TUESDAY, 24-JUN-25 12:30
TUESDAY, 24-JUN-25 12:30
"Rock Imaging Data Management & Software Tools"
Successful core digitisation depends on many factors; two of the most important are the management of the huge volumes of data that are generated, and software tools to process, visualise and interpret the multi-modal, multi-resolution, image data. The digital core repository, just as with its physical twin, must be designed to receive, store and deliver data efficiently. With potentially tens or hundreds of terrabytes of data, this is not a trivial challenge. The repository must also be equipped with tools for data visualisation and quality control, so that end users have access to integrated, validated and fully curated core and cuttings data sets.
Software is central to this extraction of knowledge from the data. Whether it is public-domain, open-source, python libraries or proprietary algorithms developed over many years, data processing and interpretation software is as indispensable to the modern geologist as the trusty hammer.
This webinar will bring together a group of experts in the field of core digitisation and rock image processing who will present detailed accounts of the tools they have developed to implement reliable digital core repositories and use advanced software tools to extract reliable rock properties.
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BIO: Christian Hinz
2015 M.Sc. in Geosciences from University of Mainz (JGU Mainz)
Hydrogeology, Field-scale Modeling, Digital Rock Physics
2015 – 2018 Doctoral studies at University of Mainz
“Reactive flow in porous media based on numerical simulations at the pore
scale”
Digital Rock Physics, Code development, Digital carbonate dissolution
2019 – 2021 Application Engineer DRP, Math2Market GmbH, Kaiserslautern
DRP Application Engineering
DRP Trainings and Support
2021 – now Business Manager DRP, Math2Market GmbH, Kaiserslautern
DRP Business Development
DRP Team Management
SUMMARY:
Digital Rock Physics (DRP) and Digital Core Analysis represent the digitalization of Routine and Special Core Analysis (SCAL). With the maturing of the technique, DRP now shifts from research and development (R&D) to exploration and production (E&P). This goes along with new requirements that are facilitated by cutting edge cloud-hosted digital platforms. We present a professional software suite combining the high-performance numerical solutions, workflow automation, and the prediction of reservoir rock parameters required for E&P workflows.
The typical DRP workflow begins with 3D image processing and segmentation of 3D gray value images of reservoir rocks obtained by a variety of image acquisition devices. Based on the resulting voxel-based geometry, the geometric properties of digital rocks are determined, including pore analysis, material analysis, and identification of individual pores, grains, and fractures. For SCAL digitalization, the determination of transport properties in digital reservoir rocks is a key capability. Among these properties, the presented software package predicts the absolute permeability of porous and microporous reservoir rocks, computes capillary pressure curves in mixed-wet systems, and determines the relative permeability curve. Further features are the determination of electrical properties and of overall mechanical properties, computation of rock deformation and failure. Latest developments include the currently highly demanded incorporation of geochemical reaction capabilities for acidizing treatments and CO2 sequestration setups.
All the above capabilities are combined in the commercial DRP software package GeoDict®, the all-in-one solution for this paradigm shift in the oil and gas industry.
BIO: Daniel Austin
Daniel is Global Business Development Manager for Earth Science Analytics and has over
10 years of experience in geosciences. Originally from the United Kingdom, Dan has a range of experience in E&P especially with the Atlantic transform margins and West Africa. He received both his bachelor’s and master’s degrees from the University of Southampton.
SUMMARY:
The recent history of hydrocarbon exploration consistently indicates the advantages of integrating knowledge and data derived from different disciplines such as basin modelling, structural geology and geophysics. The availability and scale of data from different basins, as well as the quality of the data have dramatically increased over the last 30 years.
Despite this increase in data quantity and quality, conventional data analysis approaches have suffered from two challenges that hinder making data driven decisions in the oil and gas industry. Firstly conventional approaches have limitations that prevent the use of all available data. The second challenge has been the lack of appropriate data platforms to facilitate the easy integration of different data types and domains.
Here we present how modern data-centric approaches such as those used by Tesla, Amazon and Netflix can be applied to subsurface data and unlock the value of these vast datasets through query, visualisation and end-to-end integration.
As part of this workflow we will show how a modern software platform can empower geoscientists to analyse 1000’s of images rapidly utilising both their expertise and trained machine learning models.
The proposed workflow is implemented in the EarthNET platform which enables us to efficiently integrate human experience, skills, and knowledge with models derived using the latest ML algorithms. At the heart of the platform lies a dynamic database system (EarthBANK) which not only serves as the starting point of every subsurface study but also contributes at every stage of data analysis, through smooth data (any type of data such as well, and seismic) and model results exchange.
First, we will demonstrate how to manage large collections of rock images via a web browser and show how our collaboration with Rockwash Geodata is unlocking the value within these large datasets.
We will then follow these interpretations through the digital underground, a workflow that includes four main stages starting with well data analysis and ending up in data-driven distributions of different properties required for risk and volumetric estimations together with corresponding uncertainties.
In conclusion, through a modern data platform we are able to pair state-of-the-art technology with robust subsurface datasets and facilitate unprecedented improvements in efficiency, accuracy and safety that include:
i) the integration of data and disciplines,
ii) enables geoscientists to exceed current best practice with the ML tools available today, and iii) paving the way to the "new" best practice which is integrated data science and geoscience.
BIO: Gwenole Tallec
Gwenolé Tallec
Product Expert / Business Development
Thermo Fisher Scientific
Gwenolé Tallec has had his master degree from the University of Bordeaux, France in 2002, in computer science, image processing and 3D graphics programming. He focused in Digital Rock Analysis in 2010, and is one of the PerGeos Expert at Thermo Fisher Scientific, delivering training courses, defining workflows at customer sites, and linking users and software’s R&D.
SUMMARY:
The amounts of rock imaging data generated is swelling to a point where conventional data management systems struggle to keep pace. Different types of instruments and software, in various locations, at multiple scales, produce significant amounts of data, all of which need to be shared among collaborators.
During this webinar, you will learn how Thermo Scientific™ Athena™ Software, the premium imaging data management platform, when combined with PerGeos™ Software, will allow you to easily centralize, organize, view, analyze and share rock imaging data.
What you will learn:
- How to optimize your imaging data management
- How to improve collaboration
- How to simplify your multiscale imaging workflows