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Pallav Te Sarma

from Danville, CA
Age ~47
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Also known as:
Sarma Pallav, V Sarma
Phone and address:
1268 Greenbrook Dr, Danville, CA 94526
Connected to:
Anjan G Sarma, 51Anupama V Sarma, 49Bani K Sarma, 44Bhaswati Sarma, 40Chitra S Sarma, 50Ganapathy N Sarma, 48Janardana V Sarma, 56Kavitha Sarma, 47Mallika Sarma, 32Manjima E Sarma, 52

Pallav Sarma Phones & Addresses

  • 1268 Greenbrook Dr, Danville, CA 94526
  • San Ramon, CA
  • Foster City, CA
  • Antioch, CA
  • Houston, TX
  • Stanford, CA
  • Bakersfield, CA

Resumes

Resumes

Pallav Sarma Photo 1

Co-Founder And Chief Scientist

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Location:
1268 Greenbrook Dr, Danville, CA 94526
Industry:
Oil & Energy
Work:
Tachyus
Co-Founder and Chief Scientist
Chevron 2006 - Jan 2015
Staff Reserch Scientist
Solomob 2006 - Jan 2015
Co-Founder
Exxonmobil Jun 2003 - Sep 2003
Simulation Research Intern
Schlumberger Jun 2002 - Aug 2002
Simulation Research Intern
Education:
Stanford University 2003 - 2006
Doctorates, Doctor of Philosophy Indian Institute of Technology (Indian School of Mines), Dhanbad 1996 - 2000
Bachelors, Bachelor of Technology, Petroleum Engineering Stanford University 1995 - 1997
Doctorates, Doctor of Philosophy, Petroleum Engineering
Skills:
Reservoir Simulation
Reservoir Management
Reservoir Engineering
Petroleum Engineering
Petroleum
Modeling
Simulations
Upstream
Geostatistics
Uncertainty Analysis
C++
Matlab
Field Development
Petroleum Economics
Well Testing
Java
Reserves
Machine Learning
Software Development
Stochastic Processes
Android Development
Process Optimization
Mobile Applications
Pattern Recognition
Artificial Intelligence
Optimization
Programming
Optimal Control Theory
Probability Theory
Data Assimilation
Inverse Problems
Statistics
Interests:
Artificial Intelligence
Inverse Modeling
Data Assimilation
Optimization
Stochastic Processes
Machine Learning
Geostatistics
C++ and Java Programming
Android App Development
Statistics
Reservoir Simulation
Optimal Control Theory
Probability Theory
Reservoir Engineering
Languages:
English
Assamese
Hindi
Pallav Sarma Photo 2

Staff Research Scientist At Chevron Corp., Cofounder At Solomob Inc.

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Position:
Cofounder at SoLoMob Inc, Staff Reserch Scientist at Chevron Corporation
Location:
San Francisco Bay Area
Industry:
Oil & Energy
Work:
SoLoMob Inc - San Ramon, CA since Jan 2012
Cofounder
Chevron Corporation - San Ramon, CA since 2006
Staff Reserch Scientist
ExxonMobil Upstream Research Company Jun 2003 - Sep 2003
Research Intern
Schlumberger Technology Center Jun 2002 - Aug 2002
Research Intern
Schlumberger GeoQuest Jul 2000 - Sep 2001
Reservoir Engineer
Education:
Stanford University 2001 - 2006
PhD, Petroleum Engineering Indian School of Mines 1996 - 2000
BTech, Petroleum Engineering
Skills:
Reservoir Simulation
Reservoir Management
Reservoir Engineering
Process Optimization
Software Development
Android Development
Mobile Applications
Machine Learning
Artificial Intelligence
Pattern Recognition
Stochastic Processes
Uncertainty Analysis
Probability Theory
Petroleum Engineering
Geostatistics
Reserves
Modeling
Field Development
Petroleum Economics
Upstream
Simulations
Java
C++
Matlab
Programming
Interests:
Reservoir Simulation, Optimization, Optimal Control Theory, Statistical Pattern Recognition, Artificial Intelligence, Probability Theory, Stochastic Processes, Geostatistics, Analytical Mathematics, Well Testing, Petroleum Economics, Programming Concepts and Object Oriented Programming, Android App Development
Honor & Awards:
George Dantzig Dissertation Award 2nd Prize for best doctoral dissertation on optimization presented by INFORMS (Sep, 2007). Ramey Fellowship at Stanford University for excellence in research (Jun, 2006). Second Runner up at the Canadian International Petroleum Conference Graduate Student Presentation Competition (Jun, 2006) Merit Award in the Business Association of Stanford Engineering Students (BASES) Innovator's Challenge Competition (Jun, 2006). Chevron Scholarship for outstanding contributions during internship (Dec, 2004, 2005). SIAM Stanford Chapter Annual Research Excellence Award (May, 2005). Who's Who in America, 2006-2009. Miller Fellowship at Stanford University for High Academic Achievement (Fall, 2002). Society of Petroleum Engineers Scholarship for high academic achievement (1999 - 2000). Oil India Limited Scholarship for high academic achievement (1997 – 2000). North East Council Scholarship for high academic achievement (1997 – 2000).

