
A New Chapter: SeisWare Joins the CMG Family
We’re excited to share some big news: SeisWare is now part of Computer Modelling Group Ltd. (CMG), a global leader in energy software solutions.
Seisware is now a part of Computer Modelling Group Ltd.

In oil and gas geology, “picking tops” is the process of identifying and marking key stratigraphic boundaries or formation tops within well logs. This task is crucial for understanding the subsurface structure, as these tops define reservoir boundaries, help with correlation between wells, and guide drilling decisions. However, picking tops comes with significant challenges, particularly around naming conventions and human error, which can impact data accuracy and consistency.
Inconsistent Naming Conventions
Across different fields, companies, or even geologists, naming conventions can vary widely. One geologist may label a particular formation as “Top Sandstone,” while another calls it “Sand A.” This inconsistency makes it difficult to correlate tops across projects and creates confusion in data interpretation. Standardizing naming conventions is essential but can be challenging to enforce manually.
Subjectivity and Human Error
Tops picking is highly interpretive. Different geologists may interpret formation boundaries differently based on their experience and subjective judgment. This subjectivity can introduce errors when multiple geologists work on the same project, especially in areas where the data isn’t straightforward or where formations are thin or complex. Even skilled geologists can miss subtle details or make inconsistent picks across large datasets.
Time-Consuming Process
Manual tops picking is repetitive and time-intensive, especially for large projects with hundreds of wells. Geologists spend considerable time analyzing logs and making interpretations that, if done inconsistently, could cause delays or errors during interpretation and development.
With advances in machine learning and artificial intelligence, software can now assist geologists with predictive tops picking, offering several key benefits.
Improved Consistency
Predictive algorithms can learn from existing data and apply the same interpretation across multiple wells, ensuring that formation tops are picked consistently. This reduces human error and ensures that tops are named and correlated reliably across the dataset.
Faster Interpretation
Predictive tops picking allows geologists to quickly generate preliminary tops, which they can then review and refine. This significantly reduces the time spent on initial interpretation, allowing geologists to focus on more complex or uncertain areas rather than manually marking every well.
Enhanced Collaboration
With predictive models suggesting standardized tops names and picks, it’s easier to collaborate across teams and regions. Consistent naming and correlation make it simpler to share and interpret data, avoiding misunderstandings and misalignments in the interpretation process.
Standardize Naming Conventions
A few options exist within SeisWare to either rename tops or work with existing naming conventions.
Run Tops calculations
Set Displayed Tops
Make it Colorful
Sometimes a pop of color helps to interpret and communicate information. SeisWare users can approach this well-by-well or map a larger area.
Switch on predictive tops picking
Predictive tops picking isn’t about replacing the geologist but rather augmenting their expertise. By combining a geologist’s deep understanding of the geology with the consistency and speed of computer algorithms, predictive tops picking enables more efficient, reliable, and standardized interpretation.
In short, predictive tops picking addresses many of the traditional challenges—namely, inconsistent naming, subjectivity, and time demands—while allowing geologists to focus on the intricate, nuanced aspects of interpretation that require human insight. With predictive assistance, geologists can work more efficiently and produce more accurate subsurface models, ultimately leading to better decision-making in exploration and production.
Questions about anything in this article? Reach out to us to find out more!
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We’re excited to share some big news: SeisWare is now part of Computer Modelling Group Ltd. (CMG), a global leader in energy software solutions.

SeisWare officially rolled out version 11.0 on May 12th, marking a major software release packed with powerful new tools.

Join SeisWare at the 2025 GeoConvention. See what we have in store for this year’s conference.
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