Interpretation of production tests in geothermal wells with T2Well-EWASG

Vasini, Ester Maria; Battistelli, Alfredo; Berry, Paolo; Bonduà, Stefano; Bortolotti, Villiam; Cormio, Carlo; Pan, Lehua

doi:10.1016/j.geothermics.2017.06.005

Cited by 27 publications

(12 citation statements)

References 20 publications

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“…In the case of space, it is discretized to form basic differential equations. The TOUGH code has been continuously developed and successively validated for more than 35 years, as evidenced by the work initiated by Pruess [65][66][67][68] and subsequent numerous tests confirming its reliability based on benchmark experiments and multi-variant validation [69][70][71][72][73][74][75][76][77][78]. Therefore, the authors of this paper have based their work on previously conducted validations and focused only on model calibration based on available geological parameters.…”

Section: Numerical Methodology and Mathematical Modelmentioning

confidence: 99%

Assessment of the Effective Variants Leading to Higher Efficiency for the Geothermal Doublet, Using Numerical Analysis‒Case Study from Poland (Szczecin Trough)

et al. 2020

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Numerical models of geothermal doublet allows us to reduce the high risk associated with the selection of the most effective location of a production well. Furthermore, modeling is a suitable tool to verify possible changes in operational geothermal parameters, which guarantees liveliness of the system. An appropriate selection of software as well as the methodology used to generate numerical models significantly affects the quality of the obtained results. In this paper, the authors discuss the influence of such parameters as grid density and distance between wells on the efficiency of geothermal heating plant. The last stage of the analysis was connected with estimation of geothermal power potential for a hypothetical geothermal doublet. Numerical simulations were carried out using the TOUGH2 code, which applies the finite-difference method. The research was conducted in the Szczecin Trough area (NW Poland), based on archival data from Choszczno IG-1 well. The results demonstrated that in the studied case of the Choszczno region, the changes in the distance of boreholes can have a visible influence on obtained results; however the grid density of the numerical model did not achieve a significant impact on it. The results show the significant importance of numerical modeling aimed at increasing the efficiency of a potential geothermal heating plant.

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Section: Numerical Methodology and Mathematical Modelmentioning

confidence: 99%

Assessment of the Effective Variants Leading to Higher Efficiency for the Geothermal Doublet, Using Numerical Analysis‒Case Study from Poland (Szczecin Trough)

et al. 2020

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“…The T2well is a widely accepted numerical simulation program, and many publications use it to study problems about geothermal development. The accuracy of this code has been recognized by the industry and scientific research institutes (Li et al, 2015;Vasini, 2016;Vasini et al, 2018;Xu et al, 2018).…”

Section: Numerical Simulation Code and Wellbore-reservoir Coupling Thmentioning

confidence: 97%

Numerical evaluation of building heating potential from a co-axial closed-loop geothermal system using wellbore–reservoir coupling numerical model

Feng

et al. 2019

Energy Exploration & Exploitation

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Geothermal energy is one of the most potential renewable energy resources. How to efficiently extract and utilize geothermal energy has been a worldwide hot topic. Co-axial closed-loop geothermal system is a novel method using a continuously closed wellbore without water exchange with. It is more suitable for reservoirs with medium or low temperature and permeability because many problems could be avoided such as lack of in situ groundwater or low infectivity of the reservoir. Many companies and research institutes have applied closed-loop geothermal system in building heating engineering and some fine results have been gained. However, in practical engineering construction, the area of a closed-loop geothermal system heating system is a very important parameter. It directly determines the cost accounting and initial design of the project. Accurate and reliable estimation of heating capacity becomes very important. In this study, a wellbore–reservoir coupling model is established, which is calibrated using measured data from a short-term field trial operation. We have carried out mixed convective–conductive fluid-flow modeling using a wellbore flow model for TOUGH2 called T2Well to investigate the heat extraction performance of closed-loop geothermal system. The system evolution and the effect of flow rate and injection temperature on heat production performance are discussed. The result shows that the intermittent production cycles are more beneficial for heat extraction and system maintenance, and the temperature recovery between two heating seasons is enough to maintain system heating. And we can calculate that a geothermal well can ensure heating of buildings of 10,000–20,000 m2 and the heating area of intermittent operation is 4000 m2 more than continuous operation. Besides, the sensitivity analysis of parameters is also carried out.

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“…Compared with the direct method, using well logs to identify lithology is a universal indirect method, which is more accurate, effective and economical. Until now, there have been many lithology identification methods associated with logs, including the cross plotting method, traditional statistical analysis and several machine learning methods [8][9][10]. The cross plotting takes a considerable amount of time of an experienced analyst, especially in the heterogeneous reservoir.…”

Section: Introductionmentioning

confidence: 99%

A Data-Driven Approach for Lithology Identification Based on Parameter-Optimized Ensemble Learning

Sun

Jiang

et al. 2020

Energies

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The identification of underground formation lithology can serve as a basis for petroleum exploration and development. This study integrates Extreme Gradient Boosting (XGBoost) with Bayesian Optimization (BO) for formation lithology identification and comprehensively evaluated the performance of the proposed classifier based on the metrics of the confusion matrix, precision, recall, F1-score and the area under the receiver operating characteristic curve (AUC). The data of this study are derived from Daniudui gas field and the Hangjinqi gas field, which includes 2153 samples with known lithology facies class with each sample having seven measured properties (well log curves), and corresponding depth. The results show that BO significantly improves parameter optimization efficiency. The AUC values of the test sets of the two gas fields are 0.968 and 0.987, respectively, indicating that the proposed method has very high generalization performance. Additionally, we compare the proposed algorithm with Gradient Tree Boosting-Differential Evolution (GTB-DE) using the same dataset. The results demonstrated that the average of precision, recall and F1 score of the proposed method are respectively 4.85%, 5.7%, 3.25% greater than GTB-ED. The proposed XGBoost-BO ensemble model can automate the procedure of lithology identification, and it may also be used in the prediction of other reservoir properties.

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Interpretation of production tests in geothermal wells with T2Well-EWASG

Cited by 27 publications

References 20 publications

Assessment of the Effective Variants Leading to Higher Efficiency for the Geothermal Doublet, Using Numerical Analysis‒Case Study from Poland (Szczecin Trough)

Assessment of the Effective Variants Leading to Higher Efficiency for the Geothermal Doublet, Using Numerical Analysis‒Case Study from Poland (Szczecin Trough)

Numerical evaluation of building heating potential from a co-axial closed-loop geothermal system using wellbore–reservoir coupling numerical model

A Data-Driven Approach for Lithology Identification Based on Parameter-Optimized Ensemble Learning

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