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Prediction of Salt Boundaries using Deep Learning Neural Network

Salt segmentation from subsurface seismic data can be quite challenging and time-consuming, even for an experienced human interpreter...

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Investigating Invisible Lost Time (ILT) on Textual Data using Artificial Intelligence

During the well construction process, every activity is carefully described and recorded by the onboard crew. This produces a massive amount of textual data in daily rig reports.

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Overcoming Trust Deficit and Improving User Adoption of AI with Trust-First Modeling Approach

As the adoption of Artificial Intelligence (AI) expands across the business sectors, so does the public debate around its limitations and vulnerability to malfeasance and human biases...

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Accelerate Seismic Domain Conversion using Artificial Intelligence

Seismic data is a key component in the E&P industry; however, accurate measurement of subsurface parameters is usually acquired through well logging. Let’s look at the differences...

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Accelerate Carbon Capture Storage Innovations with Artificial Intelligence

Reduction of greenhouse gas emissions into the environment is a key requisite for ensuring a healthy and sustainable planet. The initiative has gained rapid momentum and almost all...

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Optimize Rate of Penetration for Maximum Productivity using AI

Well planning and drilling is a highly complex procedure that incorporates several factors and parameters to ensure maximum productivity. Amongst these, the Rate of...

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Leveraging Big Data and Data Science to Enable Digital Transformation of the Upstream Oil and Gas Industry

Most major oil companies today have embarked on digitalization programs in response to the impact of cumulative downturns...

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Put Your Data Up Front and Center

Finding and collating data can be incredibly time consuming, taking up to 70 percent of an E&P professional’s time. With 10 TB of data being created per well per day, the challenge is not getting any smaller. If we as an industry are to make the most...

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A Machine Learning Risk Management Framework for Sustainable Oil and Gas Solutions

Artificial intelligence (AI) and associated machine learning (ML) algorithms and models are generating new insights from the dark data in the oil and gas industry. As the AI/ML models are...

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Fluid Likelihood Prediction - A Data-driven AI Approach

One of the most important factors in successfully identifying reservoirs and estimating realistic reservoir parameters is to understand play characteristics within the associated geology...

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Enabling Artificial Intelligence and Machine Learning Through Talent Transformation

AI/ML is seen as a key enabler of digital transformation by the E&P companies. But what enables AI/ML? The following article is the first in a 4-part blog series, which explains four success...

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Sharpen Your Subsurface Understanding with Assisted Lithology Interpretation

The volume of legacy data within the oil and gas industry is vast, with new data being generated daily. This data needs to be integrated and interpreted consistently to better understand...

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DecisionSpace® 365 and Open Subsurface Data Universe (OSDU)

A Cloud-based, subscription service for E&P applications to empower you to be creative and help realize your objectives. It’s a sure way to meet your business goals and transformation..

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Transformative Intelligence for E&P

Over the last decade, oil and gas companies have understood the need to embrace cloud, artificial intelligence, and machine learning technologies to remain competitive in a changing industry.

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Optimizing Seismic Fault Interpretation with AI and Cloud Technologies

The interpretation of faults in 3D seismic data is a critical component of hydrocarbon exploration and development workflows. Faults frequently control factors such as reservoir compartmentalization and fluid migration and may create drilling hazards

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Automated Borehole Metadata Quality Management Using an AI approach

Operators are inundated with vast and growing volumes of digital borehole data as the number of logs, cores, surveys and petrophysical analyses per well is growing

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Put Your Data Up Front and Center

Finding and collating data can be incredibly time consuming, taking up to 70 percent of an E&P professional’s time. With 10 TB of data being created per well per day, the challenge is not getting any smaller. If we as an industry are to make the most...

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Enabling Artificial Intelligence and Machine Learning Through Talent Transformation

AI/ML is seen as a key enabler of digital transformation by the E&P companies. But what enables AI/ML? The following article is the first in a 4-part blog series, which explains four success...

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Webinars

An Explainable Artificial Intelligence Model for Fluid Likelihood Estimation using Pre-Stack Seismic Data

One of the most important factors in successfully identifying reservoirs and estimating realistic reservoir parameters is to understand play characteristics within the...

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Optimize Seismic Domain Conversion Efficiency with Artificial Intelligence

Domain conversion of seismic data using a well-calibrated velocity model is currently the most common method for estimating subsurface depth during exploration. However...

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Managing & Making the Most of Your Seismic Data on the OSDU™ Platform

Digital transformation of Exploration & Production (E&P) data has the potential to save millions of dollars in costs, while enhancing productivity, by bringing greater accessibility to...

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Optimize Rate of Penetration for Maximum Productivity using Artificial Intelligence

The Rate of Penetration (ROP) is a key criteria for achieving an efficient and productive drilling operation. The ideal ROP depends on multiple geological and operational factors and...

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UAE: Next Generation Information Management and National Data Repository

Integrating ever-growing quantities of complex E&P data efficiently and effectively remains a core challenge to the industry, and if left unaddressed, can compromise our ability...

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The Power of Collaboration and Innovation in Enterprise Data Visualization for E&P Companies

Lack of effective integrated visualization of subsurface data too often prevents productive collaboration among exploration...

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Overcome Well Positioning Challenges using a Digital Ecosystem

Analyzing all possible scenarios using historical data collected from multiple E&P domains (geology and geophysics, well construction, production, and reservoir) to decide well...

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The Transformation of Well Construction Data Management Health Checks

This webinar will be about data management from the well construction point of view. The oil industry has been generating safety-critical and very expensive data since its beginning...

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Optimize Seismic Interpretation with AI & Cloud Technologies

The interpretation of faults in seismic data is a critical component of hydrocarbon exploration and development workflows. However, the traditional methods of interpreting...

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Integrating Data through the Exploration Workflow. A Case Study of the Zambezi Delta

We will use the Zambezi Delta, offshore Mozambique, to demonstrate how an incomplete regional dataset can be used in the initial exploration and appraisal stage of the petroleum...

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Investigate Invisible Lost Time (ILT) on textual data using Artificial Intelligence

During well construction, every activity is carefully recorded by the onboard crew, and this produces a large amount of textual descriptions in the daily rig reports. Later, these descriptions...

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Data-Driven Modeling – Digital Twin for Corrosion Flow Assurance

The prediction of corrosion rate and its migration is of paramount importance to the oil and gas industry. In fact, according to the National Association of Corrosion Engineers...

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Automated Oil and Gas Metadata Quality Management Using AI

A metadata, simply put, is data about data. Essentially, these are meticulously catalogued information across various domains that are categorized based on keyword and subject...

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Are you able to put the data you need at your fingertips?

Learn how we can help you spend less time finding data and more time improving the accuracy of your interpretation in this webinar recording.

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Accelerate Carbon Capture Storage Innovations with Artificial Intelligence

Carbon Capture and Storage (CCS) is the process of capturing Carbon dioxide (CO2) formed during power generation and industrial processes and storing it to prevent its emission into...

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From Deep-Time to the Future: Discussing the Development of Next-Generation Plate Models with Examples from the South Atlantic

The South Atlantic played a key role in the formulation of plate tectonic theory, and plate modelling has come a long way since the very first computer-assisted reconstructions

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