An experimental study to measure oil recovery factor by chemical agents and carbon dioxide after waterflooding.

Development of tight formations would be one of the main priority for petroleum industries due to the enormous demand to the fossil fuels in various industries. In this paper, we provided a set of experiments on the generated foams by carbon dioxide (CO2) and nitrogen (N2), cyclic CO2 injection, water alternating gas injection (WAG), active carbonated water injection (coupling surfactant effects and carbonated water (CW)), and introducing the impact of active carbonated water alternating gas injection (combination of WAG and CW injection) after waterflooding. Carbon dioxide is more feasible than nitrogen, it can be mobilize more in the pore throats and provided higher oil recovery factor. Generated foam with CO2 has increased oil recovery factor about 32% while it's about 28% for generated foam by N2. Moreover, according to the results of this study, the maximum oil recovery factor for active carbonated water alternating gas injection, active carbonated water injection, and water alternating gas injection measured 74%, 65%, and 48% respectively.

Reliability Analysis of the New Exponential Inverted Topp-Leone Distribution with Applications.

The inverted Topp-Leone distribution is a new, appealing model for reliability analysis. In this paper, a new distribution, named new exponential inverted Topp-Leone (NEITL) is presented, which adds an extra shape parameter to the inverted Topp-Leone distribution. The graphical representations of its density, survival, and hazard rate functions are provided. The following properties are explored: quantile function, mixture representation, entropies, moments, and stress-strength reliability. We plotted the skewness and kurtosis measures of the proposed model based on the quantiles. Three different estimation procedures are suggested to estimate the distribution parameters, reliability, and hazard rate functions, along with their confidence intervals. Additionally, stress-strength reliability estimators for the NEITL model were obtained. To illustrate the findings of the paper, two real datasets on engineering and medical fields have been analyzed.