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<span style="font-size:20.0pt;font-family:"Tahoma",sans-serif;
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<span style="font-size:16.0pt;font-family:"Tahoma",sans-serif;
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<span style="font-size:16.0pt;font-family:"Tahoma",sans-serif;
mso-bidi-font-family:"Times New Roman";color:#222222">PhD Dissertation Defense</span><span style="font-size:16.0pt;font-family:"Albertus Extra Bold",serif;color:#222222"></span></h2>
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<b><span style="font-size:14.0pt;font-family:"Tahoma",sans-serif;mso-bidi-font-family:
Arial;color:#222222">Shale Gas Production Forecasting using Reservoir Simulation with Hydraulic Fracture Mapping
</span></b></p>
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<b><span style="font-size:14.0pt;font-family:"Tahoma",sans-serif;mso-bidi-font-family:
Arial;color:#222222"><span style="mso-spacerun:yes"> </span>Ben Xu</span></b><span style="font-family:"Arial",sans-serif;color:#222222"></span></p>
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<b><span style="font-family:"Arial",sans-serif;color:#1F497D"> </span></b><b><span style="font-family:"Arial",sans-serif;color:#222222">Date: Thursday, November 19, 2019</span></b><span style="font-family:"Arial",sans-serif;color:#222222"></span></p>
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<b><span style="font-family:"Arial",sans-serif;color:#222222">Location: Technology Bridge (Formerly ERP)</span></b><span style="font-family:"Arial",sans-serif;
color:#222222"> Building 9, room 123</span></p>
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<b><span style="font-family:"Arial",sans-serif;color:#222222">Time: </span></b><span style="font-family:"Arial",sans-serif;color:#222222">9:00 AM – 11:30 AM</span></p>
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<b><span style="font-family:"Arial",sans-serif;color:#222222"> </span></b><span style="font-family:"Arial",sans-serif;color:#222222"></span></p>
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<b><span style="font-family:"Arial",sans-serif;color:#222222">Committee Chair:</span></b><b><span style="font-family:"Arial",sans-serif;color:#1F497D"> </span></b><span style="font-family:"Arial",sans-serif;color:#222222">Dr. <span>Guan Qin</span></span></p>
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<b><span style="font-family:"Arial",sans-serif;color:#222222"> </span></b><span style="font-family:"Arial",sans-serif;color:#222222"></span></p>
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<b><span style="font-family:"Arial",sans-serif;color:#222222">Committee Members:</span></b><span style="font-family:"Arial",sans-serif;color:#222222"></span></p>
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<span style="font-family:"Arial",sans-serif;color:#222222">Dr. Ganesh Thakur, Dr. Christine Ehlig-Economides, Dr. Michael Nikolaou, Dr. Kyung Jea Lee</span></p>
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<a><span style="font-size:14.0pt;
font-family:"Calibri Light",sans-serif;color:#222222">Abstract</span></a><span style="mso-bookmark:m_-4917301324375125784__Toc134716"></span><span style="font-size:14.0pt;font-family:"Calibri Light",sans-serif;color:#2E74B5"></span></h1>
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We presented a brand new correlation between the microseismic magnitude and the shape factor coefficients in the classic dual-porosity model accompany a procedure to calibrate this coefficient with real production data. The novel contribution was the employment
of the shape factor in the dual-porosity model to characterize a relatively complex small scale fracture network, which numerically integrates with the large scale fractures geometry in the EDFM model to forecast shale gas well production. A constrained result
of using microseismic data to measure the length and direction of the large scale fractures was put into the embedded discrete fracture model (EDFM) to integrate the large scale fracture into a corner point grid. The EF-DP model considered stimulation data
such as total fluid volume for hydraulic fracturing, flow rate, wellhead pressure, sand concentration, and proppant size.
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To verify the credibility of this model, we performed two sets of parameter sensitivity analyses for the large scale fractures and the small scale fractures. We used two sets of real-world shale gas production data for history matching and successfully used
the EFDP model to quantify analysis the impact of frac-hit on a shale gas producing well. Parameter sensitivity analysis confirmed that enhanced small scale fracture permeability could effectively increase production, mainly by strengthening far-field reservoir
drainage volume. </p>
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According to the application results, we found that the EFDP model was effectively and accurately predict shale gas production, and quantitatively evaluate the impact of frac-hit between multiple wells.
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