Possessing acreage in even the hottest of shale plays doesn’t necessarily guarantee a return on investment.
But a trio from Texas Standard Oil has devised a method to evaluate the economic potential of an asset. Relying heavily on data, their method goes beyond the conventional ways of building type curves based on production data from nearby horizontal wells in targeted areas.
“This works fine if only one bench is being targeted with a statistically significant number of wells, having somewhat uniform completions among the wells,” Texas Standard’s Abhishek Gaurav, Edward J. Gibbon and Timothy M. Roberson wrote in a paper they presented in February at the Society of Professional Engineers’ Canada Unconventional Resources Conference in Calgary. “The problem soon becomes complicated when multiple benches are being targeted with varying landing depths in each bench.”
Successfully navigating an abundance of data to decipher what impacts production could set the winners apart from the losers when it comes to acquiring shale assets. The team created a dashboard, which integrates various data analytics, to help E&Ps and other potential investors quickly identify factors that could affect production and ultimately, profits.
“Data mining integrated with available geological information assists in identifying the key parameters that affect well performance,” the authors wrote. “Once optimized for completions parameters, one can identify the real potential of an asset under consideration.”
The continuous push to optimize completions techniques—as operators pump more proppant, drill deeper and adjust spacing—could place a previously unattractive asset among the most desirable.
But completions are only one factor, according to the authors. Combine this with geological data such as reservoir pressure with information on faults, anticipated drilling costs and production type curves, and economic forecasting becomes less cloudy.
It helps that some of this data is publicly available from state agencies such as the Texas Railroad Commission or can be cobbled together from company reports.
“The aggregation of data on several wells feeds into the creation of a huge data-set, in other words, big data. Once a combination of above-mentioned factors is taken into account, the pattern identification process related to correlation of performance vs. parameters is quickly established,” the authors wrote. “The type curve, which corresponds to the optimum parameters for the particular area of interest, is then used for economic forecasting.”
Completion variables that factor into the economics include: proppant amounts, type of fracture fluid, stage length, the number of clusters per stage and perforation per cluster, to name a few.
Other areas to consider include depth changes, thickness of carbonate layers, faults, production methods and leasing costs.
“If it costs $50,000 per net acre in the core of any basin and the EURs for 3 economic benches are in the 1,000,000 BOE per well, 80% oil range; how does this compare to an area with a cost of $1,000 per net acre with 2 economic benches having EURs of 800,000 BOE per well, 44% oil range, in the same price environment for a different lateral length?,” the authors asked. “This comparison makes it imperative to integrate leasing cost with the AFE [authorization for expenditure] in the well economics or the project economic modeling for a more accurate evaluation.”
The company is currently developing unconventional assets in Permian, focusing on the Midland Basin’s Wolfcamp and Spraberry plays as well as the Delaware Basin’s Wolfcamp and Bone Springs. Gaurav is a completions engineer; Gibbon, vice president of reservoir engineering; and Roberson, president.
Gaurav said their work was well received during the conference, and they have received positive feedback from E&Ps, private-equity groups and others.