Machine learning-based fracturing parameter optimization for horizontal wells in Panke field shale oil

In the process of developing tight oil and gas reservoirs, multistage fractured horizontal wells (NFHWs) can greatly increase the production rate, and the optimal design of its fracturing parameters is also an important means to further increase the production rate. Accurate production prediction is essential for the formulation of effective development strategies and development plans before and during project execution. In this study, a novel workflow incorporating machine learning (ML) and particle swarm optimization algorithms (PSO) is proposed to predict the production rate of multi-stage fractured horizontal wells in tight reservoirs and optimize the fracturing parameters. The researchers conducted 10,000 numerical simulation experiments to build a complete training and validation dataset, based on which five machine learning production prediction models were developed. As input variables for yield prediction, eight key factors affecting yield were selected. The results of the study show that among the five models, the random forest (RF) model best establishes the mapping relationship between feature variables and yield. After verifying the validity of the Random Forest-based yield prediction model, the researchers combined it with the particle swarm optimization algorithm to determine the optimal combination of fracturing parameters under the condition of maximizing the net present value. A hybrid model, called ML-PSO, is proposed to overcome the limitations of current production forecasting studies, which are difficult to maximize economic returns and optimize the fracturing scheme based on operator preferences (e.g., target NPV). The designed workflow can not only accurately and efficiently predict the production of multi-stage fractured horizontal wells in real-time, but also be used as a parameter selection tool to optimize the fracture design. This study promotes data-driven decision-making for oil and gas development, and its tight reservoir production forecasts provide the basis for accurate forecasting models for the oil and gas industry.

Fit-for-purpose treatment goals for produced waters in shale oil and gas fields

Hydraulic fracturing (HF), or "fracking," is the driving force behind the "shale gas revolution," completely transforming the United States energy industry over the last two decades. HF requires that 4-6 million gallons per well (15,000-23,000 m³/well) of water be pumped underground to stimulate the release of entrapped hydrocarbons from unconventional (i.e., shale or carbonate) formations. Estimated U.S. produced water volumes exceed 150 billion gallons/year across the industry from unconventional wells alone and are projected to grow for at least another two decades. Concerns over the environmental impact from accidental or incidental release of produced water from HF wells ("U-PW"), along with evolving regulatory and economic drivers, has spurred great interest in technological innovation to enhance U-PW recycling and reuse. In this review, we analyze U-PW quantity and composition based on the latest U.S. Geographical Survey data, identify key contamination metrics useful in tracking water quality improvement in the context of HF operations, and suggest "fit-for-purpose treatment" to enhance cost-effective regulatory compliance, water recovery/reuse, and resource valorization. Drawing on industrial practice and technoeconomic constraints, we further assess the challenges associated with U-PW treatment for onshore U.S. operations. Presented are opportunities for targeted end-uses of treated U-PW. We highlight emerging technologies that may enhance cost-effective U-PW management as HF activities grow and evolve in the coming decades.

Geochemical and microbial characterizations of flowback and produced water in three shale oil and gas plays in the central and western United States

Limited understanding of wastewater streams produced from shale oil and gas wells impedes best practices of wastewater treatment and reuse. This study provides a comprehensive and comparative analysis of flowback and produced water from three major and newly developed shale plays (the Bakken shale, North Dakota; the Barnett shale, Texas; and the Denver-Julesburg (DJ) basin, Colorado) in central and western United States. Geochemical features that included more than 10 water quality parameters, dissolved organic matter, as well as microbial community structures were characterized and compared. Results showed that wastewater from Bakken and Barnett shales has extremely high salinity (∼295 g/L total dissolved solids (TDS)) and low organic concentration (80-252 mg/L dissolved organic carbon (DOC)). In contrast, DJ basin showed an opposite trend with low TDS (∼30 g/L) and high organic content (644 mg/L DOC). Excitation-emission matrix (EEM) fluorescence spectra demonstrated that more humic acid and fluvic acid-like organics with higher aromaticity existed in Bakken wastewater than that in Barnett and DJ basin. Microbial communities of Bakken samples were dominated by Fe (III)-reducing bacteria Geobacter, lactic acid bacteria Lactococcus and Enterococcus, and Bradyrhizobium, while DJ basin water showed higher abundance of Rhodococcus, Thermovirga, and sulfate reducing bacteria Thermotoga and Petrotoga. All these bacteria are capable of hydrocarbon degradation. Hydrogenotrophic methanogens dominated the archaeal communities in all samples.

