No abstract

No abstract

ANN Model was developed utilizing experimentally determined MMP data of 201 reservoir oil and CO2 injected gas. The data bank was randomly divided into training (70%) and testing parts (30%). The conventional statistical measures like coefficient of determination (R2), root mean square error (RMSE) and mean absolute error (MAE) were used to evaluate the predictive efficiency of the model and correlation. Cross-plot of predicted values versus the predicted data was also made to examine the accuracy of developed model. All the important parameters that affect MMP were considered in developing ANN model. These parameters include reservoir temperature, reservoir oil compositions and properties of heptane plus and composition of N2, C1, H2S in the injected CO2 gas stream. The results showed that developed correlation and ANN model can predict the MMP value with high R2, low RMSE and low MAE. The values of R2, RMSE and MAE are 0.9469, 218.7832 and 175.8902 respectively for testing data points. The presented technique can be used to provide an estimate of the MMP in the absence of experimental data and should be utilized in the initial screening of CO2 miscible flooding process. A novel correlation using artificial neural network (ANN) to predict MMP has been developed in this study. The MMP plays an important role in designing the miscible gas flooding processes and to plan appropriate surface injection facilities. MMP is traditionally measured through experimental and non-experimental techniques. The experimental methods are expensive and time consuming and results from currently used correlations vary significantly and hence there is need of reliable, easy and fast prediction technique.

An approach for post-frac production profiling has been presented in this study by integrating a fracture model with a reservoir simulation model for a well drilled in tight sand reservoir of Lower Indus Basin in Pakistan. The presented integrated approach couples the output from the fracture growth model with a reservoir simulation model to effectively predict the behavior of a fractured reservoir. Optimization of hydraulic fracturing was done efficiently through the work presented in this study. The integrated model was used to perform various sensitivities. The production profiles obtained for each case were subsequently used to determine the most profitable case, using an economic model.

Pakistan has not been yet able to exploit its huge shale resources pertaining to uncertainness of potential reserves, appropriate technology, and commercial extraction. The exploitation of these shale resources can significantly fulfill the evergrowing energy need of Pakistan. This study assesses the economic feasibility of emerging shale gas plays in Pakistan by employing a reservoir analog approach to the US shale formations that are closely related to the shale formations in Pakistan. The aim is to eliminate the associated economic uncertainties of the future shale gas projects of Pakistan and to provide guidance for the early assessment of emerging shale gas plays with no production history or previously drilled wells. Recommendations for the economically viability of shale gas plays in Pakistan have also been prepared from this study. Economic model was developed based on discounted cash flow method. Sensitivity analysis of different financial (royalty rates and corporate tax rate) and well construction and stimulation parameters (drilling, completion, hydraulic fracturing, well-testing, and well tie-in costs) were performed to evaluate their effect on the net present value (NPV). Results showed that production from Pakistan shale gas resource using existing technology is economically feasible with the break-even gas price of $11.35/Mscf if operators received financial incentives on royalty and taxes from government. With prevailing tax regime, the hydrocarbon extraction from the proposed field is financially expensive and risky with the gas prices ranges between $18.77/Mscf and $53/Mscf for different financial scenarios. It was found that hydrocarbon extraction from the proposed shale gas field is economically viable with the combination of favorable financial incentives and technological advancements.