Explorer Geophysical Corner

The past few years have seen increasing interest in the application of machine learning techniques in the industry, specifically in seismic interpretation. Over a clastic Tertiary clinoform interval in the public F3-Netherland dataset, we benchmarked advanced neural network algorithms against standard probabilistic lithology classifications from seismic data, to understand their benefits and limitations, and to check which approach works best under which circumstances.

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American Association of Petroleum Geologists (AAPG)
Explorer Emphasis Article

Researchers generally say they are scrambling to keep up with the changing needs of the oil industry combined with the emerging, broader concerns of society. Amazingly, technology research for oil and gas continues to flourish even now, despite some recent problematic headwinds. And even though computing-related technology gets most of the attention these days, today’s energy research extends far beyond Big Data and its applications.

American Association of Petroleum Geologists (AAPG)
Explorer Geophysical Corner

“Machine learning” has become a common phrase in geophysics. These methods, based on complex algorithms and statistics, allow geoscientists to speed up and improve their interpretations. However, as interpreters, we can feel intimidated and concerned about how much of our expertise can be replaced by machine learning algorithms. To better understand the limitations, we assess the importance of human validation and participation in one machine learning process, highlighting the upsides and downsides of a machine-derived process versus a geoscientist-guided selection of attributes. As Earth scientists, we explored a suite of seismic attributes and selected those that were meaningful for interpreting a deepwater channel system and compared our results with the attributes derived from principal component analysis.

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American Association of Petroleum Geologists (AAPG)
Asia Pacific Blog

International Energy Summit 2020 24-25 October 2020 Artificial Intelligence systems can process millions of data streams to provide actionable insight that compliments human skills. Hence, creating a higher efficiency in fulfilling the increasing demand of energy that oil and gas can serve. In light of hoping to broaden the knowledge of utilizing such artificial intelligence in this field, this year, International Energy Summit (IES) 2020 brings up the theme of 'Artificial Intelligence: Challenges and Innovations for Petroleum Industry.' There were three series of events, grand seminar, career talk, and infographic competition, and four great speakers who graced our event: Mr. Bruno de Ribet as Global Director, Strategic Projects at Emerson E&P Software, Mr. Robert “Bob” C. Shoup as Chief Geologist for subsurface consulting & Associates LLC and the Director for Clastic Reservoir System, Mr. Suwarta as an Assistant Manager Upstream Data Science at Pertamina, and Mr. Epo Kusumah as a lecturer in Universitas Pertamina.

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American Association of Petroleum Geologists (AAPG)
Explorer Geophysical Corner

As discussed in part 1 of this article, when it comes to the attributes used in equation 1 for seismically determining shale capacity, it is difficult to make a manual choice for the cut off values. To alleviate such a problem, application of machine learning techniques could be useful and thus worth exploring.

American Association of Petroleum Geologists (AAPG)
Explorer Geophysical Corner

The goal of reservoir characterization work carried out for a shale play is to enhance hydrocarbon production by identifying the favorable drilling targets. The drilling operators have the perception that in organic-rich shale formations, horizontal wells can be drilled anywhere, in any direction, and hydraulic fracturing at regular intervals along the length of the laterals can then lead to better production. Given that this understanding holds true, all fracturing stages are expected to contribute impartially to the production. However, studies have shown that only 50 percent of the fracturing stages contribute to overall production. This suggests that repetitive drilling of wells and their completions without attention to their placement must be avoided, and smart drilling needs to be followed by operators.

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American Association of Petroleum Geologists (AAPG)
Asia Pacific Blog

AAPG Asia Pacific is proud to announce two new AAPG Asia Pacific Presents talks, featuring Bruce Ainsworth and Gretchen Gillis. AAPG Asia Pacific Presents is a collection of online presentations being offered free of charge. The 60-90 minute session will be conducted through Zoom, and will be followed by a short Q&A period, handled by a moderator. To register for one or both of these talks, click on the link(s) below. Registrations will be accepted on a first-come basis.

