Swastika Nevaskar shares best practices on quality control for multi-client, multi-environment seismic data

“The seismic landscape is evolving, and with it, the challenges and opportunities. As we navigate the complexities of multi-client, multi-environment data, quality control isn’t just a best practice—it’s the bedrock of our industry’s future,” mentions Data Scientist Swastika Nevaskar.

Data is a multifaceted instrument, but its intricacy is particularly pronounced in the seismic sphere, which operates on a multi-client and multi-environmental scale. Within this realm, data isn’t merely a collection of signals; it’s a confluence of subsurface reflections gathered from diverse terrains and licensed to multiple stakeholders.

According to geophysicist and data scientist Swastika Nevaskar, the challenge lies in capturing these seismic echoes, deciphering them across varied landscapes, and catering to the diverse needs of multiple clients. This multi-layered approach amplifies the complexity and indispensability of data in the seismic world.

In this narrative, quality control standards are crucial. In her more than a decade of experience in corporate data management, Nevaskar has developed best practices that have allowed her to navigate the industry with confidence.

Best Practices in Quality Control

Multi-client and multi-environmental data scenarios are complex, and the margin for error is minimal. Quality control ensures the accuracy and reliability of the data, which in turn influences critical business decisions.

Drawing from her vast professional experience and strong educational background, Nevaskar shares some of the best practices in navigating seismic data processes she has honed over the years:

• Rigorous Data Acquisition: One of the foundational steps in ensuring quality is to have thorough data acquisition standards. Nevaskar emphasizes the importance of collecting raw data of the highest caliber, whether through both granular and actionable or with tools like Omega2 and Reveal. Leveraging from her experience, as Nevaskar used a new internal data processing technology such as REVEAL’s latest land data processing modules, she ensured the comprehensiveness and accuracy of data. She shares, “Data is the foundation of our work. If the foundation isn’t strong, everything we build on it can crumble.”

• Targeted Techniques: Nevaskar believes every environment and client need is unique. As seismic data can be acquired in various settings – land (onshore), marine (offshore), transition zone, and borehole (VSP – Vertical Seismic Profile), the need for tailored processing techniques is paramount. This is when tools like GeoTomo’s ThrustLine and TomoPlus are helpful when processing onshore data. Data scientists with these can customize data processing to suit specific project requirements, ensuring optimal targeted results.

• Continuous Validation and Verification: The stakes are high in the intricate landscape of multi-client, multi-environment seismic data. Companies often acquire diverse data types, from reflection and refraction data to passive seismic readings and from marine and land seismic data to time-lapse and transition zone recordings. Given the variety of sourced data, they subsequently process, interpret, and license this information to many clients.

With this multifaceted nature, Nevaskar underscores the imperative of consistent validation and verification stages within the data processing pipeline. She believes any discrepancies or anomalies will be promptly identified and rectified by instituting regular checkpoints tailored to each data type. This rigorous approach not only safeguards the integrity of the data but also guarantees that the end product delivered to clients is of unparalleled quality.

• Integration of Geoscience and Data Analytics: Nevaskar’s transition from geoscience to data science was strategic. She believes that the future of seismic data lies in integrating traditional geoscience knowledge with modern data analytics, such as Python, Tableau, Supervised/Unsupervised Machine Learning, and Stats Models. This comprehensive skill set will empower organizations to identify valuable assets with precision. She is convinced that integrating traditional geoscience knowledge with contemporary data analytics paves the way for deeper insights and more informed decision-making.

• Stakeholder Collaboration: Given Nevaskar’s experience managing large projects and delivering strategic wins, she understands the value of continuous communication and stakeholder collaboration. When handling multi-client projects, Nevaskar advises ensuring the team works on aligned goals to achieve above and beyond the goals. She believes a successful project is a product of close planning and consistent checks within the team to ensure smoother project execution and better results.

Based on her experience, she successfully obtained multi-line optimal images using Omega as she guided a 20-person team through each intricate stage of the processing stream—from procurement and price negotiation to vendor quality control. This was further exemplified when she built a group of 15 to 25 professionals, spearheading 6 data science and business analytics projects that pioneered methods that slashed company cycle times by a staggering 50% at a Fortune 500 company.

Nevaskar’s Best Practices in Action

Nevaskar’s journey in the industry is marked by over 12 years of experience delivering pristine subsurface images for intricate geologic environments through seismic data processing and imaging. Her expertise is evident from her track record of managing projects worth approximately $200+ million, combined with her expertise in tools such as Omega2, Reveal, and GeoTomo, which makes her a leading voice in the domain.

One of her notable achievements was processing low signal, complex 2D land data from Papua New Guinea’s Eastern and Western fold belts. Through optimal processing application, she yielded structurally correct images that were pivotal for interpretation and drilling decisions. This breakthrough was shared at a workshop in Melbourne, Australia, leading to standardizing processing quality control across the industry.

Nevaskar’s leadership skills are further highlighted by her role in leading a 20-person team, overseeing everything from procurement to price negotiation and quality control of significant vendor work. Her emphasis on continuous learning and innovation is evident in her efforts to mentor geo-tech personnel, championing new technologies and processing modules.

She shares, “This journey is a learning experience. A best practice is not gained overnight but through a series of ups and downs, successes and failures, which I had a fair share.”

Addressing Uncertainties with Trust 

Nevaskar acknowledges that becoming overly reliant on data analytics can also pose a danger if not handled properly. However, she mentions that in today’s digital world, reliance on data is not an option but a must to adapt and keep up.

“Data becomes more complex, and we, data scientists, should learn how to evolve. That is why we have shared these best practices. It is our way of learning from one another so that all can be better and grow,” Nevaskar shares.

Her journey from the intricate world of geoscience to the dynamic realm of data science is not just a transition but a reflection of the broader evolution of an industry. As the seismic industry continues its journey into uncharted territories, the role of experts like Nevaskar proves vital in advancing the industry with these best practices.

The Data Scientist mentions, “In the end, it’s about trust. Trust in the data, the processes, and the people behind them, and you will see good results.”