunities including imbibition, and drawdown management that have been theoretically established elsewhere and, if applied, could add value to improve the project economics.

Digital transformation of industrial businesses: A dynamic capability approach

“…However, for industrial businesses, the problem lies not in making such devices, but in digitizing the business to be at the forefront of controlling digital platforms and digital industrial equipment, and in transforming from a product-based business model to one that incorporates live services within their machines. For example, in healthcare, traditional software focused on medical records and document management is being replaced by cloud computing with instantaneous access to patients' data; in supply chain management (Ben-Daya et al, 2019;Calatayud et al, 2018), "self-thinking supply chains" based on IoT and AI-ML enable firms to receive supply chain events from different partners and suppliers, analyzing those events, and take proactive business decisions; in shipping, IBM and Maersk have a blockchain-based system to trace container shipping (Lal and Johnson, 2018); in airlines, the automated cockpit grows increasingly complex and substitutes for traditional piloting (Casner et al, 2014). Yet, the danger, let alone opportunity, posed by IIoT for industrial businesses is especially sharp.…”