Testing page for app

Although polymer flooding has become a promising enhanced oil recovery (EOR) technique, no field tests have been performed to date in Alaska’s underdeveloped heavy-oil reservoirs.

Most history-matching studies have fixed resources—that is, the team of engineers and geoscientists is predetermined. Moreover, the deadlines are always very strict. This constrained scenario often leads to an unfortunate result: The quality of the study suffers.

The complete paper describes piloting the collection and analysis of distributed temperature and acoustic sensing (DTS and DAS, respectively) data to characterize flow-control-device (FCD) performance and help improve understanding of steam-assisted gravity drainage (SAGD) inflow distribution.

The industry increasingly relies on forecasts from reservoir models for reservoir management and decision making. However, because forecasts from reservoir models carry large uncertainties, calibrating them as soon as data come in is crucial.

The results of the authors’ research showed promising benefits from the use of a systematic procedure of model diagnostics, model improvement, and model-error quantification during data assimilations.

The complete paper explores the use of multilevel derivative-free optimization for history matching, with model properties described using principal component analysis (PCA) -based parameterization techniques.

In 2019, the US experienced the lowest natural gas prices since 2016. This was despite natural gas consumption increasing in the residential and commercial sector by 2% (between October and December) according to the US Energy Information Administration.

The complete paper presents an integration of geology, geohazards, geophysics, and geotechnical assessments for a design of an offshore gas production facility and an associated export pipeline.

This paper analyzes the risk of hydrate formation and blockage, aiming at various gas/liquid flow patterns and considering the phase distribution and interface distribution characteristics of different flow patterns.

The synopses in this feature show how machine learning can provide accurate prediction of annular pressure buildup, first-year oil production, and (in conjunction with novel casing accessories) the time and location of water breakthrough along a lateral wellbore.