Private-equity-backed tech startups are fostering change in the oil and gas space with innovative, disruptive technology. Many investors have turned to transformative technologies to enable digitalization and improve returns. Given the current price environment, harnessing digital technologies has proven to be a critical part of survival.
As many oil and gas companies look for solutions to help cut costs, Investor profiled three forward-thinking digital technology startups that are moving through the energy industry and helping streamline operations, boost efficiencies and maximize production.
Data Gumbo, a Houston-based industrial blockchain company, has developed a trusted transactional network, GumboNet, to automate smart contracts for the energy industry.
Established in 2015, Data Gumbo was originally an Internet of Things platform used for aggregating and cleaning data for oil and gas companies that struggled to get a clean view of data across multiple sources.
However, after identifying a multimillion-dollar cost-saving opportunity to eliminate a sizable inefficiency between an oil supermajor and one of its suppliers, CEO Andrew Bruce developed GumboNet, an industrial blockchain network that provides a single transactional record.
The underlying issue in the transactional ecosystem, he said, is that data are interpreted differently between operators, E&P companies and service providers. This discourse complicates data coordination and ramps up expenses.
Data Gumbo acts as a neutral infrastructure that uses field data to confirm the execution of pre-agreed contracts to prevent disputes and automate contract execution. This enables parties on both sides of the transaction to significantly reduce their operating expenses.
“Blockchain provides a direct measure of the value you want to gain from a contract,” Bruce said.
By using field data to verify contract terms, the network eliminates interpretation differences and facilitates automated calculation, reconciliation and payment of invoice line items with total transparency. GumboNet cuts 5% to 10% on average out of contract costs and, in some cases, up to 25%, according to Bruce.
“E&Ps can save millions of dollars from automating transactions because it eliminates contract leakage, reconciliation expenses, and they can negotiate discounts and do daily accruals … if you add all of that up, then you will see double digit million-dollar savings on your opex,” he said.
The startup is financially backed by Saudi Aramco’s venture arm, Saudi Aramco Energy Ventures, and Equinor Technology Ventures, the venture subsidiary of Equinor. In May 2019, the company completed a $6 million equity funding round co-led by the venture firms. The round brought Data Gumbo’s total funding to $9.3 million.
Operators in the Permian and Bakken oil fields have adopted GumboNet. Last year, Austin-based Antelope Water Management LLC tapped GumboNet to provide real-time transparency and contract automation across its water infrastructure, treatment, sourcing and disposal services. This marked the first use of a blockchain platform for water management services in U.S. shale plays.
Data Gumbo provides third-party oversight to Antelope’s water quality and water volumes, an important capability that prompted the company to enter the deal, according to Antelope CEO Dustin Brownlow. Cost savings from this project are about $4 million annually, Bruce said.
In the Bakken, the OOC Oil & Gas Blockchain Consortium piloted the technology for water haulage services in a bid to lower administrative costs while reducing payment disputes and chances for fraud. The consortium includes oil and gas majors Chevron Corp., ConocoPhillips Co., Exxon Mobil Corp., Equinor ASA and Royal Dutch Shell Plc, among others.
GumboNet will replace a manual transaction system with automated payments, which could generate $3.7 billion annually in cost savings for the water business, according to Bruce.
In the Gulf of Mexico, the company is working with a large oil company to track drilling equipment, personnel on board and drilling fluids using blockchain.
In March 2020, Data Gumbo entered the global market when specialized drilling and project management services provider Air Drilling Associates (ADA) installed the application on a project in Southeast Asia. GumboNet will automate execution and invoice payments for ADA’s integrated project management contracts, including personnel, consumables and drilling tools.
This project is the first use of blockchain in geothermal energy drilling, adding to the company’s list of successful endeavors.
“This is the prime time for this technology in the market when everyone is doing everything they can to remove all of their opex. At this point, companies desperately need technologies like GumboNet to drive down the costs from their operations,” Bruce said. “Data Gumbo’s network enables companies to gain access to that hidden value within their organization.”
GumboNet utilizes a subscription-based model, which alleviates pressure on companies to build and sustain an in-house blockchain model from scratch. Bruce notes that the integration of technology poses little to no risk because there is the option to unsubscribe; it does not involve cryptocurrency and mining like other blockchain platforms; and there are no upfront costs.
“Users have the ability to pick up profits that go straight to their bottom line by cutting expenses from their existing operations using an industrial blockchain that is subscription-based, so you don’t have to spend a bunch of time and money trying to figure out how it works or how to implement it,” he said.
