[Editor's Note: Mrigya Fogat is a member of the TWA Editorial Board and is the author of previous TWA articles.]
Mrigya Fogat (MF): Hi, everyone. I am Mrigya, editor in chief for The Way Ahead for SPE, and today we're back with another interview.
We have with us Sushma Bhan, technical director of the SPE Data Science and Engineering Analytics Technical Section. She also champions SPE's Global AI for Energy Initiative. Previously, she spent more than 30 years at Shell, where she served as chief data officer for subsurface and wells. She developed enterprise-wide data strategies and led global digital initiative accelerators. Throughout her career at Shell, she held several leadership positions in data, AI, and digitalization, delivering multimillion-dollar savings across 20 countries and numerous Shell assets.
She currently serves on the board of Rice University's Master of Science program and previously served on the board of Ikon Science. Her leadership earned her one of the industry's most prestigious honors: recognition as a 2024 Hart Energy Influential Woman in Energy.
We're really happy to have her here with us today. Welcome, Sushma.
Sushma Bhan (SB): Thank you, Mrigya. It's really a delight to meet you and have this opportunity.
MF: Sushma, you've had such an incredible journey. It's a unique combination of data, energy, AI, and digital transformation. From what I've read, your career has focused on data, IT, analytics, and you eventually became chief data officer for subsurface and wells at Shell. Looking back, what were some of the most important career decisions that shaped your journey?
SB: Thirty years at Shell and now serving as an SPE technical director have given me many opportunities. Looking back, the first thing I would say is that I invested very early in building strong technical acumen in data, IT, computing, and analytics. That foundation helped me understand not just the tools, but how they behave, how they fail, and ultimately how they enable business value.
I had opportunities to work across production, exploration, and even downstream chemicals. That broad exposure gave me a deep understanding of how technology supports business outcomes.
The second deliberate choice I made was learning the subsurface value chain end to end, from discovery and drilling to development, production, decommissioning, safety, and security. I wanted to understand geoscience, reservoirs, and wells in depth. That gave me a much clearer view of how data influences production, reserves, and ultimately, the bottom line.
The third lesson came later in my career: becoming someone who could bridge technology and business. It's not enough to understand systems and technology. You need to translate complex data topics into simple, decision-ready language for stakeholders.
Finally, I learned the value of tackling difficult and complex data challenges, whether they involved security, fragmentation, silos, or governance. Taking on those tough opportunities became one of the biggest accelerators in my career.
MF: That's fascinating. Today everyone talks about breaking down silos and making data-driven decisions, but you've been doing that long before data and AI became buzzwords. How has the industry's perception of data changed over the past 3 decades?
SB: The biggest shift is that businesses now recognize data quality and accessibility as business issues rather than IT issues. Data has moved from being viewed as files and storage to being treated as a strategic asset. It directly impacts safety, efficiency, and value creation.
Historically, business ownership of data quality was weak. Today, with analytics and AI driving decisions, trust in data is essential. The awareness of the importance of quality data, combined with years of pain points, has created tremendous momentum for change.
I remember an asset leadership meeting in Oman where every asset leader talked about data challenges. It became clear that poor data management was a major obstacle.
Now, we see strong management support, chief data officer roles, governance frameworks, and enterprise-wide stewardship. Companies have moved from local, reactive approaches to enterprise platforms, standards, and structured ownership. Data is no longer an afterthought. It's central to optimization, foresight, automation, and business impact.
MF: Many of our readers are young professionals entering the industry and often working with mature fields that date back to the 1950s and 1960s. If you were starting on such a field today, what would your roadmap be for transforming it into a digitally ready asset?
SB: I would start with data management standardization. Without trusted and structured data, neither digital workflows nor AI models can scale.
First, identify the key business processes and the critical data they generate, including logs, PVT data, well tests, seismic information, completions, and production events. Ensure the data is stored with quality controls, governance, and reliability.
Second, make multidisciplinary teams accountable for data quality. Data ownership cannot sit solely with IT or data managers. Geoscientists, engineers, and asset teams need to own the data they create and use.
Third, establish clear discipline ownership. Geological, geophysical, and reservoir engineering disciplines should define how their data is stored, managed, validated, and measured.
Once those foundations exist, you can standardize legacy data, harmonize naming conventions, resolve duplicates, and build trusted records for wells and reservoirs. Ultimately, the goal is to make data a living asset that is available, managed, and ready to support business decisions across the entire value chain.
MF: As people embrace AI-driven predictions and decision-making tools, there is often discussion about physics-based models versus AI-based models. Have you seen situations where AI uncovered insights that traditional physics-based approaches could not?
SB: I would not frame it as physics versus AI. The future is physics plus AI.
Physics-based models give us understanding, trust, constraints, and decades of scientific knowledge. AI provides speed, pattern recognition, and the ability to learn from very large datasets and high-frequency operational data. Together, they create a powerful combination.