Publications

Us Patents

System And Method For Efficient Well Placement Optimization

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US Patent:
20090216505, Aug 27, 2009
Filed:
Feb 19, 2009
Appl. No.:
12/389227
Inventors:
Pallav Sarma - San Ramon CA, US
Wen Hsiung Chen - Danville CA, US
Assignee:
Chevron U.S.A. Inc. - San Ramon CA
International Classification:
G06F 17/10
G06F 17/17
US Classification:
703 2
Abstract:
The disclosed methods, systems, and software are described for optimizing well placement in a reservoir field. A geological model of a reservoir field, a grid defining a plurality of cells, one or more wells to be located within the plurality of cells, and an objective function are all provided. The geological model is associated with the grid defining the plurality of cells. The locations of the wells are represented by continuous well location variables associated with a continuous spatial domain. A gradient of the objective function is calculated responsive to the continuous well location variables. The locations of the wells are then adjusted responsive to the calculated gradient of the objective function. Iterative calculation of the gradient and adjustment of the wells continue until the well locations are optimized. A visual representation of the reservoir field can be generated based on the optimized well placements.

System And Method For Predicting Fluid Flow In Subterranean Reservoirs

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US Patent:
20100198570, Aug 5, 2010
Filed:
Jan 29, 2010
Appl. No.:
12/657929
Inventors:
Pallav Sarma - San Ramon CA, US
Wen Hsiung Chen - Danville CA, US
International Classification:
G06G 7/57
US Classification:
703 10
Abstract:
A reservoir prediction system and method are provided that use generalized EnKF using kernels, capable of representing non-Gaussian random fields characterized by multi-point geostatistics. The main drawback of the standard EnKF is that the Kalman update essentially results in a linear combination of the forecasted ensemble, and the EnKF only uses the covariance and cross-covariance between the random fields (to be updated) and observations, thereby only preserving two-point statistics. Kernel methods allow the creation of nonlinear generalizations of linear algorithms that can be exclusively written in terms of dot products. By deriving the EnKF in a high-dimensional feature space implicitly defined using kernels, both the Kalman gain and update equations are nonlinearized, thus providing a completely general nonlinear set of EnKF equations, the nonlinearity being controlled by the kernel. By choosing high order polynomial kernels, multi-point statistics and therefore geological realism of the updated random fields can be preserved. The method is applied to two non-limiting examples where permeability is updated using production data as observations, and is shown to better reproduce complex geology compared to the standard EnKF, while providing reasonable match to the production data.

Constrained Pressure Residual Preconditioner For Efficient Solution Of The Adjoint Equation

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US Patent:
20120150506, Jun 14, 2012
Filed:
Dec 12, 2011
Appl. No.:
13/323060
Inventors:
Choongyong Han - Houston TX, US
John Wallis - Sugar Land TX, US
Pallav Sarma - San Ramon CA, US
Gary Li - Katy TX, US
Mark Schrader - The Woodlands TX, US
Wen Chen - Danville CA, US
Assignee:
Chevron U.S.A. Inc. - San Ramon CA
International Classification:
G06F 17/11
G06G 7/57
G06F 17/16
US Classification:
703 2
Abstract:
A method, system and computer program product is disclosed for using a constrained pressure residual (CPR) preconditioner to solve adjoint models. A linear system of fluid flow equations comprising a plurality of variables that represent fluid flow properties in a geological formation of a subterranean reservoir is provided. Matrix (Ã), which comprises a transpose of a Jacobian matrix associated with the linear system of fluid flow equations, is constructed. A constrained pressure residual preconditioner Mis constructed responsive to the matrix (Ã). Matrix equation (Ã)y=d is then solved using the constrained pressure residual preconditioner M.

