Lucent Technologies Inc.

Exxonmobil Upstream Research Company

Exxonmobil Research and Engineering Company

Alcatel Lucent

Exxonmobil Technology and Engineering Company

Krishnan Kumaran

Simon C Borst

Sudheer A Grandhi

Philip Alfred Whiting

Bulin B Zhang

Joe Huang

Jingbo Wang

Carl Jeremy Nuzman

Randy C Tolman

Jeffrey Roberts Bailey

Paul E Pastusek

Pavlin B Entchev

Pavel Dimitrov

Lei Wang

Sanjeev Khanna

Nachi K Nithi

Stefan Hussenoeder

Bhaskar Sengupta

David J Schmidt

Dominique G Gillard

Murali Aravamudan

Kajamalai Gopalaswamy Ramakrishnan

Colin Leon Kahn

Teh Chung Ho

Limin Song

Michael C Romer

Narasimha-Rao Venkata Bangaru

Tomihisa Oda

Walter Weissman

Randall David Partridge

Gaylord W Richards

Francis Dominique

Keiji Yoeda

Matthias Imhof

Alan Mark Schilowitz

Iraj Saniee

Yoshihiro Iwashita

Debasis Mitra

Henry Alan Wolf

Richard Charles Dougherty

Terry Si-Fong Cheng

Daniel Matthew Andrews

Renzo Moises Angeles Boza

Kouseki Sugiyama

Indra Widjaja

Aravind Srinivasan

Gregory S Payette

Dominique Gillard

Niranjan A Subrahmanya

Keith Stanley

Matthew S Casey

Vishwas Gupta

Fred W Schroeder

Peng Xu

Erika A O Biediger

Timothy Owen Murphy

Martin J Terrell

Kavita Ramanan

Federico A Tavarez

Darren Pais

Benjamin J Spivey

Thomas A Badgwell

Kelly E Wrobel

Geoffrey Edmund Margrave

Lijun Qian

Jeffrey R Bailey

Predrag Jelenkovic

Donald Allen Burnett

Guy F Medema

Kevin Ross

Robert L Brovey

Michel Mandjes

Steven F Sowers

Renzo M Angeles Boza

Jing Bo Wang

Kelly Wrobel

Erika A Biediger

Matthias G Imhof

A method of identifying hydrocarbon production information is disclosed. In in a first hydrocarbon management environment, a first audio signal is detected and a characteristic acoustic fingerprint is identified therefrom. The fingerprint is stored in a memory, along with identifying information associated with the first signal. A second audio signal is detected and a characteristic acoustic fingerprint is identified therefrom. The fingerprints are compared, and if the fingerprints match the identifying information of the first audio signal is assigned to the second audio signal. A notification regarding the matching of the characteristic acoustic fingerprints of the first and second audio signals is issued.

Method and system for acoustic monitoring and pattern recognition in hydrocarbon management activities

A method and controller system are described for automatically tuning a controller of a drilling rig. The controller system includes a controller that determines a moving average of measured values, determines a moving standard deviation of the measured values, defines an outer zone of measured values with the determined moving average and the determined moving standard deviation, defines an inner zone of measured values with the determined moving average and the determined moving standard deviation, monitors the measured values for the occurrence of statistical events with respect to the outer zone and inner zone. Based on the detected statistical event, the controller adjusts the gain of the controller the based on the statistical event being associated with the outer zone or inner zone.

Controller with automatic tuning and method

Methods of drilling a wellbore within a subsurface region and drilling control systems that perform the methods. The methods include accessing an objective map and calculating a plurality of critical points of the objective map. The methods also include scoring each critical point and selecting a selected critical point of the plurality of critical points. The selected critical point describes an estimated value of at least one drilling performance indicator for a selected value of at least one independent operational parameter. The methods further include operating the drilling rig at the selected value of the at least one independent operational parameter and, during the operating, determining an actual value of the at least one drilling performance indicator. The methods also include updating the objective map to generate an updated objective map and repeating at least a portion of the methods.

Methods of drilling a wellbore within a subsurface region and drilling control systems that perform the methods

For a monitored corrosion sensor, such as a sensor based on one or more mechanical oscillators disposed in a fluid flow, one or more values are measured over time. The values can be measured at a desired frequency, such as a once per second, once per minute, or another convenient frequency. The measured data can then be analyzed as a time series. The goal of the analysis is to identify variations in the time series data that are sufficiently unexpected relative to the prior behavior of the time series within a given time window. The identified variations can then, for example, be excluded from consideration when determining a corrosion-related value for the sensor.