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American Association of Petroleum Geologists (AAPG)
Explorer Emphasis Article

As so much in the oil and gas industry relies on expert interpretation over unstructured data and understanding of elaborate geological concepts, tracking the production and consumption of conceptual knowledge and information is crucial. Systems need to be developed that can capture these interpretative trails in order to meet the needs of exploration. IBM’s Hyperknowledge Trails may just be that system.

American Association of Petroleum Geologists (AAPG)
Events Blog

Part of AAPG’s GeoAnalytics Credentialing Program, this two-day online AAPG Short Course, Excel-Based Random Forest Machine Learning Algorithms: Programming and Application 2.0, is set to take place 28–29 April 2020 for web-based participation only. 

American Association of Petroleum Geologists (AAPG)
Events Blog

Part of AAPG’s GeoAnalytics Credentialing Program, this two-day online AAPG Short Course, Excel-Based Random Forest Machine Learning Algorithms: Programming and Application, is set to take place 14–15 April 2020 for web-based participation only. 

American Association of Petroleum Geologists (AAPG)
Workshop
Virtual Workshop
Wednesday, 17 March Thursday, 18 March 2021, 8:00 a.m.–5:00 p.m.

This workshop will focus on advances made in petroleum systems analysis as a predictor of hydrocarbon presence, new technology and applications, and future directions of this important geological tool.

American Association of Petroleum Geologists (AAPG)
Webinar
London, England
Wednesday, 1 July 2020, 12:00 p.m.–1:00 p.m.

This presentation and demonstration will focus on a machine learning workflow in the upstream Oil and Gas domain to predict formation tops by applying artificial intelligence and machine learning techniques to learn the well logs signatures. This deep learning model provides high quality predictions to aid the geologists in picking lithology markers consistently and in an accelerated fashion thus boosting their operational efficiency. The self-learning model, which is a unique differentiator of dataVediK and encompasses the detection of outliers and data quality issues and their subsequent validation and suggested corrections to improve the quality of data in an automated fashion during the model training process. The demo will then showcase a real-time drilling solution built using this ML model, whereby the formation tops are predicted, and the structural model is updated automatically as the GR log is acquired.

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American Association of Petroleum Geologists (AAPG)
Webinar
Virtual Webinar
Wednesday, 24 June 2020, 7:00 p.m.–8:30 p.m.

Join us for the 'New Directions in Automation' webminar. Where the opportunities are now, and how to pivot and take advantage of them. Webinar will be presented via Zoom 7:00pm to 8:30pm CDT, 24 June 2020.

American Association of Petroleum Geologists (AAPG)
Webinar
Virtual Webinar
Wednesday, 28 October 2020, 12:00 p.m.–1:00 p.m.

There are many studies that talk about the economies of scale associated to cloud storage that make it so cheap. Yet oil and gas companies managing petabytes of seismic data are not jumping on the cloud storage bandwagon. In this talk, Suri Bhat, Vice President of Sales and Marketing at Bluware, will explore why moving petabytes of seismic data to the cloud is difficult. He will share some of the true costs of managing large data sets in the cloud and why it doesn’t add significant business value. In the same way that lifting and shifting legacy tools and services to the cloud yields little value, moving seismic data to the cloud also yields little value. It isn’t until applications, workflows and even the data storage formats are re-engineered that real business value and even cost saving can be found. He will explore how this is possible today with open file formats. Webinar presented via Zoom on 28 October 2020 at 12:00 London time (UTC-0)

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American Association of Petroleum Geologists (AAPG)
Webinar
Virtual Webinar
Monday, 9 November 2020, 12:00 p.m.–1:00 p.m.

Belmont develops Sandy. An AI accelerated platform dedicated to identifying risks and opportunities by fusing subjective human interpretations within an objective digital representation of the world. Sandy can make sense of a large corpus of information, automatically organising the knowledge it contains and making it ready for your daily utilisation to build a solid cognitive foundation of your projects. Discover how in this talk.

American Association of Petroleum Geologists (AAPG)

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