Model for economic evaluation of closed-loop geothermal systems based on net present value

Xiao, Dianshi; Liu, Mingjie; Li, Li; Cai, Xueliang; Qin, Shiyin; Gao, Ruoyu; Liu, Jianhong; Liu, Xiantao; Tang, Haijun; Gao, Li

doi:10.1016/j.applthermaleng.2023.121008

Cited by 61 publications

(10 citation statements)

References 97 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Some of the researchers in the sub-surface characterization of diversified systems have made significant works for the development of the most sophisticated workflows such as the analysis of water level inside the drilled wells, analyzing the anomalies and ion diffusion in shale reservoirs, economic evaluation of closed-loop for the geothermal systems, spaceborne multispectral subsurface Reflectance analysis, global karst carbon sink bathymetric mapping etc. [ [29] , [74] , [75] , [76] , [81] , [82] ]. These plays can be structural, stratigraphic and/or a combination of these two regimes.…”

Section: Discussionmentioning

confidence: 99%

Appraisal of reservoir quality for hydrocarbon-bearing deep-water Miocene sandstones incised valley, south-east Asian offshore Indus: An application of seismic attributes and instantaneous spectral porosity quantitative reservoir simulations

Naseer,

Singh,

Khalid

et al. 2024

Heliyon

View full text Add to dashboard Cite

Section: Discussionmentioning

confidence: 99%

Appraisal of reservoir quality for hydrocarbon-bearing deep-water Miocene sandstones incised valley, south-east Asian offshore Indus: An application of seismic attributes and instantaneous spectral porosity quantitative reservoir simulations

Naseer,

Singh,

Khalid

et al. 2024

Heliyon

View full text Add to dashboard Cite

“…The success of global economy largely dependst on energy sources, particularly electricity, and availability. A country’s economic and political stability also hinges on the energy sector, particularly the exploration and availability of hydrocarbons, which are essential for development, prosperity, and nation building. − …”

Section: Introductionmentioning

confidence: 99%

“…A country’s economic and political stability also hinges on the energy sector, particularly the exploration and availability of hydrocarbons, which are essential for development, prosperity, and nation building. 4 − 6 …”

Section: Introductionmentioning

confidence: 99%

Geochemical Evaluation of Paleocene Source Rocks in the Kohat Sub-Basin, Pakistan

Sohail,

Mehmood,

Jahandad

et al. 2024

ACS Omega

View full text Add to dashboard Cite

The Kohat sub-basin is one of the main hydrocarbon-producing sedimentary basins located in the northwest extension of the Indus Basin in Pakistan. It contains numerous proven and potential petroleum from the Cambrian to the Miocene. Conventional petroleum resources have been depleting rapidly over the last couple of years. Therefore, unconventional resources should be explored using a variety of geochemical and geophysical techniques to address the energy demands. Geochemical techniques, including total organic carbon (TOC) assessment, Rock-Eval pyrolysis, organic petrography, and biomarker studies, are essential for evaluating the potential of shale gas reservoirs to delineate future prospects in a basin. The source rock potential of the Paleocene rocks, including the Patala, Lockhart, and Hangu formations of the sub-basin, is evaluated using geochemical analyses on well cuttings from the Tolanj-01 well. The analyses include estimation of total organic carbon (TOC), Rock-Eval pyrolysis, and organic petrography (vitrinite reflectance) to evaluate the organic richness, thermal maturity, kerogen type, hydrocarbon type, and environment of deposition. Other techniques for extractable organic matter (EOM) include solid−liquid chromatographic separation of fractions, gas chromatography (GC-FID)/whole oil chromatography, and gas chromatography−mass spectrometry (GC-MS). The organic matter (TOC, wt %) analysis reveals that 18 (18) samples of the Hangu formation (0.08−1.8 wt %) show poor values, 12 (12) samples of the Lockhart formation (0.05−0.5 wt %) have poor to fair content, and 26 (26) samples of the Patala formation have poor to fair (0.08−0.19 wt %) TOC content. Rock-Eval pyrolysis studies including hydrogen index, oxygen index, T max , quantities of free hydrocarbons (S 1 , mg/ g), and hydrocarbons produced from pyrolysis (S 2 , mg/g) are determined for the well-cut samples (56) of the Paleocene rocks. The hydrogen index values for the Hangu formation are lower than 200, and those for the Lockhart and Patala formations range between 100 and 250. A maceral analysis is also conducted on these samples, which reveal that the majority of the samples of the Paleocene units present in the basin belong to kerogen types II/III. The thermal maturity of the Hangu and Lockhart formations falls in the late-stage oil window, while that of the Patala formation falls in the peak to late oil window. The genetic potential (GP) for these rock units is also determined based on S 1 and S 2 values, which reveals that it is generally poor except for a few samples of the Hangu and Lockhart formations, which show fair GP values. For the organic petrography (vitrinite reflectance, R 0 ), one sample from each unit is selected, which shows that the Hangu, Lockhart, and Patala formations fall in the category of the mature oil window with their R 0 (%) values being 0.95, 0.89, and 0.82, respectively. The extracts (EOM) from these rock units are also analyzed to assess the depositional settings, biological source input, biodegradation, thermal ...

