Houston, TX, United States of America

Alpay Erkal


 

Average Co-Inventor Count = 8.0

ph-index = 1

Forward Citations = 2(Granted Patents)


Company Filing History:


Years Active: 2019

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1 patent (USPTO):Explore Patents

Title: Alpay Erkal: Innovator in Subterranean Production Estimation

Introduction

Alpay Erkal is a notable inventor based in Houston, TX (US). He has made significant contributions to the field of subterranean production estimation, showcasing his expertise through innovative patent developments. His work focuses on enhancing the understanding and prediction of production in stimulated reservoirs.

Latest Patents

Alpay Erkal holds a patent titled "Production estimation in subterranean formations." This patent describes a system that includes a tool capable of obtaining data that characterizes a stimulated reservoir. The system features a processor that predicts the production of the stimulated reservoir using the characterizing data and outputs the predicted production. The process involves stimulating a reservoir and obtaining data that characterizes it, allowing for accurate predictions of production. Additionally, one or more 3-D volumes may be produced based on the characterizing data, facilitating inferences about the stimulated reservoir.

Career Highlights

Throughout his career, Alpay Erkal has worked with prominent companies in the industry, including Schlumberger Technology Corporation and Schlumberger Holdings Limited. His experience in these organizations has contributed to his development as an inventor and expert in subterranean production estimation.

Collaborations

Alpay has collaborated with notable professionals in his field, including Javaid Durrani and Helena Gamero-Diaz. These collaborations have further enriched his work and contributed to advancements in the industry.

Conclusion

Alpay Erkal's innovative contributions to subterranean production estimation demonstrate his commitment to advancing technology in this field. His patent and career achievements reflect his expertise and dedication to improving production prediction methods.

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