For example, advanced analytics applied to mature assets can identify production performance issues and improve predictive capabilities in ways that were more difficult in the past. However, trusted operational decisions still rely on combining AI insights with physical understanding. The most effective future solutions will leverage both.
MF: Looking across the upstream industry, which technologies have had, or will have, the most impact on the way we work?
SB: Real-time surveillance and digital twins stand out.
When I first joined Shell, operators physically walked fields to inspect equipment. Over time we introduced SCADA systems, and today we can monitor wells, reservoirs, and facilities in real time through digital representations of assets. This capability improves safety, reduces risk, and enables faster decision-making.
Data visualization and analytics have also had a major impact. Bringing together live, historical, and static data into a visual environment allows engineers, technical teams, and leadership to identify patterns and make better decisions.
More recently, agentic AI is emerging as a transformative technology. While not yet fully mature, the ability for AI agents to gather information, evaluate models, interpret reports, and assist in decision-making has tremendous potential.
The true power will come from combining trusted data, digital twins, advanced analytics, and humans in the loop. Subject matter experts remain essential because they provide context, judgment, and accountability.
MF: That leads perfectly into my next question. Technology transformation is just as much about people as it is about technology. You've held many leadership positions. How did you drive organizational change and help people adopt new technologies and processes?
SB: That is a very important question because transformation ultimately depends on people.
Over my career, I have seen many waves of technological change, from desktop tools and cloud technologies to today's AI revolution. The biggest lesson is that success depends on bringing people along on the journey. You need to create awareness and understanding of the value technology delivers. People naturally have concerns about change and may worry about issues such as job displacement.
The key is to focus on business outcomes rather than the technology itself. When people see improvements in safety, efficiency, speed, or cost savings, they become much more receptive to change. It's also important to involve end users and key stakeholders early. Building trust, maintaining transparency about risks and benefits, and creating clear governance and accountability structures all contribute to successful adoption and organizational transformation.
MF: I see that your career has been a combination of many technical roles. You mentioned earlier that you made a conscious decision early in your career to build a strong grasp of technical concepts, even beyond traditional IT and data disciplines. Later, you moved into a number of leadership roles.
Many young professionals find themselves at a crossroads between continuing down a technical path and building deep expertise versus pursuing leadership opportunities. How did you make that decision? Was there a period when you were balancing both before fully transitioning into leadership roles?
SB: That's a very good question because I see many young professionals and students with aspirations of quickly moving into management or leadership positions.
The first and most important thing is building technical depth. That foundation is incredibly important whether you remain a technical expert or move into management. As I mentioned earlier, understanding your business, the full technical landscape, and how everything works end to end is essential.
For example, I worked extensively in the subsurface domain. Learning the systems, tools, workflows, and business processes helped me become grounded in the discipline. Whether you're coming from computing, data science, petroleum engineering, or another field, it's important to establish yourself as someone who truly understands the business.
The second point is that leadership is not about titles. It's not about becoming a manager, general manager, or vice president. Leadership is about influence. It's about bringing solutions, thinking holistically, motivating people, and creating business impact. You have to build yourself into a well-rounded professional. That includes not only technical capability but also behavioral skills, communication, and influence with both peers and business stakeholders.
It's also important to seek opportunities where you can lead as an expert. Those opportunities may arise through volunteer work, challenging projects, or difficult business problems. Taking on those challenges allows you to demonstrate your technical expertise, project management capabilities, and ability to drive change.
As an immigrant from India who joined Shell in my twenties, communication was a major learning area for me. I had to learn how to communicate effectively with technical colleagues while also developing strong business acumen. Alongside technical training, I pursued leadership development and executive MBA studies. Learning to speak the language of business, understanding different cultures and environments, and working globally were all essential parts of my development. Communication is especially important. You must be able to translate technical ideas into terms that business stakeholders can understand. That ability will serve you at every stage of your career.
Another important lesson is to remain a continuous learner. The world changes constantly. Technology evolves, industries evolve, and geopolitical dynamics shift. You need to stay curious, adapt, and continue learning.
Over time I realized that technical skills and leadership skills are not mutually exclusive. In fact, both are necessary. My approach became maintaining technical awareness while continuously strengthening my business acumen so I could have a greater impact.
Build a strong technical foundation, stay curious, keep learning, and take advantage of opportunities to broaden your skills. Organizations like SPE are also excellent platforms for developing yourself while building your career.
MF: I'd like to narrow the focus to women in our profession. You've received the Hart Energy Influential Women in Energy Award and held numerous leadership positions throughout your career. What advice would you give to young women who are building their careers and climbing the corporate ladder?
SB: The first thing I would say is to build confidence and pursue stretch opportunities.
When people talk about confidence, they often leave it undefined. Years ago, while attending an IBM course in Austin, a senior colleague gave me advice that has stayed with me ever since. He told me that confidence comes from competence. Build your knowledge. Build your skills. Develop expertise in your field. Whether you're working in downstream, upstream, data science, engineering, or any other area, understand it deeply.