show abstract

“…Studies on EOR methods have shown that there are more than twenty types of different EOR techniques 6 with and imbalanced frequency of the EOR techniques. Employing an inappropriate recovery technique could result in permanent damage to the reservoir and substantial financial losses and environmental hazards 7 . Therefore, a precise and dependable EOR screening process is crucial in the initial stages of reservoir development.…”

Section: Introductionmentioning

confidence: 99%

Application of power-law committee machine to combine five machine learning algorithms for enhanced oil recovery screening

Yousefzadeh,

Kazemi,

Al-Maamari

2024

Sci Rep

View full text Add to dashboard Cite

One of the main challenges in screening of enhanced oil recovery (EOR) techniques is the class imbalance problem, where the number of different EOR techniques is not equal. This problem hinders the generalization of the data-driven methods used to predict suitable EOR techniques for candidate reservoirs. The main purpose of this paper is to propose a novel approach to overcome the above challenge by taking advantage of the Power-Law Committee Machine (PLCM) technique optimized by Particle Swam Optimization (PSO) to combine the output of five cutting-edge machine learning methods with different types of learning algorithms. The PLCM method has not been used in previous studies for EOR screening. The machine learning models include the Artificial Neural Network (ANN), CatBoost, Random Forest (RF), K-Nearest Neighbors (KNN), and Support Vector Machine (SVM). The CatBoost is used for the first time in this work for screening of EOR methods. The role of the PSO is to find the optimal values for the coefficients and exponents of the power-law model. In this study, a bigger dataset than those in previous studies, including 2563 successful worldwide EOR experiences, was gathered. A bigger dataset improves the generalization of the data-driven methods and prevents overfitting. The hyperparameters of the individual machine-learning models were tuned using the fivefold cross-validation technique. The results showed that all the individual methods could predict the suitable EOR method for unseen cases with an average score of 0.868. Among the machine learning models, the KNN and SVM had the highest scores with a value of 0.894 and 0.892, respectively. Nonetheless, after combining the output of the models using the PLCM method, the score of the predictions improved to 0.963, which was a substantial increase. Finally, a feature importance analysis was conducted to find out the most influential parameters on the output. The novelty of this work is having shown the ability of the PLCM technique to construct an accurate model to overcome the class-imbalance issue in EOR screening by utilizing different types of data-driven models. According to feature importance analysis, oil gravity and formation porosity were recognized as the most influential parameters on EOR screening.

show abstract

Model for economic evaluation of closed-loop geothermal systems based on net present value

Cited by 61 publications

References 97 publications

Appraisal of reservoir quality for hydrocarbon-bearing deep-water Miocene sandstones incised valley, south-east Asian offshore Indus: An application of seismic attributes and instantaneous spectral porosity quantitative reservoir simulations

Appraisal of reservoir quality for hydrocarbon-bearing deep-water Miocene sandstones incised valley, south-east Asian offshore Indus: An application of seismic attributes and instantaneous spectral porosity quantitative reservoir simulations

Geochemical Evaluation of Paleocene Source Rocks in the Kohat Sub-Basin, Pakistan

Application of power-law committee machine to combine five machine learning algorithms for enhanced oil recovery screening

Contact Info

Product

Resources

About