Data Gumbo intends to drive the adoption of blockchain and help establish its legitimacy as a linchpin technology in industrial business relationships.
“Blockchain will have a major impact on the oil and gas industry—and all global industries—and we will lead the charge in its broad adoption for sweeping operational improvements,” Bruce said.
Novi Labs Inc.
Formed in 2014, Austin-based software company Novi Labs Inc. emerged on the scene with capital from Bill Wood Ventures and, later, equity investment firm Cottonwood Venture Partners.
Novi’s cloud-based technology leverages large-scale datasets and machine learning algorithms to predict and analyze economic outcomes for oil and gas investments. Novi’s mission is to help operators design and drill wells that are more profitable by solving the challenges of well planning, and Jon Ludwig, president and co-founder of Novi, has led the company’s efforts to do that on a global scale.
To date, Novi’s technology has been deployed in every major shale basin, including the Delaware and Midland basins, the Williston Basin, the Appalachian Basin, the Denver-Julesberg Basin, Oklahoma’s SCOOP/ STACK, the Montney Formation, the Duvernay Shale, Eagle Ford Shale and Argentina’s Vaca Muerta Formation.
In May 2019, the startup closed a $7 million series A funding round with Cottonwood and Bill Wood Ventures. Novi deployed the funds toward scaling its team and software platform to meet the demands of shale producers and investors.
In Novi’s beginning stages, the company developed a partnership with Hess Corp. that resulted in the field trial and implementation of Novi’s software on Hess’ Williston Basin asset during Ludwig’s tenure with the corporation.
The full-scale project gave Ludwig firsthand experience with applying machine learning algorithms and large-scale datasets to the problem of unconventional development optimization. It also provided him with insight into the economic disparities that operators experience from well development.
Witnessing the pressure of running 10 to 20 drilling rigs at once and a massive ramp up in capital, Ludwig saw how the pace of shale development put significant strain on planning workflows and software tools for operators and their decision-making apparatus overall. There was simply not enough automation and efficiency to keep up with the pace of development.
“Most of the workflows and tools in the pre-drill decision-making process are fairly archaic, manual and tedious. The pace of decision-making in unconventional plays drives it beyond the breaking point and leads to suboptimal decisions,” he said.
Novi developed its well planning software to address this issue. The technology targets three use cases: fully automated producing well forecast, A&D evaluation and, at the core, return on capital optimization.
Novi’s solution combines machine learning driven predictive analytics with multiple well design inputs, capital costs and commodity price assumptions to model the financial performance of a well over time, enabling shale producers to optimally allocate capital and mitigate risks for development projects.
Given the present supply and demand shocks, Ludwig anticipates that A&D evaluation will be the most important use case for Novi’s software, as it adds scale and efficiency to the evaluation workflows for potential acquisitions.
“The A&D market is frozen now, but it will be robust after spring redeterminations,” he said. “Companies with strong balance sheets are going to see opportunities and private-equity sponsors are going to sponsor companies to go out and acquire assets.”
In January, Novi and Paramount Resources Ltd. formed a strategic partnership focused on increasing net asset values by enabling Paramount’s engineering teams to rapidly analyze all possible development scenarios to produce the most capital-efficient drilling plan.
The integration of Novi’s well planning suite into the workflows of the liquids-focused Canadian energy company will help quantify and predict changes to development scenarios resulting in improved capital allocation.
Traditionally, the industry’s approach to workflows utilizes spreadsheet driven type curves that provide a general prediction, assuming the completion design for all the wells in an area. This averaging methodology results in less accurate and biased results, according to Ludwig.
However, Novi’s software makes individual well forecasts and captures nonlinear and nonparametric data relationships. This shortens the processing timeline for capital allocation scenarios from a couple of months to a few hours.
“Most of our customers are looking to replace traditional manual, Excel-driven workflows with our software. So the efficiency difference is [over] 50%,” Ludwig said.
Additionally, the level of quality of the output is greatly improved with precise forecasts and a better understanding of performance drivers in a given basin. Novi’s workflows represent a much more accurate and efficient replacement to what operators—in most cases—manually use now, according to Ludwig.
In March, the company released Novi Prediction Engine version 2.0. The new software provides critical economic data to E&P workflows such as well planning or A&D. Users can run a wide range of large-scale scenarios in minutes and get immediate feedback on the economic feasibility of each plan.
Novi Prediction Engine was built to add efficiency and scale by simplifying the creation of “what if” scenarios that are key to reducing risks associated with maximizing return on capital and net asset value. It uses machine learning to automate resource intensive capital allocation based on a wide variety of inputs and enables parallel testing of spacing, stacking and stimulation intensity scenarios.
