Research




  PhD Research

  • Advanced image and video processing
  • Machine Learning
  • Deep Learning
  • Computer vision
  • Geo Processing
  • Data Visualization
  • Seismic Interpretation

PhD Abstract

        The exploration of oil and gas are vital part of today’s increasing power demands to meet the energy we need to power our homes, businesses, and transportation. Oil and gas explorers use seismic surveys, both onshore and offshore, to produce detailed images of the various rock types, layers, and their location beneath the Earth's subsurface using highly sensitive sensors. The obtained data undergo a series of processing steps, which require powerful computers, sophisticated software’s, and specialized manpower. Several Tera bytes of data is collected everyday using modern acquisition techniques. To extract information from such huge data, interpreters manually delineate important structures, which contain hints about petroleum and gas reservoirs such as salt domes, faults, channels, fractures, and horizons. These features typically span over several Sq. Km and are delineated based on correlation, changes in illumination, intensity, contrast, and texture of seismic data. There are very limited tools available for automatic detection and manual interpretation is extremely time consuming and labor intensive.
        In my PhD research, I am proposing to automate the process of seismic interpretation using advanced image processing techniques. I have proposed novel seismic attributes based on texture dissimilarity, phase coherence, visual attention theory, and the modeling of human visual system to quantify the changes and highlight the seismic features in a three-dimensional (3D) space. I have also developed fully- and semi-automated workflows that are interactive and easy-to-use for the delineation of important geological structures within seismic volumes. Experimental results on the real and synthetic datasets show that the proposed algorithms outperform the state-of-the-art methods for seismic interpretation.
        In short, my PhD thesis proposes automated, interactive and interpreter-assisted workflows, which have a very promising future in effective seismic interpretation. The proposed research is computationally inexpensive and is expected to not only become a handy tool in the interpreter’s toolbox for detecting and delineating geological structures but also reduce the time for seismic interpretation from years to months.

      Digital Signal Processing

    • Advanced DSP Algorithms
    • Acoustic Seeker
    • Adaptive Tracking
    • Echo Cancellation
    • Noise Cancellation/Rejection
    • Linear and Non-linear Filter Design
    • Perfect Filter Reconstruction
    • Adaptive Signal Processing (LMS, NLMS, RLS, KALMAN etc)
    • Real Time Correlation
    • GUI using MATLAB, Labview and Visual C++
    • Bird Recognition System
    • Voice Recognition System
    • Passive Vehicle Logging System
    • Simulink S-Functions (MATLAB)
    • Real Time Windows Target
    • Concept Demonstration Modelling
    • Interfacing between Software's (ActiveX, RTDX, DDE)
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      Radar Signal Processing

    • Phased Array RADAR
    • FMCW RADAR
    • Pulsed RADAR
    • Synthetic Aperture RADAR
    • Concealed Metal Detector RADAR
    • Passive Seeker
    • Pulse Compression
    • Direction of Arrival
    • Analog Beamforming
    • Digital Beamforming (Adaptive Beamforming)
    • Analog Phase Shifter (Vector Modulators)
    • Digital Phase shifters (Bit Phase Shifters)
    • MTI and CFAR (CACFAR, OSCFAR, GOCA, SOCA, AND, OR)
    • Data Acquisition
    • System Design and Prototyping
    • I have experience on Radars at VHF, L, X and K Bands
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      Controls

    • PID Control
    • Adaptive Control
      • Dead Beat
      • Gain Scheduling
      • Minimum Variance
      • Model Reference Adaptive Control (MRAC)
      • Pole Placement
      • Self Tuning Regulator (STR)
    • System Identification
    • Stability Analysis of Control Systems
    • Control of Linear and Non-linear Systems
    • Control of Wiener-Hammerstein Systems
    • Twin Rotor Control
    • Inverted Pendulum
    • Robotic Arm Manipulator
    • Magnetic Levitation Controller
    • Speed and Position Control of DC motor
    • Adaptive Tracking of Linear and Non-linear Systems
    • Neural Networks for Control and Tracking of Non-linear Systems
    • Real time experiments of minimum and non-minimum phases plants
    • Direct and Indirect Adaptive Inverse Control of Linear and Non-linear Plants
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      Neural Networks

    • Adaline
    • Madaline
    • Back Propagation
    • Pi Neural Network (PiNN)
    • Recurrent Neural Network
    • Multilayer Perceptron (MLP)
    • Radial Basis Neural Network (RBNN)
    • Higher Order Neural Network (HONN)
    • Multilayer Feedforward Neural Network (MFNN)
    • Lyapunov Function based Design of Neural Network (Lyap NN)
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      Digital Image Processing

    • Noise Removal
    • Image Compression
    • Image Cryptography
    • Image Enhancement and Restoration
    • Video Tracking
    • Fingerprint Recognition System
    • Hand Vein Recognition System
    • Face Recognition System
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      Embedded Systems

    • DSP kit
      • Single Core
        • TMS320C6713
        • TMS320C6416
      • Multi-Core
        • TMS320C6474
    • FPGA
      • Spartan II
      • Spartan III
      • Virtex 3
      • Virtex 6
    • Micro-controller
      • PIC
      • Phillips
      • ATMEL 
    • Data Acquisition
      • GaGe (Multichannel @ 125MSPS)
      • NI5105 (Multichannel @ 60MSPS)
      • ICS645 (Multichannel @ 5MSPS)
      • AD6M (DSP Daughter Card, Multichannel @ 6MSPS)
      • MF624 (Multifunction, Multichannel IO Board)
    • Printed Circuit Board (PCB) Designing
    • Hardware Implementation of DSP Algorithms on DSP kit and FPGA
    • Fixed and Floating Point Implementations
    • Software Profiling
    • DSP/BIOS Implementation
    • Interfacing Daughter Cards on DSP kit
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      Real Time Implementations

    • Perfect Filter Reconstruction
    • FMCW RADAR
    • Phase Shifter Control Board
    • Concealed Metal Detector
    • Pulse Compression
    • Six Different CFAR Implementations
    • Digital Beamforming
    • Noise Cancellation
    • Adaptive Algorithms (LMS, NLMS and RLS)
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      Miscellaneous

    • Networking Solution
    • Basic working knowledge of Antenna, RF and Microwave
    • Driver development for PCI devices for Windows XP Platform
    • ...
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