Exxonmobil Upstream Research Company

Exxonmobil Research and Engineering Company

Jingbo Wang

Krishnan Kumaran

Limin Song

Narasimha-Rao Venkata Bangaru

Jeffrey Roberts Bailey

Pavel Dimitrov

Lei Wang

Dominique Gillard

Matthew S Casey

Peng Xu

Vishwas Gupta

Erika A O Biediger

Stefan Hussenoeder

Bhaskar Sengupta

Steven F Sowers

Robert L Brovey

Fred W Schroeder

Guy F Medema

Dominique G Gillard

Methods and systems for detecting a condition within a component of a process plant, including obtaining a first and second set of parameter measurements from a first and second plurality of sensor locations along a first dimension of an outside surface of a component, processing the first and second set of parameter measurements to develop a continuous surface condition profile of the component using a predetermined model. The predetermined model includes a forward solution to an equation describing the condition and is linearly separable in at least two dimensions corresponding to the first and second dimension. The model includes an inverse solution to the equation to provide a set of coefficients corresponding to a set of basis functions of the forward solution based on the first and second set of parameter measurements.

Sensor network design and inverse modeling for reactor condition monitoring

Methods and systems for controlling drilling operations include using a statistical model to identify at least two controllable drilling parameters having significant correlation to one or more drilling performance measurements. The methods and systems further generate operational recommendations for at least two controllable drilling parameters based at least in part on the statistical model. The operational recommendations are selected to optimize one or more drilling performance measurements.

Automatic drilling advisory system based on correlation model and windowed principal component analysis

Method for identifying geologic features from geophysical or attribute data using windowed principal component (), or independent component, or diffusion mapping () analysis. Subtle features are made identifiable in partial or residual data volumes. The residual data volumes () are created by () eliminating data not captured by the most prominent principal components (). The partial data volumes are created by () projecting the data () on to selected principal components (). Geologic features may also be identified from pattern analysis () or anomaly volumes () generated with a variable-scale data similarity matrix (). The method is suitable for identifying physical features indicative of hydrocarbon potential.

Windowed statistical analysis for anomaly detection in geophysical datasets

A computer implemented method for the detection of features such as faults or channels in seismic images. First, edges are detected in a smoothed seismic image (). To detect a fault line, an image intensity of the edges is projected in multiple spatial directions, for example by performing a Radon transform (). The directions of maximum intensity are used to define a fault line (). To detect channels, smooth curves are identified within the detected edges (). Sets of parallel smooth curves () are then identified and used to define channels ().

Detection of features in seismic images

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New York, NY, United States of America

Jingbo Wang