Currently the "Pump and Dump" method employed by Exploration and
Production (E&P) companies in deepwater is simply not enough to control increasingly
dangerous and unpredictable shallow hazards. "Pump and Dump" requires a heavy
dependence on accurate seismic data to avoid shallow gas zones; the kick detection
methods are slow and unreliable, which results in a need for visual kick detection; and it
does not offer dynamic well control methods of managing shallow hazards such as
methane hydrates, shallow gas and shallow water flows. These negative aspects of
"Pump and Dump" are in addition to the environmental impact, high drilling fluid (mud)
costs and limited mud options.
Dual gradient technology offers a closed system, which improves drilling simply
because the mud within the system is recycled. The amount of required mud is reduced,
the variety of acceptable mud types is increased and chemical additives to the mud
become an option. This closed system also offers more accurate and faster kick
detection methods in addition to those that are already used in the "Pump and Dump"
method. This closed system has the potential to prevent the formation of hydrates by
adding hydrate inhibitors to the drilling mud. And more significantly, this system successfully controls dissociating methane hydrates, over pressured shallow gas zones
and shallow water flows.
Dual gradient technology improves deepwater drilling operations by removing
fluid constraints and offering proactive well control over dissociating hydrates, shallow
water flows and over pressured shallow gas zones. There are several clear advantages for
dual gradient technology: economic, technical and significantly improved safety, which
is achieved through superior well control.
| Identifer | oai:union.ndltd.org:tamu.edu/oai:repository.tamu.edu:1969.1/4441 |
| Date | 30 October 2006 |
| Creators | Elieff, Brandee Anastacia Marie |
| Contributors | Schubert, Jerome J. |
| Publisher | Texas A&M University |
| Source Sets | Texas A and M University |
| Language | en_US |
| Detected Language | English |
| Type | Book, Thesis, Electronic Thesis, text |
| Format | 2554566 bytes, electronic, application/pdf, born digital |
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