Investigation of different chemical modifiers based on the Pd/Mg mixture for the determination of sulfur in shale oil by high-resolution continuum source graphite furnace molecular absorption spectrometry

This study investigated different combinations of Pd/Mg, as chemical modifier, for sulfur determination, via CS molecule, in shale oil samples by high-resolution continuum source graphite furnace molecular absorption spectrometry (HR-CS GF MAS). It was evaluated the mixture Pd/Mg in aqueous solution, Pd/Mg in propan-1-ol and the Pd/Mg in propan-1-ol plus Ru as a permanent modifier. The best sensitivity was achieved with Pd/Mg mixture in propan-1-ol. The high solubility of the samples in propan-1-ol promotes a better interaction with the modifier and, consequently, a more efficient thermal stability of the CS molecules. Due to the high sulfur content in the samples, the analytical line at 258.288 nm was used. Only a minimum sample preparation was required, i.e., a dilution in propan-1-ol by a factor of 1:10 (w/w). Temperatures of 800 °C and 2200 °C were the optimized conditions for pyrolysis and vaporization, respectively. The calibration curve was constructed with l-cysteine aqueous standard solutions. The characteristic mass was 27 ng; detection and quantification limits were 0.012% (w/w) and 0.039% (w/w), respectively. The accuracy of the proposed method was confirmed by the statistical agreement (Student's and Welch's t-test at 95% confidence level) using the certified reference material CRM NIST 1084a and an OTE oil sample whose sulfur content was previously determined by the standard method ASTM D4294. The method was successfully applied in three shale oil samples. The sulfur content in the investigated samples ranged from 1.0% (w/w) to 1.3% (w/w).

Volatile-organic molecular characterization of shale-oil produced water from the Permian Basin

Growth in unconventional oil and gas has spurred concerns on environmental impact and interest in beneficial uses of produced water (PW), especially in arid regions such as the Permian Basin, the largest U.S. tight-oil producer. To evaluate environmental impact, treatment, and reuse potential, there is a need to characterize the compositional variability of PW. Although hydraulic fracturing has caused a significant increase in shale-oil production, there are no high-resolution organic composition data for the shale-oil PW from the Permian Basin or other shale-oil plays (Eagle Ford, Bakken, etc.). PW was collected from shale-oil wells in the Midland sub-basin of the Permian Basin. Molecular characterization was conducted using high-resolution solid phase micro extraction gas chromatography time-of-flight mass spectrometry. Approximately 1400 compounds were identified, and 327 compounds had a >70% library match. PW contained alkane, cyclohexane, cyclopentane, BTEX (benzene, toluene, ethylbenzene, and xylene), alkyl benzenes, propyl-benzene, and naphthalene. PW also contained heteroatomic compounds containing nitrogen, oxygen, and sulfur. 3D van Krevelen and double bond equivalence versus carbon number analyses were used to evaluate molecular variability. Source composition, as well as solubility, controlled the distribution of volatile compounds found in shale-oil PW. The salinity also increased with depth, ranging from 105 to 162 g/L total dissolved solids. These data fill a gap for shale-oil PW composition, the associated petroleomics plots provide a fingerprinting framework, and the results for the Permian shale-oil PW suggest that partial treatment of suspended solids and organics would support some beneficial uses such as onsite reuse and bio-energy production.