Journal of Petroleum Science and Technology
Volume:13 Issue: 2, Spring 2023

In this study, in order to know the effective petroleum system in charging reservoirs in oilfields located in the west of Dezful Embayment, the cutting shales from Pabdeh, Kazhdumi, and Garau formations (Cretaceous-Paleogene Source Rocks) were selected for Rock-Eval Pyrolysis, Organic Petrography, Bulk, and Compositional kinetic. Furthermore, the Pabdeh shale samples are described as a mixture of kerogen types II and III with lower thermal maturity. The Kazhdumi shale samples show Type III and Type II/III kerogens and fall within the oil window zone. In addition, the Garau shale samples are determined to have Type III and Type II/III kerogens with high thermal maturity in the zone of the oil window. The bulk and compositional kinetic parameters reveal that the organic facies of the Kazhdumi and Garau formations indicate thermally mature kerogens able to generate and expel mature oils, but the Pabdeh Formation does not have enough maturity for oil generation. The composition kinetic model demonstrates that the Pabdeh and Kazhdumi formations are very similar in pyrolysate composition to the Garau Formation (due to the high sulfur in the kerogen of the Garau Formation). Finally, the Garau Formation is the main source rock, and the Kazhdumi Formation is the second one for filling hydrocarbon reservoirs in the studied area.

Predictive models employing random forest regression and support vector machines (SVMs) were developed to predict output parameters in an industrial natural gas sweetening plant. Extensive data comprising 550 input/output variables from a gas processing facility in western Iran was leveraged to construct and evaluate the models. The key output forecast was rich amine loading (mole of acid gas per mole of amine). The dataset was partitioned into training (80%), optimization (10%), and testing (10%) subsets after normalization. An R-squared value of 0.97 and a Mean Absolute Error (MAE) of 0.008 were achieved by the random forest regression, outperforming SVM’s R-squared score of 0.91 with an associated MAE of 0.012. Furthermore, the random forest model was optimized using particle swarm optimization (PSO), a metaheuristic technique. The pivotal innovation entails exploiting comprehensive empirical data with hundreds of variables to build data-driven models capable of exceptional predictive fidelity exceeding 0.9 R-squared. This research establishes random forest regression, especially after optimization with PSO, as a highly efficacious and robust methodology for the simulation and optimization of natural gas treating plants

Fischer-Tropsch synthesis is a direct method to produce fuels with low aromatic and sulfur content. Among various types of catalysts used for Fischer-Tropsch synthesis, the perovskite catalysts are more effective in a wide range of chemical reactions and have significant applications for gas-solid reactions. This study investigates the application of LaFe(1−x)CoxO3 perovskite catalyst with various Co to Fe ratios in Fischer Tropsch synthesis. The perovskite oxides are prepared via the sol-gel method and characterized using temperature-programmed reduction (H2-TPR), X-ray diffraction (XRD), Transmission electron micrographs (TEM), and BET surface area techniques. In addition, the catalyst is tested in a fixed bed reactor at 240, 260, 280, and 300 °C and 20 barg pressure. The results show that the crystal structure of LaFe(1−x)CoxO3 perovskite catalyst is changed and demonstrated high activity due to the iron active site; therefore, by increasing the amount of iron catalyst structure shifts to the orthorhombic and the CO conversion increases noticeably. Results show that the LaFe0.7Co0.3O3 catalyst at 280 °C is a possible candidate for Fischer-Tropes synthesis.

Wellbore stability is dominated by in-situ stress and geomechanical parameters of formation rocks, so estimating these parameters around the wellbore is important. The studied well is a suitable candidate for investigation of wellbore stability due to continuing directional drilling and planning for oriented perforation and hydraulic fracturing program from the wellbore and availability of dipole sonic, nuclear magnetic resonance (NMR), core image, and log data to optimize and estimate wellbore stability conditions. In this study, the rock permeability is derived from dipole sonic analysis to investigate the certainty of the model; these results are compared with NMR and special core analysis results. Then, based on these results, pore pressure, in-situ stress, rock mechanical properties, stress and fracture distributions, and anisotropy of formation are calculated and compared with Image log Results. Finally, the optimum mud weight to avoid wellbore failure can be estimated from all these data. As the final results, the maximum horizontal stress direction is N33E, and most open fractures are in this direction. The minimum horizontal stress direction is in N57W, and the safe and appropriate mud weight is between 6.5 and 7.5 ppg, which can be considered 7 ppg. This technique is based on dipole sonic analysis that can be applied to investigate wellbore stability in intervals with no core or image log analysis.

Feed streams of natural gas refineries and petrochemical industries contain mercury traces, threatening the environment and human health. Moreover, brazed aluminum heat exchangers are susceptible to being attacked by this component. The current research discusses the mercury removal capacities of alumina-based sorbents containing copper sulfide as an active metal. Cat-A and MRU-4 are synthesized and characterized using XRD, BET, TEM, XRF, and LECO methods. The experiments were carried out by loading the sorbents in a fixed-bed reactor, and they were sulfided by using a nitrogen gas stream containing 8 mol% of H2S at the temperature of 285oC. Then, their mercury removal capacities are measured at the temperature of 60 oC, pressure of 1 atm, and gas flow rate of 220 cm3/min versus time. Results showed that Cat-A and MRU-4 sorbents reached their static adsorption capacities of 12.1 and 19.3 wt%, respectively. Moreover, mercury adsorption variations of sorbents against time indicate that MRU-4 had faster dynamic adsorption than Cat-A sorbent. Ultimately, the characterization results also confirmed that the structures of MRU-4 and Cat-A adsorbents were mesoporous and microporous, respectively.

The main aim of this study is to simulate and optimize an integrated industrial natural gas (NG) to polypropylene (PP) plant (NGTPP). The optimization in this study aimed to increase the PP productivity as an objective function of the optimization problem. This plant consisted of four subunits: NG to synthesis gas, synthesis gas to methanol, MTP , and PTPP  units. After sensitivity analysis of all possible effective parameters, reformer temperature(TRef.gas), methanol reactor temperature(TMeOH), methanol reactor pressure (PMeOH), hydrocarbon return flow ratio to methanol reactor (RHC), PP reactor temperature(TPPR), PP reactor pressure(PPPR), Ticl4(MTicl4) and TEA(MTEA) inlet flow to PP reactor have been selected. These parameters were optimized using the Sinus-Cosine Algorithm(SCA). Optimal obtained results showed that the TRef.gas, TMeOH, PMeOH, RHC, TPPR, PPPR, MTicl4, and MTEA equal 875.53 0C, 225.91 0C, 140.87 bar, 0.7, 55.19 0C, -1.96 bar, 107.97 kg/h, and 3.93 kg/h, consequently. Maximum PP productivity was 7058.85 kg/hr at the optimum point.