سال انتشار: ۱۳۸۵

محل انتشار: اولین کنگره مهندسی نفت ایران

تعداد صفحات: ۲۳

نویسنده(ها):

Dr. Nasser Alizadeh – Assistant Professor, Amir-Kabir University of Technology

چکیده:

This paper describes a development strategy with peripheral water flood for S-reservoir, a
large oil bearing carbonate part of the Persian golf oil reservoirs.
The heterogeneity, discontinuity, size and different rock type characteristics of this
reservoir lead to a decisional divergence between development options.
In this paper it is explained how the sensitivity assessment and risk analysis can be used
to identify the most dominating risk component(s) with respect to the field productivity
and capability of meeting the oil production target. Once these dominating risk
components become known, we could: a) further optimize the field development by
properly formulating the drilling and completion strategy, b) re-prioritize the data
acquisition and reservoir characterization program to lessen the uncertainties and further
minimize the risks.
In this study we have used the Experimental Design Methodology to shorten the number
of simulation runs required for sensitivity assessment and risk analysis. The probability
analyses identify and rank the most sensitive parameters that help in field development:
maximize the exposure to the reservoir components that bring positive impact and
minimize those that have the negative impact on field recovery and economics.
The sensitivity analysis and risk assessment running concurrently with reservoir
simulation to develop a Pareto Chart for different reservoir parameters such as Kv/Kh
ratio, vertical transmissibility, horizontal transmissibility, residual oil saturation, aquifer
radius, aquifer permeability, skin factor and the location of the producers.
The most sensitive parameters with respect to oil recovery are identified for reassessment
and further improvement and optimization of the development plan. Data
acquisition program, reservoir performance evaluation and production injection strategies
are conducted with these sensitivities in mind. They are executed with the highest
priorities given to the most sensitive parameters.
Monte Carlo simulations again are run on periodic basis with actual field data input to
further optimize the development.