Use Your Data to Stay Ahead of the Curve

Kami Keim is Director of Product Development at Ovation Data. Her 27+ years of experience within the oil & gas sector includes organizations such as Schlumberger, Equinor and Spinnaker Exploration. She has held leading roles in transforming information management strategies and was the custodian of one of the largest seismic databases in the Gulf of Mexico. Keim’s specialist expertise is in geophysical and geological data management and technology.

Oil companies are entering their next chapter of grappling with big data, and taking it beyond a previous focus on data management. They are still evolving their approaches to access and security, and have learned a lot in the process. They understand more fully the complexities of finding their data, sharing it, and addressing its deteriorating condition. Now, innovative teams are looking to reap greater ROI from their organization’s data, establish their big data in its rightful place as a profit center, and explore ways to actually monetize it. Advances in AI and machine learning are accelerating this evolution.

Previous challenges remain

The energy industry recently celebrated 100 years of using seismic reflection data in exploration, and that represents a huge amount of information and much of it predates digital data deliveries. A great deal of data is contained in old media and unusable formats, so companies need help in making data readable, accessible, and usable. Even when the data is online, many companies still struggle with finding what they need.

Technology to the rescue

Fortunately, expertise is available to meet the challenge. For example, an oil company wants to leverage data trapped in an old or proprietary seismic format but is unable to migrate it into the latest SEG-Y format for use in today’s software for analysis. Fortunately, we can extract the data from old media, migrate it from outdated formats, and convert it from locked data into a ready-to-run resource. Subject matter experts perform quality control by cleaning out bad shot points, reading wavelets and shot point locations, and creating a current SEG-Y file to load into interpretation software where it can be used.

A more extreme scenario relates to an oil company with valuable data contained in tapes that were submerged under water for a full year after Hurricane Katrina. The client viewed the situation as insurmountable, but we recovered 100 percent of the data. Our technology is not limited by format, and we can read data contained on film, paper, microfiche, or digital, and make it ready to run.

Transcription buyers beware

Data must be readily available and in a usable format to avoid delays in making data-driven decisions. Yet some transcription providers perform only a bit-to-bit copy of clients’ data from old media, and implement quality control and reformatting just when the data is actually needed. This leaves decision makers waiting for data to be found and then restructured before it can be used. This approach is like fixing a hole only when a leak arises, rather than ensuring the roof remains waterproof.

In addition, many of these same companies place a proprietary wrapper around datafiles which clients cannot penetrate without buying additional services even after they have paid for transcription, storage and maintenance. Be sure to select a service provider that stores data in native formats without wrappers unless encryption is specifically requested. Fortunately, Ovation has developed methods to break wrappers applied by other storage vendors, and we can unlock data for clients to use in a new format going forward. Also watch for egress fees (which we view as “ransom”) charged by some providers in order for clients to retrieve their own data.

Selecting a data management partner

Reputation and the quality of the client experience are so important. Clients want a competitive, differentiated, and customized offering of services that solves their specific needs along with a single point of contact and personal one-on-one interaction.

Everyone wants their strategies to be supported by top-notch approaches and not lagging behind, so another key aspect involves partnerships. Ask your prospective data management partner how it leverages its own partners’ latest technology for the benefit of its clients. Who are they working with to integrate the best of new technology and the highest level of innovation, deployed as rapidly as possible?

Advantages of AI and machine learning

Wanting more than storage and disaster prevention, companies want to make data available for new tools such as AI and analytics but data must be in the proper format and readily accessible to leverage these new technologies and unlock its true value. Only then can an AI system do the heavy lifting of personnel and time-intensive operations, or can an analytics package sum up and display vast data quantities in meaningful, automated displays that facilitate timely decisions.

Traditionally, someone had to painstakingly comb through the data set and look for trends, often misinterpreting or missing key indicators altogether. AI systems are trained to search for fundamental indicators and highlight them. This technology holds great promise in many areas, seeing more of what is present now and predicting what may appear later.

Extract data value and generate revenue

One way for companies in the energy industry to transform idle data into a profit center is by disseminating data sets and then offering potential buyers a flavor of data available for purchase and a space to view it. Companies can decide to re-license their proprietary seismic data from certain plays where they are not currently drilling. Our software can vectorize a seismic section and well logs, take it from analog to digital, create meta data, then make it fit for purpose. In short, we can vectorize your seismic data for use in new exploration software, and we can reformat well data to read trends. We can digitize your x-ray images to feed AI models, migrate your media files to take advantage of the newest remastering techniques, and more.

What’s next?

Taking data management to the next level means driving its evolution from transcription to digital and beyond. Good data governance policies run the gamut from how data comes in, who encounters it along the way to extract value and add value, to determining its final resting place and capturing metadata that enables access and provides relevance. On the horizon are even more effective ways to share data and use our private cloud to reduce the burden. Excellent expertise, unique proprietary tools, and exciting innovation will continue to improve analysis and leverage the growing benefits of AI and machine learning. The future is indeed bright!