When you have the knowledge, preparation, and understanding, you naturally enter meetings and projects with confidence because you've done the work required to be successful. Confidence isn't a magical trait. It's built through learning, preparation, understanding your role, communicating effectively, and consistently showing up prepared.
I would also encourage young women to build expertise and establish credibility. You don't need to know everything, but you should strive to understand your domain and perform your role exceptionally well. Credibility comes from being reliable, trustworthy, and consistently delivering quality work.
Another important recommendation is to seek mentors. There are many experienced professionals willing to share knowledge and guidance. Don't limit yourself to mentors who look like you or share the same background. Throughout my career, I learned from many different people whose skills and experiences complemented my own. Find people who can provide honest feedback, challenge you, and help shape your career.
Networking is equally important. Organizations like SPE offer incredible opportunities to connect with professionals, build leadership capabilities, and expand your understanding of the industry beyond your immediate workplace.
I would also encourage young professionals to take calculated risks. Sometimes we become comfortable with what we already know. Growth often comes from stepping into unfamiliar situations, whether that's a volunteer role, a new project, or a leadership opportunity.
Support other women and colleagues as well. Success isn't only about your own achievements. It's about helping others succeed too.
Think strategically. Understand your company's mission and goals. Look beyond your immediate tasks and understand the bigger picture. Ask yourself how your work contributes to the organization's success.
Be authentic. Bring your unique perspective. Always act ethically and stand for what is right.
And perhaps most importantly, believe in yourself. If you don't believe in yourself, it's very difficult for others to do so.
MF: Many women reach a stage in their careers where they are balancing professional growth alongside family responsibilities and commitments outside of work. What advice would you give for managing that balance? And how do you handle situations where taking on visible opportunities might be perceived negatively?
SB: This is a very important topic.
The first thing is understanding the fundamentals of your role and delivering on your responsibilities. But when it comes to balancing work and life, I've always believed in integrating personal and professional commitments rather than treating them as completely separate worlds.
Plan proactively. If you have important family commitments, put them on your calendar. If you have obligations involving your children, elderly parents, or other priorities, communicate openly and transparently with your manager and colleagues. Good planning and preparation go a long way.
At the same time, maintain a strong delivery mindset. You have responsibilities at work, and it's important to fulfill them. That may mean being selective about additional commitments and avoiding overextension. Take on what you can realistically deliver and do it well.
Throughout my career I was involved in many activities, including leadership roles within Shell's Women's Network. Managing those commitments required careful planning and a supportive family environment. Having a strong support system matters. Trusted colleagues, managers, family members, and friends can all play a role. There is no perfect balance. The key is being thoughtful about your commitments, prioritizing effectively, communicating clearly, and making sure you're honoring the responsibilities you've chosen to take on.
Planning, foresight, openness, and communication are essential.
MF: For young professionals interested in the intersection of reservoir engineering, geoscience, production, data, and AI, what advice would you give them? From both a technical and soft-skills perspective, how can they differentiate themselves and stand out?
SB: First, understand what you're trying to achieve. Regardless of your role, having the end goal in mind is critical.
Technology and business environments are changing rapidly. Successful professionals are open-minded, adaptable, and willing to learn. What differentiates people is not simply collecting credentials or certifications. The real question is how you apply those skills and what value you create. You need to translate knowledge into business impact. When you attend a conference, complete a certification, or learn a new skill, think about how you can apply those insights to generate value for your organization and colleagues. Be purposeful.
With AI, robotics, automation, and other emerging technologies becoming increasingly important, I strongly encourage professionals to embrace these changes. AI is here to stay. Develop fluency in it. Understand how it works and how it can create value. At the same time, maintain strong core technical expertise in your discipline while thinking across disciplines. Look for the connections between different domains and understand how they work together.
Another important differentiator is adopting a solution-oriented mindset. Many people identify problems. Fewer people come forward with potential solutions. Even if your solution isn't perfect, come prepared with ideas. Engage your mentors and senior colleagues in discussions about how challenges might be addressed. People notice those who contribute solutions rather than simply highlighting issues.
Finally, communication remains one of the most important skills you can develop. You must be able to take complex technical concepts and explain them clearly to peers, leaders, and business stakeholders. Technical expertise alone isn't enough if you can't communicate its value and impact.
Learn from role models. Stay adaptable. Don't be afraid of failure. Failure provides valuable lessons and helps build resilience. Focus on achieving small successes and building momentum. Large goals become much more manageable when broken into smaller accomplishments. And never hesitate to seek guidance from the many experts and mentors who are willing to help.
MF: Thank you, Sushma. That brings us to the end of the interview.
If I had to summarize my biggest takeaways, they would be: be excellent at what you do, communicate effectively, and focus on business outcomes and results.
Thank you for sharing so many valuable insights and lessons from your career.
SB: Absolutely. Thank you so much for the opportunity. I really appreciate your volunteer spirit and the effort you've put into conducting this interview.
I hope these insights help young professionals as they navigate their own careers. Thank you again, and all the best.