The meeting is fully registered and we are no longer accepting registration.

Keywords:  Machine Learning, Deep Learning, Artificial Intelligence, Petrophysical, Interpretation, Reservoir Characterization 

When:        Thursday, June 20, 2019 (the day after the 2019 SPWLA annual meeting)
Where:       Anadarko Corporation Headquarter 1201 Lake Robbins Drive, The Woodlands, Texas 77380

Program:

Time Speaker Affiliation Topic
7:30 AM Breakfast and Registration
8:00 AM Chicheng Xu Aramco Welcome & Introduction
8:10 AM Hani Elshahawi Shell Keynote talk: “Silo Busting - How Data Analytics is helping Petrophysics integrate with other disciplines
8:40 AM Philippe Herve SparkCognition Predicting petrophyscis, reservoir characteristic, and drilling dysfunctions with AI powered automation
9:10 AM Bin Dai Halliburton Machine learning and pattern recognition for formation testing and sampling
9:40 AM Michael Ashby Anadarko Petrophysics-Driven Well Log Quality Control Using Machine Learning
10:10 AM Break
10:30 AM Chicheng Xu Aramco When Petrophysics Meet Big Data: What can Machines Do?
11:00 AM Tianqi Deng University of Texas, Austin Comparative Study of Three Supervised Machine-Learning Algorithms in Classifying Diagenetic Facies in the Kansas Arbuckle Carbonate Formation
11:30 AM Constantine Vavourakis Emerson Limitations of Naïve Machine Learning Approaches in Geosciences: The Example of Grain Size Prediction from Microresistivity Logs
12:00 PM Lunch
1:00 PM Constantine Vavourakis Emerson Machine Learning Development in Geolog: Leveraging Deep Learning Techniques for Improved Log Prediction
1:30 PM Alex Bayeh Anadarko A Deep Learning Model and Framework for Well Log Correlation at Scale
2:00 PM Siddharth Misra University of Oklahoma Machine learning for SEM image analysis
2:30 PM Break
3:00 PM James Howard &
Shawn Zhang
DigiM Solution Machine-Learning Methods: Analysis of Rock Images and Beyond
3:30 PM Xicai (Jack) Liu Consulting Engineer
(previous Sinopec)
Determination of Shale Anisotropic Properties and Applications
4:00 PM Bin Dai Halliburton Closing Remarks

Sponsors: 


PDDA SIG Meeting Committee:

Chicheng Xu (Aramco Services Company), Michael Ashby( Anadarko Petroleum Corporation), Bin Dai (Halliburton), Zheng Gan (Core Laboratories), Constantine Vavourakis(Paradigm, Emerson), Siddharth Misra ( The University of Oklahoma )
Our Policy

It is the policy of this organization to provide equal opportunities without regard to race, color, religion, national origin, gender, sexual preference, age, or disability.
Conference attendance seating limited to fifty. Preference will be given to applicants who are willing to present at this topical conference.
Proceedings are “off the record” to encourage sharing of the latest techniques and information. Presentations will typically be 20-30 minutes (including Q&A).
Quoting and (or) recording speakers or their presentations is prohibited.
Commercialism in speaker presentations will not be permitted. Company logos should be limited to the title slide only and used only to indicate the affiliation of the author and co-authors of the presentation. 

 

SPWLA Petrophysical Data-Driven Analytics Special Interest Group (PDDA-SIG)

 

Following the positive feedback of the recently conducted special interest group (SIG) survey during 2018 SPWAL Spring topical conference, we are pleased to announce the formation of a new SPWLA special interest group dedicated on Petrophysical Data-Driven Analytics (PDDA). The vision for establishing a PDDA-SIG began at the 2018 SPWLA Spring topic conference in Houston, where more than 60 industry professionals (core analyst, tool physicists, petrophysists, geologist etc.) and data scientists attended to discuss the applications of advanced data analytics techniques to challenging petrophysical interpretations and oil field operations. Most of the conference attendees showed great interest and preregistered themselves as members of SPWLA PDDA SIG.

The goals of the PDDA-SIG are to create a venue for exchanging and sharing knowledge and best practices of applying advanced data analytics to solve challenging big-data-related problems in the oil and gas exploration and development. It aims to foster the cross-disciplinary technical collaborations between practitioners in academic and different sectors of O&G industry, and to promote networking for industry professionals.

The PDDA-SIG will cover the following primary technical areas:

  • geological–petrophysical interpretation

  • sensor and logging technology

  • rock physics and geomechanics

  • oil field operation improvement

  • data QC and management

  • AI assisted  automation

Participation in the PDDA-SIG is open for any practitioner and student who are interested in this subject matter. Please use following URL in LinkedIn Group for PDDA-SIG member registration:

https://www.linkedin.com/groups/13605420

It is planed that the PDDA-SIG will hold annual meeting and quarterly seminars. The first annual meeting is planed to be in the Spring of 2019. Please follow PDDA-SIG webpage or SPWLA newsletter for the latest update of all PDDA-SIG events.

During the 2018 Spring Topical Conference, several productive panel discussions were actively participated by PDDA SIG members. The summary was compiled by Dr. Chicheng Xu and Dr. Siddharth Misra, and published on the latest SPWLA newsletter, please check the summary here.

The inaugural PDDA-SIG executive committee (2018-2019) is composed of:

Chairman: Chicheng Xu, Aramco Services Company, Chicheng.Xu@aramcoservices.com
Vice-Chairman: Michael Ashby, Anadarko Petroleum Corporation
, ashby149@aol.com
Secretary of Publications: Bin Dai, Halliburton, Bin.Dai2@halliburton.com
Treasurer: Zheng Gan, Core Laboratories, Zheng.Gan@corelab.com
Secretary: Constantine Vavourakis, Paradigm, Emerson, Constantine.Vavourakis@emerson.com

Chicheng Xu

Michael Ashby

Bin Dai

Zheng Gan

Zheng (Jon) Gan

Constantine Vavourakis