Guest Blog: The Impact of Technology Convergence on Clean Energy

Written by: Jolie Brimm

Investing in clean energy benefits industries in several ways. The World Economic Forum states that it creates jobs for people in times of economic distress such as global health crises. Green investments develop more near-term careers compared to projects involving fossil fuel use. Another benefit is that it reduces businesses’ and sectors’ dependence on fossil fuels. As a nonrenewable resource, fossil fuels will eventually be depleted. Reducing its use allows for better conservation and environmental contribution.

These transformations are fortunately rapidly taking place, with the book The Future Is Faster Than You Think outlining how this may impact the world within the next decade. In the book, Greek-American engineer Peter H. Diamandis and journalist Steven Kotler find that technologies like artificial intelligence (AI) and robotics are developing far more quickly than expected. As a result, these greatly influence how we live—specifically, how industries operate. Here are a few ways technology is impacting clean energy:

It reduces energy waste and carbon emissions

Clean energy should not be wasted. Wasteful consumption is a terrible practice for industries and businesses, but technology prevents this. AI in smart energy monitors can connect to establishments’ energy meters and collect power consumption data. Aside from this, it identifies when and where energy wastes occur. With this technology, people in charge immediately address the causes of waste and prevent further misuse.

In the oil and gas industry, AI, machine learning, and advanced analytics monitor and analyze machines in real time for operational effectiveness. With these tools, oil and gas operators can identify and resolve machine issues contributing to carbon emissions. For example, AI can determine how to reduce gas flaring during oil extraction, reducing harmful CO2 emissions.

It optimizes energy systems

In line with preventing energy waste is the efficient use of clean energy. Ensuring that necessary groups receive adequate energy is essential for industries to operate smoothly. A Frontiers in Energy Research study notes that the Internet of Things (IoT) is contributing to clean energy sharing by connecting energy data to the network, and optimizing the energy system. With this technology, businesses distribute energy more efficiently across different groups.

The energy supply chain also benefits from AI and the IoT. Geothermal power plants use the IoT in predictive failure diagnoses and performance monitoring. Sensors detect signs and alert operators of system failures when equipment is in use. These promote geothermal energy’s utilization, proving that it can be a reliable energy source. In the long run, this can serve as a win for carbon neutrality, as geothermal energy is renewable and has a low carbon footprint.

It helps carbon capture become more efficient

Carbon capture, utilization, and storage make decarbonization possible by capturing CO2 before it is released into the atmosphere. CO2 is then transported through a pipeline to be stored underground. The problem here is the danger that comes with CO2 transportation. CO2 is highly corrosive, so pipeline leaks result in groundwater contamination.

Professionals use digital twin representations—virtual models representing pipelines in real-time—to address this issue. They monitor CO2 transportation and pipeline conditions through exception-based surveillance. This way, leak detections and pressure and temperature changes are addressed before they cause more extensive damage.

It increases access to energy storage and supply

The development of electric vehicles is revolutionary. Rechargeable cars are reducing fossil fuel consumption and are currently being examined as a source of energy. In his book Renewable Energy: Ten Short Lessons, climate change and energy professor Stephen Peake states that electric vehicles have the potential in becoming a mass source of electricity storage and supply due to bidirectional charging. This allows electric vehicles to absorb power from the grid and supply others. For instance, electric school buses in the summer could store energy for the communities during power outages. These buses can also deliver energy to remote areas with limited power.

In mining, companies are looking toward renewable energy and battery projects to power their activities. Because mining operations are remote and not connected to the electrical grid, they garner energy from transported fossil fuels. Delivering fossil fuel to remote locations is not only expensive but also a contributor to carbon emissions. Using renewable energy stored in large-scale batteries removes their dependency on harmful fossil fuels.

Our post ‘Energy Transition Stories to Help Navigate Your Future Career’ emphasizes that the transition to clean energy will take time. However, these technological advancements are making the process quicker and more efficient for industries and society.

About the Author: Jolie Brimm is a UK-based freelance writer who enjoys writing feature articles on the latest in technology. 

EAGE Digital Startup Spotlight: AgileDD

EAGE Digital recognises the role of Start Ups and Entrepreneurs in pushing innovation and new ideas for digital transformation initiatives. The Start Up Spotlight features Henri Blondelle, Co-Founder of AgileDD.

Why did you start AgileDD?

AgileDD was created in Houston in 2016 but the project itself started in 2015 when the three founders were working in the Data department of CGG. At this time, we realized the new concept of data lake and the new generation of analytical tools based on AI will increase the need for structured data to feed the data-based decision process. At this time, the way of capturing information from documents was very labor intensive and the use of the few tools based on deterministic rules was quite limited.

We got the intuition that the new generation of AI tools made available since 2012 could be useful to extract automatically and at scale the key business information locked in the unstructured formats such as the scans of the reports, the PDF files, the graphic files, or any other unstructured formats. The starting idea was very simple: if a machine learning can detect a cat and a dog in a picture, it should be possible to train it to detect a total depth or the volume of an air gun in a report! We initiated the concept of the IDP (Intelligent Document Processing) much before it became trendy!

