No abstract

We present the results of a paleoseismic trench investigation of an 8-m scarp at the mouth of Marbang Korong Creek (27°58'26.0700" N 95°13'42.3000" E) within the meizoseismal area of the 1950 Assam earthquake along the northeast Himalayan Frontal Thrust (HFT) of India. Structural, stratigraphic, and growthstratigraphy relations observed in the trench are interpreted to indicate that expression of the scarp is due to uplift and folding of near surface sediments in response to HFT displacement that reaches near the surface yet below the 5-m depth of the trench exposure. The most recent contribution to scarp growth dates to fault displacement post 2009 cal yr B.P. It remains a matter of speculation whether or not the most recent event deformation is a result of the great 1950 Assam earthquake that is reported on the basis of intensity data.

In viscous oil reservoirs, Polymer flooding is often used to improve oil recovery either after a short period of waterflooding or as a tertiary recovery process following extensive period of waterflood. After six years of water flooding in a major reservoir in Sultanate of Oman having viscous oil (90cp), a field development plan was developed to implement polymer flooding in this reservoir with anticipated incremental oil recovery of around 10% over and above that of waterflood. Necessary facilities were constructed, injection and production wells were drilled, completed, converted and the polymer flood project was initiated and ongoing since the last three years through 27 polymer injectors. By implementing proactive Well and Reservoir Management (WRM) strategies, the actual oil recoveries have been better than predicted levels so far. It is demonstrated here that proactive well and reservoir management through proper well and reservoir surveillance and dynamic adjustment of injection and production rates play a very important role in improving the performance of polymer floods as in waterfloods. Well and Reservoir Management (WRM) principles in case of a polymer flood are similar to that of high mobility ratio waterfloods with some additional aspects that are specific to a polymer flood scenario. Polymer chemical costs, its higher viscosity and non Newtonian fluid flow behavior all create unique conditions that are nonexistent in normal waterfloods. This, in turn, dictates the strategies and methods employed to optimize polymer flood performance. This paper details successful implementation of proactive WRM strategy that has played a key role in sustaining production from this polymer flood field to date. It describes the pattern management processes to optimize pattern wise polymer injection and oil recoveries, conformance control measures implemented to increase sweep and oil recovery, innovative surveillance techniques to monitor fracture growth in polymer injection wells and for evaluation and optimization of production/injection profiles. Production wells and facilities issues arising from polymer breakthrough are being addressed to mitigate any adverse effects.

A field scale polymer flood has been in operation since early 2010 in a major oil field of the Sultanate of Oman. The project comprises 27 patterns where water flood was on-going prior to initiation of Polymer flood in 2010. A polymer flood project has high chemical operating expenditure (Opex). Thus, optimization of a polymer flood requires continuous tracking of mass of polymer injected per unit volume of incremental oil produced for individual polymer flood patterns and then polymer throughput in individual patterns needs to be dynamically altered. To meet this objective, a full-field streamline simulation model has been built, history matched and is being used for optimizing the polymer-flood. Full-field simulation allows the proper modeling of each pattern and their interactions with off-set patterns, and these simulations can be performed in a reasonable computation time because of the efficiency of streamline modeling. Computational efficiency of streamline simulation has facilitated use of the model for routine well and reservoir management decisions. This would not have been possible with a finite difference model because of excessive run time and inability to clearly establish injection-production relationship as in a streamline model. The model has facilitated optimization of polymer flood patterns, specifically when to stop polymer injection, slug size, and slug concentration. Individual pattern performance can be visualized effectively and their efficiency can be compared. The model is also being used for ranking the existing water-flood patterns for the next phase of polymer-flood implementation and carrying out short term production forecast.

A field-scale polymer flood has been in operation since early 2010 in a major oil field of the Sultanate of Oman. The project is composed of 27 mature waterflood patterns that were converted to polymer flood in 2010. Because a polymer-flood project has high chemical operating expenditure, optimization of a polymer flood requires continuous tracking of the mass of polymer injected per unit volume of incremental oil produced (relative to waterflood) for each polymer-flood pattern. To meet these objectives, a fullfield streamline simulation model was built, was history matched, and is being used for optimizing the polymer flood. Full-field simulation allows the proper modeling of each pattern and their interactions with offset patterns. However, full-field simulations can be expensive, so we use a streamline-based simulator to run forecast scenarios in a reasonable computation time on reasonable hardware. Streamlines have the added benefit of determining the time-varying well-rate allocation factors per pattern, meaning that pattern-level diagnostics are relatively easy to compute and are based on the dynamic flow characteristics of the model. Computational efficiency and quantification of patterns have facilitated use of the model for routine well and reservoir-management decisions. We show that one can determine the effectiveness of the polymer flood on a pattern-by-pattern basis over the historical polymer-injection period with a standard oil-produced vs. polymer-injected ranking. In forecasting, we show how to quantify the incremental recovery caused by polymer, above base waterflood, on a pattern-by-pattern basis to facilitate optimization of polymer-flood patterns and more specifically to determine when to stop polymer injection and which new patterns to move polymer injection to.