The Oil Industry

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In the oil industry, well testing is a very useful tool to be able to model and interpret what processes are going on underground in a reservoir system and what effect it would have if drilled into. From well testing, it is quite common to observe a pressure transient derivative signature showing an upward continuous trend. These types of curves are presented by a pressure derivative versus time log-log scale plot in different software’s with KAPPA being an example. This trend can be interpreted as showing the presence of nearby no flow boundaries. However, comparing this data with such seismic and geological evidence it is often concluded that these such boundaries appear too close to the well. Another possibility to explain this type of…show more content…
The objectives of this study are to: 1. Simulate reservoir production of 100% water with no oil or gas production. 2. Observe reservoir production when water and oil is being produced at a constant rate. 3. Observe reservoir behaviour when heterogeneity is introduced and multiple reservoir parameters are altered to observe different well test pressure derivative response curves in KAPPA. The initial model was based on the fact the reservoir was a homogeneous, corner point, Cartesian model which had no oil and gas production initially but produced water at a constant rate of 10000 m3/day for a period of 31 days. This model then was then compared analytically with KAPPA to see if the data matched the data that was inputted. The next step was to add oil into the system to be able to give a more relevant model to real life scenarios otherwise the data used beforehand was meaningless and couldn’t be representative of a real life scenario. To accomplish this and to simulate with the initial conditions, the rate was reduced due to the introduction of a bubble point pressure of 150 bar and an oil production rate along with a water production rate. Finally, the last objective of this simulation was to change the properties of the reservoir to make it become heterogeneous and then comparing the derivative response curve with those of the parameters such as: change

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