Testing page for app
-
This paper shows results from use of a new technology that uses in-well-conveyed fiber-optic distributed acoustic sensing (DAS) for the detection of sand-ingress zones across the reservoir section throughout the production period in real time.
-
This paper summarizes a technology using SMP to provide downhole sand control in openhole environments.
-
Unlike continuous gas injection and water-alternating-gas injection, gas-assisted gravity drainage (GAGD) takes advantage of the natural segregation of reservoir fluids to provide gravity-stable oil displacement.
-
This paper presents a method to compare the distribution of hypothesized and realized risks to oil wells described in two data sets that contain free-text descriptions of risks.
-
Production from sand-prone reservoirs is one of the more daunting tasks, with formidable challenges. Sand management and control remain as an old problem but with new challenges because of the suppressed oil and gas prices. Cost-saving and value-adding solutions are vital now more than ever.
-
This paper provides perspective on the current state of multizone completion technology and issues encountered in the industry with developing a system that offers increased capabilities to meet the increasing challenges presented by the Lower Tertiary in the Gulf of Mexico.
-
Emerging technologies from medical science and the aerospace industry could have a disruptive impact on oil and gas operations. A panel of scientists looked into these technologies and discussed their potential role in the industry.
-
Currently, there are few studies on smart waterflooding in tight and very tight oil reservoirs. This work examines smart-waterflood opportunities in such reservoirs.
-
Previous studies demonstrate that Montney rock samples present a dual-wettability pore network. Recovery of the oil retained in the small hydrophobic pores is uniquely challenging.
-
This study shows that dimensionless numbers, together with data-mining techniques, can predict field behavior in terms of recovery factor for sparse data sets.