Search Results (3)

Hydraulic fracturing, or fracking, requires large amounts of water to extract fossil fuel from rock formations. As a result of hydraulic fracturing, the briny wastewater, often termed back-produced fracturing or fracking water (FW), is pumped into holding ponds. One of the biggest challenges with produced water management is controlling microbial activity that could reduce the pond water’s reusable layer and pose a significant environmental hazard. This study focuses on the characterization of back-produced water that has been hydraulically fractured using chemical and biological analysis and the development of a high-throughput screening method to evaluate and predict the antimicrobial effect of four naturally and commercially available acidic inhibitors (edetic acid, boric acid, tannic acid, and lactic acid) on the growth of the FW microbiome. Liquid cultures and biofilms of two laboratory model strains, the vegetative Escherichia coli MG1655, and the spore-forming Bacillus atrophaeus (also known as Bacillus globigii, BG) bacteria, were used as reference microorganisms. Planktonic bacteria in FW were more sensitive to antimicrobials than sessile bacteria in biofilms. Spore-forming BG bacteria exhibited more sensitivity to acidic inhibitors than the vegetative E. coli cells. Organic acids were the most effective bacterial growth inhibitors in liquid culture and biofilm. Full article

Accurate well productivity prediction plays a significant role in formulating reservoir development plans. However, traditional well productivity prediction methods lack accuracy in tight gas reservoirs; therefore, this paper quantitatively evaluates the correlations between absolute open flow and the critical parameters for Linxing tight gas reservoirs through statistical analysis. Dominant control factors are obtained by considering reservoir engineering theories, and a novel machine learning-based well productivity prediction method is proposed for tight gas reservoirs. The adaptability of the productivity prediction model is assessed through machine learning and field data analysis. Combined with the typical decline curve analysis, the estimated ultimate recovery (EUR) of a single well in the tight gas reservoir is forecasted in an appropriate range. The results of the study include 10 parameters (such as gas saturation) identified as the dominant controlling factors for well productivity and geological factors that impact the productivity in this area compared to fracturing parameters. According to the prediction results of the three models, the R² of Support Vector Regression (SVR), Back Propagation (BP), and Random Forest (RF) models are 0.72, 0.87, and 0.91, respectively. The results indicate that RF has a more accurate prediction. In addition, the RF model is more suitable for medium and high-production wells based on the actual field data. Based on this model, it is verified that the productivity of low-producing wells is affected by water production. This study confirms the model’s reliability and application value by predicting recoverable reserves for a single well. Full article

Mixtures of powders essentially differing in their particle morphology and size were applied to prepare polycrystals in a Y₂O₃-ZrO₂ system. An yttria–zirconia solid solution nanometric powder with a Y₂O₃ concentration of 3.5% was prepared by subjecting co-precipitated gels to hydrothermal treatment at 240 °C. The crystallization occurred in distilled water. The pure zirconia powders composed of elongated and sub-micrometer size particles were also manufactured through the hydrothermal treatment of pure zirconia gel, although in this case, the process took place in the NaOH solution. Mixtures of the two kinds of powder were prepared so as to produce a mean composition corresponding to an yttria concentration of 3 mol%. Compacts of this powder mixture were sintered, and changes in phase composition vs. temperature were studied using X-ray diffraction. The dilatometry measurements revealed the behavior of the powder compact during sintering. The polished surfaces revealed the microstructure of the resulting polycrystal. Additionally, the electron back scattering diffraction technique (EBSD) allowed us to identify symmetry between the observed grains. Hardness, fracture toughness, and mechanical strength measurements were also performed. Full article