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ERL Annual Founding Members Meeting 2020: Perspectives for geophysics in industry: Deep nets for inverse problems and questions in carbon injection

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ERL Researchers

Each year, MIT Earth Resources Laboratory invites representatives of our Founding Member companies to MIT to hear about our latest research and meet our students and postdocs. This year’s meeting will take place via Zoom, and the theme will be “Perspectives for geophysics in industry: Deep nets for inverse problems and questions in carbon injection.” In addition to technical talks, we’ll be offering additional Zoom rooms for informal discussion. Invitations have been sent to our Founding Members, project sponsors, and alumni. If you didn’t receive your invitation, please contact erl-info@mit.edu.

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All times are US Eastern Daylight Time (UTC -4

DayStartEndSessionSpeakerTitleSummary
Wednesday, May 2010:0010:15WelcomeLaurent Demanet  
10:1510:45Plenary Session IJohn WilliamsA Data 1st Case Study – Learning from Production Data 
10:4511:00Break   
11:0011:20Uncertainty Quantification & GeothermalStephen BrownMachine learning for natural resource assessment: an application to the blind geothermal systems of NevadaRegional scale maps of geological and geophysical parameters are being used in machine learning algorithms to estimate the geothermal energy potential of the Great Basin of the western United States.
11:2011:40Chen GuBayesian model selection and the application to geothermal developmentI developed a bayesian model selection method to compare multiple geothermal predictive models on the same scale, and select the best model to do robust geothermal prediction with uncertainty quantification.
11:4012:00Andrea ScarinciAssessing inference quality under model misspecification: an application to seismic inversionWe proposed a new misfit measure for robust inference under model misspecification. How can we quantitatively verify the improvement? And in what terms?
12:0012:15Break   
12:1512:30Student and Postdoc IntroductionsSamiya Alkhairy, Hilary Chang, Aarti Dwivedi, Sarah Greer, Jing Jian, Magreth Kakoko, Brindha Kanniah, Paris Smalls, Anuar Togaibekov, Mohamad Zaarour, Chenguang ZhangERL students and postdoctoral researchers introduce their work.
12:3013:45Break   
13:4514:05CO2 Storage & Induced SeismicityMaryam AlghannamUnderstanding rate effects in induced seismicityWe developed a new spring-slider model of earthquake nucleation that reflects pressurization rate effects on induced earthquakes. ​
14:0514:25Josimar Alves da SilvaModeling CO2 Storage in a Gulf of Mexico Reservoir Using Coupled Flow and GeomechanicsWe investigate the impact of large scale CO2 storage on the stability of faults in the Gulf of Mexico using a coupled flow and geomechanics model. Our model is grounded on a realistic geological model typical of the Gulf of Mexico area. We show that large-scale CO2 injection can be performed safely but care must be taken regarding the well locations and the injection schedule.
14:2514:45Tiange XingTime-dependent Deformation in BasaltWe constrained the effect of water on time-dependent brittle creep deformation in basaltic rocks from the CarbFix site in Iceland. These experiments form a base line for future carbonation experiments on the basalts. Our study will fill the current gaps in understanding of long-term deformation behavior and transport properties of basaltic rocks at reservoir conditions and provide guidance to future applications of geological CO2 mineralization storage.
14:4515:00Break   
15:0015:20Deep Learning & Seismic InversionHongyu SunElastic full waveform inversion with extrapolated low frequency dataBy leveraging deep learning technologies, we extend our work on extrapolated FWI (EFWI) by proposing to synthesize the low frequencies of multi-component elastic seismic records, and use those “artificial” low frequencies to seed the frequency sweep of elastic FWI.
15:2015:40Pawan BharadwajSymAE: an autoencoder with embedded physical symmetries for passive time-lapse monitoringSymAE is a network trained to accurately monitor the subsurface changes irrespective of the variability in the passive sources.
