King Fahd University of Petroleum and Minerals

Naveed Iqbal

Azzedine Zerguine

Abdulmajid Lawal

Karim Abed-meraim

Qadri Mayyala

Azzedine Zeguine

Abdullah Othman

Kabiru Akande

Abdelmalek Zidouri

Khurram Karim Qureshi

Ali Arshad Nasir

Mudassir Masood

Rifaqat Hussain

Bo Liu

Abdul Aziz

Muhammad Nawaz Abbasi

A system, method, and non-transitory computer readable medium for in-field seismic data compression. The system includes geophones each having a 1-bit adaptive delta modulation for converting analog seismic signals to a modulated signal and transmitting the modulated signal, and a data collection center having a 1D convolutional neural network for receiving and compressing the transmitted modulated signal. The 1D CNN is configured to suppress quantization and random noise in the modulated signal.

System and method for lightweight in-field compression of seismic data

An antenna is disclosed. The antenna includes a transparent substrate, a first square patch antenna element with a square lattice structure, a second square patch antenna element and a low profile transparent passive decoupling strip. The first square patch antenna element is disposed on the transparent substrate. The first square patch antenna element includes horizontal conductive wires and vertical conductive wires. The horizontal conductive wires and the vertical conductive wires cross each other and are equally spaced to form square spaces between. The second square patch antenna element is disposed on the transparent substrate. The second square patch antenna element has a structure identical to the structure of the first square patch antenna element. The first and the second square patch antenna elements are spaced apart from each other. The low profile transparent passive decoupling strip is disposed between the first and the second square patch antenna elements.

Transparent MIMO antenna for closely spaced antenna elements

A data-driven linear filtering method to recover microseismic signals from noisy data/observations based on statistics of background noise and observation, which are directly extracted from recorded data without prior statistical knowledge of the microseismic source signal. The method does not depend on any specific underlying noise statistics and works for any type of noise, e.g., uncorrelated (random/white Gaussian), temporally correlated and spatially correlated noises. The method is suitable for microquake data sets that are recorded in contrastive noise environments. The method is demonstrated with both field and synthetic data sets and shows a robust performance.

Adaptive noise estimation and removal method for microseismic data

A system, computer-readable storage medium and method of reflection seismic survey in a wireless seismic network within a survey area is described. The method includes detecting, in each of a plurality of wireless seismic sensor nodes, seismic reflection signals from a seismic energy source; recording, in each of a plurality of wireless geophones, detected seismic signals; transmitting, by the geophones, the recorded seismic signals as digital data, using a combination of Orthogonal Frequency-Division Multiple Access (OFDMA) and Time Division Multiple Access (TDMA), to a central data receiving device; changing the seismic energy source location for seismic reflection; and repeating the detecting, recording and transmitting a number of times for each change in seismic energy source.

Wireless seismic survey system

An apparatus, a method, and a non-transitory computer readable medium for event detection of passive seismic data are disclosed. The apparatus includes processing circuitry extracts features from the passive seismic data based on a backbone subnetwork of a residual deep neural network. The processing circuitry generates bounding box proposals for a region of interest (ROI) in the passive seismic data based on the extracted features being input to a region proposal network of the residual deep neural network. The processing circuitry classifies the bounding box proposals into two groups. Each bounding box proposal in a first group indicates that a corresponding seismic signal presents in the ROI. Each bounding box proposal in a second group indicates that no seismic signal presents in the ROI. The processing circuitry determines at least one seismic signal in the ROI from the first group of bounding box proposals.

Computer system for event detection of passive seismic data

System and program instructions for seismic survey

Method for surveying with a wireless seismic network

A system, method, and non-transitory computer readable medium that perform blind signal estimation for single-input multiple-output systems. The method can include receiving, by the two or more receiver antennas of the receiver, an observed signal comprising the input signal and an additive noise term. The method can then form a data matrix using the observed signals from the two or more receiver antennas. The method can also include computing a singular value decomposition of the data matrix. The singular value decomposition can then be used to generate a parameter matrix. The method can then form a Toeplitz signal matrix using the parameter matrix. The method can estimating the input signal using the Toeplitz signal matrix.

Blind signal estimation using structured subspace technique

A method, non-transitory computer readable medium, and system for multiple-input multiple-output for blind identification that includes receiving an input signal, originated as an output signal of a transmitter, at a receiver. A signal processing module can obtain the input signal from the receiver. The signal processing module can use a finite impulse response filter and one or more matrices derived from the input signal to minimize a cost function and obtain a parameter matrix. The parameter matrix can then be used to estimate the output signal by generating one or more Toeplitz matrices using the parameter matrix.

Toeplitz structured subspace for multiple-channel blind identification methods

A device, method, and non-transitory computer readable medium that for two-dimensional blind single-input multiple-output channel identification for image restoration. The method includes receiving, by a receiver having independent channels, a two-dimensional image data matrix then transforming the received two-dimensional image data matrix to a one-dimensional image vector. Channel parameters can then be estimated using the one-dimensional image vector. The method can then construct a restored image using the estimated channel parameters and the two-dimensional image data matrix.

Growing community of inventors

Dhahran, Saudi Arabia

Naveed Iqbal