Novi plans to make the platform completely self-service in the future, allowing users to create datasets, run predictive models, propose large scale development or A&D valuation scenarios and evaluate the results—all in near real time.
“We want to unlock every possible scenario for companies in the industry, so more time is spent on evaluating the answers and determining the best scenario for the organization,” Ludwig said.
Driven by a commitment to “work hard and maximize return on investment” for its customers, Palo-Alto, Calif.-based ResFrac Corp.’s unique software has catapulted the company in the E&P sector in just two short years.
CEO Mark McClure quit his job as an assistant professor at the University of Texas at Austin and established the software startup company in 2015, going commercial in 2018, after observing a need in the marketplace for an integrated fracture and reservoir simulator.
“In shale you create the reservoir, and the fractures are the fundamental aspect of production. Having to separate them into different categories of software makes for a very awkward, incomplete workflow that could lead to the wrong answer,” McClure said.
With backing from venture capital firm Altira Group LLC, the company has successfully developed a fully integrated 3D, cloud-based hydraulic fracture and reservoir simulator. Through a single simulation, the technology helps shale operators model and solve conventional design problems surrounding frac hits, parent-child interactions and refracs before completing wells.
In traditional projects, the fracture simulation defines frac geometry and proppant placement, while the reservoir simulation would describe the multiphase flow and fluid production from the shale. By combining these capabilities, operators can capture the life-cycle of an unconventional well and directly compare frac designs on the basis of predicted production. Ultimately, this improvement helps preserve capital for operators by shortening the trial and error of unconventional development.
“The deliverable from a ResFrac project is a prediction of net present value for different decisions,” McClure said. “For example, once we’ve built a model and history-matched it, we'll run scenarios to see what the impact would be on NPV [net present value] if the spacing is changed. We literally plot NPV versus well spacing.”
In the current price environment, he said leveraging the ResFrac tool is critical for companies still drilling and fracturing because the optimal frac design changes based on the price of oil.
“At a time when companies are struggling to survive and maintain profitability, or at least minimize loss, it’s more important than ever to maximize their rate of return and that has to be done as smartly as possible,” he said. “Frac designs need to be revisited and reconsidered to adjust for the new price environment.”
Resfrac’s software serves roughly 25 E&P companies and has been applied across most major American shale plays including the Permian, Bakken, Eagle Ford, Marcellus, Duvernay and Vaca Muerte. The company has also completed case studies with Hess, QEP Resources Inc., Range Resources Corp., ConocoPhillips and Shell International Exploration and Production Inc.
But McClure said the study with Hess revealed the most significant issue that the company has seen in its entire lifecycle.
“We found that specifically in gas shales there is a tendency for a conventional DFIT [diagnostic fracture injection test] interpretation to come in with a permeability estimate that’s too high—very, very high,” he said. “Our follow-up paper with Hess, on their now-sold Utica asset, showed how the permeability estimate makes a huge impact on the optimization of the well spacing, so essentially we showed how a very common and widespread error is made in the DFIT interpretation in gas shales.”
These inaccurate permeability analyses lead to economically suboptimal well and cluster spacing designs, which result in a 30% to 40% difference in NPV, according to McClure.
Additionally, ResFrac performed an integrated parent-child study with Hess in the Bakken. The software successfully captured a complex series of production, reinjection, DFIT, a frac hit from and offset well and subsequent production uplift. With the results, the company was able to model parameters such as fracture toughness, permeability and proppant conductivity, which Hess leveraged to address other completion design scenarios.
“Parent-child interaction is one of the biggest issues that operators report as impacting their production, and we’re the only tool that can describe the physics of parent-child interactions in a complete way,” he said.
On top of these efficiencies, the modeling process requires geologists, reservoir engineers and completions engineers to all work together. “I think a lot of companies see the value in that as well,” McClure added.
In May, ResFrac closed a preferred share financing with Altira Group and debuted a new user interface that streamlines use and provides results that are more detailed. The company also reported a 250% growth in revenue last year as its customers doubled.
In the next year, the company intends to enhance the software with an advanced automation to the workflow. The idea is to create an algorithm that automatically runs ResFrac simulations for operators and returns a recommended optimum design or automatically matches a model to data.
“Our strategy is twofold: continue to invest and work hard on the product and, of course, try to continuously grow our market share and penetration … we want to be the No. 1 solution in this market segment, period.”
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