IHS Markit has ‘harnessed the power’ of artificial intelligence (AI) to predict future production for each of the nearly one million currently producing oil and gas wells in its North American database. The results confirm the staggering rate of decline of US shale wells. Overall onshore production will decline by 35% during the next 12 months. This compares with base decline rates of 5% to 14% for global petroleum systems and under 15% a decade ago in the US.
Comparing 2017 to 2019, IHS Markit calculates that the onshore oil base decline (i.e. without taking account of new wells) nearly doubled. Base production declined by 1.8 million barrels of oil per day or 28% in 2017 and but will fall by a further 3.5 million bopd (35%) in 2019. HIS Markit’s Raoul LeBlanc commented ‘The treadmill that producers are fighting is moving very fast. As producers come under pressure to restrain investment, this decline rate is becoming the main factor that promises to slow the explosive US production growth we’ve witnessed the past few years.’
Russell Roundtree added, ‘Most engineers don’t have the time they once did to conduct in-depth, well-level, decline-curve analysis on even a handful of wells. The prospect of rapidly analyzing thousands of wells is attractive. This derived dataset becomes a valuable addition to the oil and gas community and to financial investors who need to assess a company’s risk and future performance.’
IHS adds, more positively, that while shale wells experience a ‘breathtaking plunge’ of 65% to 85% in first-year production, the dynamic (of steep declines) is sustainable because of high-initial productivity. Also, ‘much more intensive’ hydraulic fracturing is not generally leading to faster decline rates.
IHS’ AI-based tool ‘learns’ from adjacent wells in the same reservoir to improve forecasting accuracy. Analysis is also enhanced by automated partitioning a well’s history into meaningful stages, workover, re-stimulation, pump installation etc. The automated well forecasting technology detects changes to production patterns and makes a forecast using only relevant data. The technology is smart enough to recognize interventions and to compensate for them. Results are delivered via IHS’ Performance Evaluator package .
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