Joint exploration and development: A self-salvation road to sustainable development of unconventional oil and gas resources

Zheng, Lihui; Wei, Panfeng; Zhang, Zheng; Nie, Shuaishuai; Lou, Xuanqing; Cui, Kai; Fu, Yuwei

doi:10.1016/j.ngib.2017.09.010

Cited by 19 publications

(6 citation statements)

References 13 publications

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“…Here, APPI as well as the combined methods display the highest carbon and DBE distribution with 10–69 carbon atoms and DBE of 1–40, and 14–54 carbon number with 1–26 DBE number, respectively. ESI shows the least number of carbon atoms as well as DBE distribution …”

Section: Resultsmentioning

confidence: 99%

“…In order to meet the world's energy needs, the use of unconventional oil resources (extra‐heavy oil, oil sands, shale oils or tight oil) is strongly increasing . Incorporation of heavier crude oils into the market has gained great attention since their upgrading is cost intensive . Their high viscosity and chemical complexity cause various environmental and industrial problems during production, transportation and refinery .…”

Section: Introductionmentioning

confidence: 99%

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Evaluation of the combination of different atmospheric pressure ionization sources for the analysis of extremely complex mixtures

Kondyli

Schräder

2020

Rapid Comm Mass Spectrometry

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Rationale Characterization of complex samples remains a challenging task due to the high number of compounds present. Matrix effects, ion discrimination and suppression are limiting factors which force the use of different methods for the same sample to gain a broad understanding of complex mixtures. Methods Various ionization techniques such as electrospray ionization (ESI), atmospheric pressure photoionization (APPI) and atmospheric pressure chemical ionization (APCI) have been used in various problems for complex mixture analysis. Especially demanding is the analysis of energy‐related hydrocarbon mixtures, such as crude oil. Here, the different ionization sources alone and in combination with each other have been used on an ultrahigh resolution Orbitrap mass spectrometer to study a light crude oil. Results Despite the great variety of the available ionization sources, there is no single technique which can fully characterize the crude oil. Each ionization technique shows a selectivity towards specific types of compounds. While ESI is the method of choice for the detection of polar compounds, APPI and APCI favor the detection of nonpolar and low‐to‐medium polar compounds, respectively. The combination of ESI/APPI favors hydrocarbons and oxygen‐containing species. Conclusions Combining different ionization methods can be used as an alternative in order to gain more information about compounds present in a complex mixture although a combination of different ion sources could enhance suppression effects.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Evaluation of the combination of different atmospheric pressure ionization sources for the analysis of extremely complex mixtures

Kondyli

Schräder

2020

Rapid Comm Mass Spectrometry

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“…One of the challenges that reservoir management, drilling, and exploitation of oil and gas resources, and finally energy management have always faced is achieving decent productivity with the least amount of cost (Zheng et al, 2017;Abad et al, 2022). One of the most important reservoirs in the oil and gas industry is natural fracture reservoirs.…”

Section: Introductionmentioning

confidence: 99%

Prediction of fracture density in a gas reservoir using robust computational approaches

Gao

Hazbeh²,

Davoodi³

et al. 2023

Front. Earth Sci.

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One of the challenges that reservoir engineers, drilling engineers, and geoscientists face in the oil and gas industry is determining the fracture density (FVDC) of reservoir rock. This critical parameter is valuable because its presence in oil and gas reservoirs boosts productivity and is pivotal for reservoir management, operation, and ultimately energy management. This valuable parameter is determined by some expensive operations such as FMI logs and core analysis techniques. As a result, this paper attempts to predict this important parameter using petrophysics logs routinely collected at oil and gas wells and by applying four robust computational algorithms and artificial intelligence hybrids. A total of 6067 data points were collected from three gas wells (#W1, #W2, and #W3) in one gas reservoir in Southwest Asia. Following feature selection, the input variables include spectral gamma ray (SGR); sonic porosity (PHIS); potassium (POTA); photoelectric absorption factor (PEF); neutron porosity (NPHI); sonic transition time (DT); bulk density (RHOB); and corrected gamma ray (CGR). In this study, four hybrids of two networks were used, including least squares support vector machine (LSSVM) and multi-layer perceptron (MLP) with two optimizers particle swarm optimizer (PSO) and genetic algorithm (GA). Four robust hybrid machine learning models were applied, and these are LSSVM-PSO/GA and MLP-PSO/GA, which had not previously used for prediction of FVDC. In addition, the k-fold cross validation method with k equal to 8 was used in this article. When the performance accuracy of the hybrid algorithms for the FVDC prediction is compared, the revealed result is LSSVM-PSO > LSSVM-GA > MLP-PSO > MLP-GA. The study revealed that the best algorithm for predicting FVDC among the four algorithms is LSSVM-PSO (for total dataset RMSE = 0.0463 1/m; R2 = 0.9995). This algorithm has several advantages, including: 1) lower adjustment parameters, 2) high search efficiency, 3) fast convergence speed, 4) increased global search capability, and 5) preventing the local optimum from falling. When compared to other models, this model has the lowest error.

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“…Since global oil and gas consumption grows continuously, conventional oil and gas development alone cannot meet social needs [1]. Therefore, unconventional oil and gas reservoirs, which cannot be developed conventionally, are receiving more and more attention [2,3]. In China, unconventional oil and gas resources are widely distributed in Sichuan, Songliao, Ordos Junggar, and other basins, offering considerable development potential and broad prospects [4][5][6][7].…”

Section: Introductionmentioning

confidence: 99%

Stress Sensitivity of Proppant-Containing Fractures and Its Influence on Gas Well Productivity

Chen

Wei²,

Cheng³

et al. 2023

Geofluids

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Formation pressure gradually decreases with fracturing fluid flowback and gas production. Due to the stress sensitivity of the fractures, the permeability of the artificial fractures after fracturing becomes lower, which significantly affects gas well productivity. This paper focuses on two questions: (1) the stress sensitivity of proppant-containing fractures with different roughness and (2) tight gas well productivity considering stress sensitivity. Two types of artificial fracture samples, smooth and rough, are prepared and filled with different proppant concentrations. Then, the changing confining pressure method is used to quantify sample stress sensitivity. On this basis, the productivity equation for the fractured well with finite conductivity that considers fracture and matrix stress sensitivity is derived, and the influence of stress sensitivity on productivity is discussed. The results show that proppant concentration and fracture surface roughness will significantly affect fracture permeability and stress sensitivity; with increasing proppant concentration, fracture permeability increases, stress sensitivity decreases, and well productivity increases; under the same proppant concentration, the stress sensitivity is lower and the gas production is higher for smooth fracture; and when the artificial fracture changes from no proppant to proppant, the productivity of the fracturing well is improved the most.

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Joint exploration and development: A self-salvation road to sustainable development of unconventional oil and gas resources

Cited by 19 publications

References 13 publications

Evaluation of the combination of different atmospheric pressure ionization sources for the analysis of extremely complex mixtures

Evaluation of the combination of different atmospheric pressure ionization sources for the analysis of extremely complex mixtures

Prediction of fracture density in a gas reservoir using robust computational approaches

Stress Sensitivity of Proppant-Containing Fractures and Its Influence on Gas Well Productivity

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