It is often said that the cheapest oil a company owns is the remaining oil in its reservoirs that has not been produced. There is clear logic to that observation, as an oil company could avoid having to engage in the exploration and development work necessary to find the equivalent amount of oil that is known to remain underground. Rather, the oil company must only figure out how best to produce that remaining oil at a cost that doesn’t exceed its market value. In other words, oil companies need to always be striving to wring their reservoir rocks dry.

Engineers are finding that wringing out a reservoir means reimagining how they have traditionally operated. When the exploration department hands over a field to the production department, the qualities of the output are generally well established, meaning that they know whether the hydrocarbon has sufficient energy to flow to the surface without any assistance, or if it needs help to get there. If help is needed, they usually know whether a simple sucker rod pump, a downhole submersible pump (known as an ESP), a gas lift system, or another form of artificial lift is most appropriate. Many of those decisions were easy when wells were vertical, but horizontal wells have introduced new challenges that are not fully understood.

The primary responsibility of the production department is to optimize output while minimizing cost. Avoiding production failures and stopping the erosion of optimal well performance is critical, but the challenges are building as the number of horizontal wells grows, staffing is reduced, and the complexity of wells increases. Mechanizing data collection, employing artificial intelligence, and introducing machine learning to manage and optimize well performance helps producers address these challenges. Being open to operating differently, as a result of better knowledge, may be the key adjustment production staffs must make. Overcoming the challenge of “too many wells, too little time” requires a different mindset and likely software or digital tools to assist. The changing of this mindset may be a greater challenge than mastering the physics of producing wells.

For this Company Spotlight, we interviewed Ambyint Chief Executive Officer, Blake McLean, and Chief Commercial Officer, Chris Robart, about how Ambyint is helping E&P operators proactively optimize production across their entire organization rather than reacting to production problems as they arise. Ambyint delivers step-change improvements to E&P production outcomes and margins by combining advanced physics and subject matter expertise with artificial intelligence to automate operations and production optimization workflows across all well types and artificial lift systems. For more information on Ambyint, please visit www.ambyint.com.

Background: In 2004, Pumpwell Solutions was founded in Calgary by mathematicians that created a physics-based algorithm to optimize production from wells utilizing rod lift. At that time, the programmable logic controllers (PLCs) used in rod lift operations did not have the necessary computing power to handle their algorithm. Therefore, Pumpwell’s offering required an edge computing device (hardware installed in the field) that positioned it as a premium offering to customers. Nonetheless, Pumpwell’s solution was implemented on over 1,000 wells in Canada. In 2012, with artificial intelligence and machine learning becoming more prevalent, Pumpwell began to research and develop a more cost-effective and software-focused solution to optimize production, which led to the rebranding of the company to Ambyint in 2016. Today, Ambyint offers its optimization platform through both a hardware/software solution as well as a software-only offering across all well types and artificial lift systems.

Value Proposition: Over the last decade, the majority of technological advancements and efficiency gains achieved have been focused on drilling and completion activities. Now, E&P operators are starting to turn the attention to the production side of the equation. Currently, E&P operators’ activities classified under…..READ MORE

Isolated information silos within large E&P companies are very typical in the industry and prohibit collaboration and operational efficiency. Datagration’s solution to this issue, PetroVisor™, is an open-architecture software platform that aggregates and integrates data from disparate systems into one cloud-based (or on-premise) platform with built-in workflow solutions to provide real-time analytics.

The CarbonCure process involves injecting recycled CO2 into fresh concrete during mixing to create a chemical reaction whereby the CO2 is transformed into a mineral (calcium carbonate). Advantages of the process include reduced cost through the elimination of certain additives without comprising cement integrity and significant reduced CO2 emissions. CarbonCure intends to use the capital investment to accelerate its product roadmap and geographical expansion in order to achieve its goal of removing 500 megatons of carbon dioxide annually from the concrete industry by 2030.

This capital raise, which follows the company’s $25 million Series B raise in November 2019, brings the total to $75 million of equity and debt capital. Founded in 2017, GoExpedi’s innovative software procurement solution digitizes the supply chain, easing critical communication between field workers and management to create a fully transparent and integrated ecosystem.

Related Press Release: GoExpedi Secures $25 Million in Series C Funding

Energy Technology Musings

Wringing the Sponge Dry