System And Method For Modeling A Subterranean Reservoir

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US Patent:
20120215511, Aug 23, 2012
Filed:
Feb 17, 2011
Appl. No.:
13/029534
Inventors:
Pallav Sarma - San Ramon CA, US
Wen Chen - Danville CA, US
Assignee:
Chevron U.S.A. Inc. - San Ramon CA
International Classification:
G06G 7/48
US Classification:
703 10
Abstract:
A computer-implemented reservoir prediction system, method, and software are provided for updating simulation models of a subterranean reservoir. An ensemble of reservoir models representing a subterranean reservoir having non-Gaussian characteristics is provided, along with reservoir data from the subterranean reservoir used to condition the ensemble of reservoir models. For each of the reservoir models in the ensemble of reservoir models, a constrained optimization with equality constraints and inequality constraints are solved using a constrained Kernel Ensemble Kalman Filter to obtain a constrained optimal solution. The constrained optimal solutions are assembled to update the ensemble of reservoir models. The updated ensemble of reservoir models are consistent with the reservoir data provided from the subterranean reservoir and the non-Gaussian characteristics of the subterranean reservoir are preserved.

System And Method For Uncertainty Quantification In Reservoir Simulation

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US Patent:
20120215512, Aug 23, 2012
Filed:
Feb 17, 2011
Appl. No.:
13/029938
Inventors:
Pallav Sarma - San Ramon CA, US
Assignee:
Chevron U.S.A. Inc. - San Ramon CA
International Classification:
G06G 7/48
US Classification:
703 10
Abstract:
A computer-implemented reservoir prediction system, method, and software are provided for quantifying uncertainty and evaluating production performance of a subterranean reservoir. A reservoir simulation model representing a subterranean reservoir and an associated distribution of input variables are provided. A plurality of polynomial chaos expansions is generated. Each polynomial chaos expansion is used to approximate a simulation output of the reservoir simulation model for the distribution of input variables. Deterministic coefficients of the polynomial chaos expansions are calculated using a sampling process, such as a quasi-Monte Carlo method using a low discrepancy sequence. An output variable, such as cumulative oil production, and associated output variable uncertainty are forecasted using the polynomial chaos expansions and the deterministic coefficients such that production performance of the subterranean reservoir can be evaluated.

System And Method For Use In Simulating A Subterranean Reservoir

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US Patent:
20130338983, Dec 19, 2013
Filed:
Mar 15, 2013
Appl. No.:
13/843096
Inventors:
Pallav Sarma - San Ramon CA, US
Wen Hsiung Chen - Danville CA, US
Assignee:
Chevron U.S.A. Inc. - San Ramon CA
International Classification:
G06F 17/50
US Classification:
703 10
Abstract:
A computer-implemented method, system, and computer program product are disclosed for updating simulation models of a subterranean reservoir. An ensemble of reservoir models representing a subterranean reservoir having non-Gaussian characteristics is provided and the ensemble of reservoir models is updated using a subspace ensemble Kalman filter. Kemal principle component analysis parameterization or K-L expansion parameterization can be used to update the ensemble of reservoir models.

Systems And Methods For Back-Allocation Of Oil Produced By Waterflooding

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US Patent:
20220205359, Jun 30, 2022
Filed:
Dec 30, 2020
Appl. No.:
17/138582
Inventors:
- Houston TX, US
Pallav Sarma - Houston TX, US
International Classification:
E21B 49/08
G06Q 50/02
G06N 20/20
G01V 99/00
Abstract:
Systems, methods, and computer-readable media for determining the production rate of oil produced from each of a plurality of oil-bearing geological layers in an oil field. In some embodiments, the method comprises allocating injected fluid into each layer of a plurality of oil-bearing geological layers to a plurality of paths from injection sites of injection wells to production wells in each layer by balancing the mass of fluid injected into and the total fluid recovered from each oil-bearing geological layer. In some embodiments, the method comprises calculating estimated geological properties for each path in the plurality of paths to match total oil and injection fluid recovered at each production well in the plurality of production wells. In some embodiments, the method comprises using the estimated geological properties, calculating an oil production rate for each path between an injector well and a production well in a geological layer.

Model Selection From A Large Ensemble Of Models

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US Patent:
20140136165, May 15, 2014
Filed:
Mar 15, 2013
Appl. No.:
13/840855
Inventors:
Pallav Sarma - San Ramon CA, US
Wen Hsiung Chen - Danville CA, US
Assignee:
Chevron U.S.A. Inc. - San Ramon CA
International Classification:
G06F 17/50
US Classification:
703 2, 703 10
Abstract:
A method, system and processor readable medium containing computer readable software instructions for selecting representative models from a large ensemble of models is disclosed. An ensemble of reservoir models that define an input uncertainty space is provided. A target number of representative models and one or more target percentiles of output variables that the representative models are to approximate are input. The representative models from the ensemble of reservoir models that match the one or more target percentiles of output variables are selected while maximizing the spread between the selected representative models in the input uncertainty space.
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Pallav Te Sarma from Danville, CA, age ~47 Get Report