15:4016:00Matthew T.C. LiWide-band Butterfly Network: An architecture for multifrequency sub-wavelength imagingWe incorporate the physics of wave propagation into our neural network architecture in order to super-resolve scatterers with length scales below the diffraction limit.
16:0016:15Break   
16:1516:35Next-Generation Computational MethodsAdrien ScheuerThe method of polarized traces for the 3D Helmholtz equationWe have developed a fast, accurate and scalable solver for the high-frequency 3D Helmholtz equation in heterogeneous acoustic media. The solver is based on the method of polarized traces and is coupled with distributed linear algebra libraries and pipelining of the many sources to achieve a sublinear online runtime with respect to the total number of unknowns. 
16:3516:55Zhilong FangLift and Relax for waveform inversionWe developed a Lift and Relax method for full waveform inversion to mitigate the local minima issue.
16:5517:15Matteo CoupletPorous media reconstruction​ using Deep Texture SynthesisUsing deep learning, we have successfully reconstructed 3D porous media models from 2D images while preserving the macroscopic physical properties.
Wed. 05/20 Informal Discussion Rooms12:0014:001. Uncertainty Quantification & GeothermalHosted by Andrea Scarinci  
14:0015:004. Next-Generation Computational MethodsHosted by Matthew T.C. Li  
14:4516:002. CO2 Storage & Induced SeismicityHosted by Josimar Alves da Silva  
14:4517:455. FracturesHosted by Hao Kang  
17:1518:154. Next-Generation Computational MethodsHosted by Adrien Scheuer  
18:1519:15Hosted by Zhilong Fang  
Thursday, May 2110:0010:15WelcomeLaurent Demanet  
10:1510:45Plenary Session IIShuhei OnoGeneration temperature of methane estimated from doubly substituted isotopologue (13CH3D) 
10:4511:00Break   
11:0011:20FracturesEkaterina BolotskayaEarthquake Rupture Modeling:
Fracturing vs. Friction​
We qualitatively and quantitatively compared the fault parameters for different rupture propagation approaches (rate-and-state friction, slip weakening friction, exponential cohesive zone fracturing model) by means of FEM simulations. Results produced by different approaches are virtually indistinguishable (apart from very near-field stress profile observations) given the fracture energy is set the same in all cases.
11:2011:40Yue Olivia MengJamming transition and emergence of fracturing in wet granular mediaWe developed a hydromechanical model to study the impact of wettability on hydraulic fracturing patterns, and the proposed jamming phase diagram provides insights on the interplay between solid and fluid mechanics, which has wide applications in enhanced oil recovery
11:4012:00Ignacio Arzuaga GarcíaInteraction of hydraulically induced fractures with natural fractures in shaleWe introduce a combined AE-Imaging(Visual)-DIC data analysis process through which we generated Qualitative and Quantitative correlations between governing parameters of interaction between natural and hydraulic fractures in shale, particularly focused on addressing Vaca Muerta’s formation strike-slip stress regime effect on wells productivity.
12:0012:20Rafael Villamor Lora & Hao KangFracture deformation and its effects on flow – experiments and simulationsWe have developed a novel experimental setup to investigate the interplay between flow and fracture stiffness in stressed fractures. In addition, we have successfully used ABAQUS to simulate micro-indentation and the mechanical compression of multiple fracture surface asperities.
12:2012:40Ammar AlaliHybrid Data Driven Drilling and Rate of Penetration OptimizationWe have built a data-driven scheme to optimize the drilling rate of penetration by utilizing historical and real-time data, which can work in any development field.”
12:4014:00Break   
14:0015:00Business Meeting For representatives of ERL Founding Member companies and ERL faculty. 
Thu. 05/21 Informal Disucssion Rooms12:0014:002. CO2 Storage & Induced SeismicityHosted by Saleh Al-Nasser  
12:0014:003. Deep Learning & Seismic InversionHosted by Hongyu Sun  
12:4013:401. Uncertainty QuantificationHosted by F. Dale Morgan  

Image: Christine Daniloff, MIT

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