Detection of corrosion rates in processing pipes and vessels

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 for drilling a wellbore within a subsurface region and drilling assemblies and systems that include and/or utilize the methods are disclosed herein. The methods include receiving a plurality of drilling performance indicator maps, normalizing the plurality of drilling performance indicator maps to generate a plurality of normalized maps, adaptive trending of the plurality of drilling performance indicator maps to generate a plurality of trended maps, summing the plurality of trended maps to generate an objective map, selecting a desired operating regime from the objective map, and adjusting at least one drilling operational parameter of a drilling rig based, at least in part, on the desired operating regime.

Methods for drilling a wellbore within a subsurface region and drilling assemblies that include and/or utilize the methods

Selectively actuated plungers and systems and methods including the same are disclosed herein. The methods include flowing a wellbore fluid stream in fluid contact with a plunger and in an uphole direction within a wellbore conduit while the plunger is located within a target region of the wellbore conduit. The methods further include maintaining the plunger in a low fluid drag state while a variable associated with the wellbore fluid stream is outside a threshold range and transitioning the plunger to a high fluid drag state responsive to the variable associated with the wellbore conduit being within the threshold range. The methods further include conveying the plunger in the uphole direction within the wellbore conduit. The systems include the plungers and/or hydrocarbon wells that include the plungers.

Selectively actuated plungers and systems and methods including the same

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

The behavior of a monitored condition over time for a reactor or reaction system can be analyzed using groupings or windows of data to identify anomalous features in the time-average values. Anomalous features can be identified based on a threshold value generated from the analysis. Based on identification of an anomalous feature, a corrective action can be taken. For example, when the monitored condition is the pressure drop across a catalyst bed, detection of an anomaly can indicate the time to initiate a wash process for the catalyst bed before a large drop in catalyst activity occurs. By detecting an anomaly at an earlier point in time, a wash cycle can be initiated earlier so that the wash is more effective at restoring the catalyst bed to a desired condition.

Mitigation of plugging in hydroprocessing reactors

Methods and apparatus for actuating a downhole tool in wellbore includes acquiring a CCL data set or log from the wellbore that correlates recorded magnetic signals with measured depth, and selects a location within the wellbore for actuation of a wellbore device. The CCL log is then downloaded into an autonomous tool. The tool is programmed to sense collars as a function of time, thereby providing a second CCL log. The autonomous tool also matches sensed collars with physical signature from the first CCL log and then self-actuates the wellbore device at the selected location based upon a correlation of the first and second CCL logs.

Method for automatic control and positioning of autonomous downhole tools

Method for identifying geologic features from seismic data () using seismic anomaly detection by a double-windowed statistical analysis. Subtle features that may be obscured using a single window on the data are made identifiable using two moving windows of user-selected size and shape: a pattern window located within a sampling window larger than the pattern window (). If Gaussian statistics are assumed, the statistical analysis may be performed by computing mean and covariance matrices for the data within the pattern window in its various positions within the sampling window (). Then a specific measure of degree of anomaly for each voxel such as a residue value may be computed for each sampling window using its own mean and covariance matrix (), and finally the resulting residue volume may be analyzed, with or without thresholding, for physical features indicative of hydrocarbon potential ().

Seismic anomaly detection using double-windowed statistical analysis

Method for analyzing seismic data representing a subsurface region for presence of a hydrocarbon system or a particular play. Seismic attributes are computed, the attributes being selected to relate to the classical elements of a hydrocarbon system, namely reservoir, seal, trap, source, maturation, and migration. Preferably, the attributes are computed along structural fabrics () of the subsurface region, and are smoothed over at least tens or hundreds of data voxels. The resulting geologic attributes () are used to analyze the data for elements of the hydrocarbon system and/or recognition of specific plays, and for ranking and annotating partitioned regions () of the data volume based on size, quality, and confidence in the prospectivity prediction (). A catalog () of hydrocarbon trap configurations may be created and used to identify potential presence of hydrocarbon traps and/or aid in scoring () and ranking partitioned regions as hydrocarbon prospects.

Method for seismic hydrocarbon system analysis

An automated method for texture segmentation () of geophysical data volumes, where texture is defined by double-window statistics of data values, the statistics being generated by a smaller pattern window moving around within a larger sampling window (). A measure of 'distance' between two locations is selected based on similarity between the double-window statistics from sampling windows centered at the two locations (). Clustering of locations is then based on distance proximity ().

Geophysical data texture segmentation using double-windowed clustering 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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Raritan, NJ, United States of America

Krishnan Kumaran