A numerical sensitivity analysis of streamline simulation
MetadataShow full item record
Nowadays, field development strategy has become increasingly dependent on the results of reservoir simulation models. Reservoir studies demand fast and efficient results to make investment decisions that require a reasonable trade off between accuracy and simulation time. One of the suitable options to fulfill this requirement is streamline reservoir simulation technology, which has become very popular in the last few years. Streamline (SL) simulation provides an attractive alternative to conventional reservoir simulation because SL offers high computational efficiency and minimizes numerical diffusion and grid orientation effects. However, streamline methods have weaknesses incorporating complex physical processes and can also suffer numerical accuracy problems. The main objective of this research is to evaluate the numerical accuracy of the latest SL technology, and examine the influence of different factors that may impact the solution of SL simulation models. An extensive number of numerical experiments based on sensitivity analysis were performed to determine the effects of various influential elements on the stability and results of the solution. Those experiments were applied to various models to identify the impact of factors such as mobility ratios, mapping of saturation methods, number of streamlines, time step sizes, and gravity effects. This study provides a detailed investigation of some fundamental issues that are currently unresolved in streamline simulation.
accuracy in streamline
gravity effect in streamline
Chaban Habib, Fady Ruben (2004). A numerical sensitivity analysis of streamline simulation. Master's thesis, Texas A&M University. Texas A&M University. Available electronically from
Showing items related by title, author, creator and subject.
Streamline Tracing and Time of Flight Diagnostics for Waterflooding Optimization: Theory and Application Chen, Rongqiang (2015-09-15)The objective of this work is to demonstrate the power and utility of streamline-based methods for flow diagnostics and waterflooding optimization. The robustness and high efficiency of the new post-simulation streamline ...
Fast history matching of finite-difference model, compressible and three-phase flow using streamline-derived sensitivities Cheng, Hao (Texas A&M University, 2006-10-30)Reconciling high-resolution geologic models to field production history is still a very time-consuming procedure. Recently streamline-based assisted and automatic history matching techniques, especially production data ...
Mohamed Ibrahim Daoud, Ahmed (Texas A&M University, 2006-04-12)Conditioning geologic models to production data and assessment of uncertainty is generally done in a Bayesian framework. The current Bayesian approach suffers from three major limitations that make it impractical for ...