What is the biggest data challenge today for companies in oil and gas?

At the end of the day, is to provide to decisions makers data they trust. It is really not an easy challenge and it is even more difficult than being able to measure all the dimension of the data quality. At AgileDD, we think it is achievable if the end users are placed in the middle of the data processes and can understand from where the data are coming and how they have been processed securely.

What steps can organizations take to maximize the value of their data?

That is a really difficult question, even, I guess, for an experimented CTO. As it was said some time ago by the DAMA, implementing an efficient data management in an organization is depending of the data governance team capability to clearly understand the company business, culture, tools, organization and to translate these “environmental elements” into “data activities”. The main steps are always the same: Adopting standards, building solid reference and master data to insure the data interoperability, Adapting the data architecture to the business changes (and not the opposite!), Manage the data quality, don’t forget about the data security. But the real art is to put all the steps together in a rapidly changing technical world.

Do you already have any interesting use cases?

Starting from the Oil & Gas domain, we have developed some new business in the Mining, Water Treatment and the US Defense sectors. I think the experience we have gained during this journey may interest our visitors.

What do you hope to achieve at EAGE Digital 2022?

At first, it will be a real pleasure to meet data scientists, geo-professionals, and students in-person after long months of discussions in video calls, chats and other slack channels! So, the first objective is to socialize again and re-invent what should be the subsurface data management once again around a beer or two with friends!

We would like also to show that the IDP domain is progressing very rapidly and some challenges like capturing handwritten values from SCAL, PVT, Geochemical reports which were not possible 2 years ago are now in production. We hope that the experience we gained recently with the Mining and Defense sectors could be reused for some new subsurface data challenges. We have various demos for the ones visiting our booth, and it is the second objective.

The last one is also to figure out how we are in the competition and understand from the visitors how our platform should continue to progress to support their new challenges

If all that can be achieved in Vienna, it will be a great event!

Interested in learning more about AgileDD, visit their website here.

EAGE Digital recognizes the importance of Start-ups and entrepreneurs, and therefore we are offering start-ups a special discounted fee and speaker participation. We’re looking for innovative and disruptive technologies that transform the digital space not only in Oil and Gas, but across different applications of geoscience and energy transition.

Learn more about signing up as a Start Up company for EAGE Digital 2022.

 

EAGE Digital Talks: Digital Ecosystems

Watch this recording from the EAGE Digital 2020 conference featuring Martin Galavazi (Fugro) in discussion with key industry players on the dynamics of digital ecosystems and managing the complex aspects of collaboration and partnerships.

The success of a digital ecosystem therefore depends on both relational and technical aspects. Relational aspects may include mutual commitment and transparency of partners, fear of supplier lock-in and focus on the ‘win’ of the other. Technical aspects may include data exchange formats, connectivity standards and system integrations for instance. How can we encourage both the relational as well as technical aspects that are required to deliver on the potential of digital ecosystems in large scale energy operations? How can we also leverage new technology partners and foster open collaborations with traditional competitors?

Panelists include:

• Jamie Cruise, Head of Products for Data, Digital Subsurface Solutions – Schlumberger
• Ali Al-Mujani, Chairman and CEO – Target Group
• Andreas Blumauer, Founder and CEO – Semantic Web Company

Interested in more discussions like this? Join us at EAGE Digital 2022 to discuss the key challenges and emerging solutions in digital transformation for the energy industry.

EAGE Digital Insights: Special Topic First Break focuses on Digital Transformation in Geoscience

Geoscientists are utilizing artificial intelligence to do the work once done by human minds. People are consequently freed up to focus on the bigger picture. The July issue of First Break magazine showcases the latest digitization initiatives in the industry that are enabling energy companies to improve exploration of new and existing fields and also ramp up for the energy transition.

• Sergey Alayaev et al demonstrate a workflow for geosteering in an outcropbased synthetic fluvial succession and explain why their method reduces uncertainty and correctly predicts most of the major geological features.
• Tsimfer Sergey et al present the deployment of machine learning at one of the world’s largest oil companies.
• Alex Katashov et al analyse a new digital platform combining the use of actual downhole data, machine learning, and verification of the results obtained with hydrodynamic simulators.
• Nicholas T. Okita et al show how cloud computing helps to improve ESG type practices while also providing a cheaper alternative to the huge cost of acquiring an infrastructure.
• Roberto Ruiz et al explore the potential of mining an extensive petrophysics and rock physics well database in the Norwegian Sea through advanced machine learning algorithms for estimation of reservoir elastic properties, and what it could mean for the optimization of workflows.
• Philip Hargreaves et al discuss how digitization is helping the geoscience profession to widen its scope in the search for cleaner sources of energy
• Paul Genberg presents a new a new exploration studio that is using AI to break down silos and help its young geoscientists to flourish.

Visit the EAGE First Break website to read the articles in this special issue.