Weathered and fractured crystalline basement is known as the important unconventional reservoir in the Cuu Long Basin. Naturally fractured reservoir plays a crucial role in oil exploration to contribute for hydrocarbon production in Vietnam. However, the complexity and heterogeneity of the fractures system in the basement reservoir are challenges for oil and gas production. They require the realistic simulation scenarios to estimate the hydrocarbon potential as well as field development plan of these reservoirs. Thus, this paper aims to propose the feasibility development scenarios to improve oil recovery factor for crystalline basement reservoir, X field, Cuu Long Basin, Vietnam. First, history matching process is validated for the model to fit the actual production data (reservoir pressure, pressure, water cut in each well) in order to approach closer the fluid flow behavior through the reservoir. The manual matching was selected to adjust the actual aquifer size and permeability distribution with limit simulation runs. Next, the highest reliability matching model which approximately reflects the actual fluid flow behavior can be used as the base case to forecast the future reservoir performance through the field development plan. The most potential scenario is to add six new infill production wells, two side track wells and two water injection wells. The forecasted results indicate that this scenario yields 8% more oil recovery factor compared to the natural drive with thirteen producers. This result suggests that the precise field development plan is to increase the efficiency of the production process by increasing the displacement parameters of residual oil and reservoir sweep efficiency by stimulation. The major contribution of this paper demonstrates the merits of the field development plan in fractured basement reservoir. The findings of this study can help better understand the fluid flow behavior using the production history profiles and field development scenarios of crystalline basement reservoir of Cuu Long Basin.
Multi-point statistic method (MPS) can overcome the inherent disadvantages of traditional method based on variogram and object modeling, simultaneously allow the modeling progress, and become more flexible and rational. The algorithms based on variogram and gridding geological model are able to control the final result under the collection of samples' data (well data) and another corresponding data (seismic). Though, these methods have trouble in modeling the shape of geological features. Then, object-modeling method can generate digitized geological features with responsible shapes; conversely, a final result in accordance with an input data is difficult to achieve. Combining the advantages of two mentioned methods, MPS describes the relationship of data in space based on the group of adjacent points or has a certain relationship, it allows the generation of digitized geological features corresponding with responsible shapes, and moreover, it is able to control the final result under a collection of input data (whose nature is still the pixel-based). The Oligocene reservoir, X field, was formed in fluvial/lacustrine and sedimentary mainly deposited in Northwest-Southeast, which is primarily affected by latitude-sub-latitude faults' system. An Oligocene facies model of X field is built based on MPS, and it will show the geological features more clearly than the existing one. It also shows the remarkable ability on controlling the final result. MPS allows to combine a lot of different data (geology, seismic, outcrop, etc.) with the geological viewpoints which are shown by training image and itself proves the superiority over traditional methods. Duration of each model simulation is approximately 3000 s and huge size (over 15 million cells), and it is better while compared with 1717.8750 s in case of sequential simulation by SISIM method and default properties.
The paper presents the Kriging technique based on Matlab environment applied to interpolate the value of all points in the interpolation range from porosity values obtained from 13 wells of lower Miocene reservoir, ST Xam oil field. The MATLAB function meshgrids are used to create the interpolated cell (cell-Kriging) instead of point discrete interpolation. After selecting the Variogram model with nugget values and the correlation threshold (in scope), the next step is Kriging porosity values which regression permeability values. Finally, displays the values in the cells and interpolated coordinates X, Y, respectively. With input data the first mission is to analyze this set, select the necessary parameters and removal of useless data, and assess the scope of application of each type of data. Then combine the document with wellogging interpretation results to determine reservoirs and the layered in which filter out the corresponding data averaging and conducting. Based on the selected average value of the corresponding products in each well for each subclass, calculate the results of an empirical Variogram model as the basis for Kriging weighted matrix. The last work is to calculate error and evaluate the reliability of the Kriging results. The error of porosity model are minor and distributed apropriately with kriging range. However the results are numerous correlation. The permeability experiment results are collected just from 03 points, therefore the ultimate solution is recurred porosity from porosity Kriging results.
Pour Point Depressant (PPD) Testing are used extensively to modify the crystallinity of hard waxes and to reduce the natural pour point of crude. The best PPD chemical and best dosage for crude oil treatment will be chosen based on the laboratory test results to: Reduce pour point of crude oil; Reduce viscosity of crude oil; Improve rheological properties of crude oil; Reduce wax deposition rate and pipeline restart pressure. The chemical performance evaluation for PPD, proposed to use at X Oil Field has been conducted in Crude oil and Petroleum products Lab. The following properties have been determined in laboratory for blank sample (which is a mixture of H1, H4 and H5 crude oil samples with ratio of 2.1:1.4:1.0) and sample treated by PPD (rundown crude oil sample): Pour Point (for blank sample and treated sample); Wax Appearance Temperature (WAT) and Wax Disappearance Temperature (WDT) (for blank sample); Dynamic Viscosity (for blank and treated samples); Yield Stress by Rheometer (for blank and treated samples) for 100 mins, 1000 mins and 02 days shut-in times; Wax Deposition Rate by Cold Finger for blank and treated samples; Restart Pressure by Restart Loop (for blank and treated samples) for 100 mins, 1000 mins and 02 days shut-in times.
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