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Dive into the research topics where Dar-Lon Chang is active.

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Featured researches published by Dar-Lon Chang.


information processing and trusted computing | 2014

Field Trial Results of a Drilling Advisory System

Dar-Lon Chang; Gregory S. Payette; Darren Pais; Lei Wang; Jeffrey R. Bailey; Nicholas David Mitchell

Field tests of a real-time Drilling Advisory System (DAS) have demonstrated value in several drill well surveillance applications. This system receives drilling data and transmits recommended operating parameters to the driller using existing rig systems and Wellsite Information Transfer Specification (WITS) data records. Using this industry standard, DAS can be deployed to any suitable data acquisition system on the diverse rig equipment available in the industry. The DAS computer may also be connected to a company network to enable desktop viewing of the drilling recommendations in the office. The method embodied in the software comprises both a learning mode and an application mode. In learning mode, systematic changes in parameters are recommended to explore the operating space, and calculation of an objective function determines results. Complex decisions to change operating parameters such as weight on bit, rotary speed, and flow rate can also be made with the assistance of DAS via early detection of drilling dysfunctions which change with depth and formation. The operator’s ROP (Rate of Penetration) management process is focused on MSE (Mechanical Specific Energy) surveillance, and the DAS process extends this methodology to a real-time operating system. DAS is designed to assist the driller by capturing and organizing real-time data without imposing on their judgment and control. It is intended to be a digital helper that enhances the driller’s ability to interpret current drilling conditions and make effective decisions. Remote access capabilities and customized output to the driller’s display were demonstrated in field trials, and key lessons from field trials have been implemented. The field trials included multiple hole sections in onshore and offshore wells across a wide variety of drilling conditions. In one example provided in this paper, the use of DAS provided 35% higher ROP when DAS was used to avoid drilling dysfunctions.


Journal of Petroleum Science and Engineering | 2015

Image-based Stokes flow modeling in bulk proppant packs and propped fractures under high loading stresses

Paula C. Sanematsu; Yijie Shen; Karsten E. Thompson; Tony Yu; Yanbin Wang; Dar-Lon Chang; Bashar Alramahi; Ali Takbiri-Borujeni; Mayank Tyagi; Clinton S. Willson


Archive | 2010

Optimizing well operating plans

Bruce A. Dale; Timothy Kirk Ellison; Dieter Postl; Dar-Lon Chang; Jennifer Hommema


Archive | 2012

Drilling advisory systems and methods with combined global search and local search methods

Lei Wang; Stephen Matthew Remmert; Paul E. Pastusek; Jeffrey R. Bailey; Matthew T. Prim; Darren Pais; Dar-Lon Chang; Gregory S. Payette


Archive | 2014

Drilling Advisory Systems and Methods to Filter Data

Dar-Lon Chang; Lei Wang; Paul E. Pastusek; Jeffrey R. Bailey; Gregory S. Payette; Darren Pais


Archive | 2015

DRILLING A WELLBORE

Gregory S. Payette; Dar-Lon Chang; Darren Pais; Jeffrey R. Bailey


SPE International Production and Operations Conference & Exhibition | 2012

Simulation and Visualization of Near-Well Flow

Pietro Valsecchi; Darren McDuff; Dar-Lon Chang; Hao Huang; Jason A. Burdette; Ted A. Long; Christof Karmonik


Archive | 2012

DRILLING ADVISORY SYSTEMS AND METHODS WITH DECISION TREES FOR LEARNING AND APPLICATION MODES

Lei Wang; Stephen Matthew Remmert; Paul E. Pastusek; Jeffrey R. Bailey; Matthew T. Prim; Dar-Lon Chang; Gregory S. Payette


Archive | 2013

Method to Detect Drilling Dysfunctions

Lei Wang; Jeffrey R. Bailey; Brian J. O'donnell; Dar-Lon Chang; Gregory S. Payette


information processing and trusted computing | 2009

Optimization of Carbonate Stimulation based on Long-Term Well Performance Predictions

Dieter Postl; Timothy Kirk Ellison; Dar-Lon Chang; Chris E. Shuchart; Arnout Laurens Mols; Nazri Nor; H. Al-Kharaz; Antonio Valle; Christopher John Sieben; Ram Chintaluri S; Zhihua Wang; Luis Sanchez; Ali M. Farah

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