Seismic Horizon Interpretation

The next step after the data has been loaded correctly and the well ties with the well tops correctly identifying your horizons of interest, we have the step of Horizon Interpretation.

Horizon Interpretation: Time or Depth Interpretation

In seismic interpretation, the process of understanding subsurface structures from seismic data involves the critical step of horizon interpretation, either in Time of Depth, which ever you want just stay consistent. This refers to identifying distinctive boundaries or reflections within the data, often indicative of geological formations.

Manual Interpretation:

In seismic interpretation of both 2D and 3D data, the process usually involves both automated and manual picking to achieve a greater understanding of subsurface structures. Following the initial application of automatic horizon picking usually on the easier surfaces, such as the water bottom or mid-Oligocene picks where the software package is quite good at maintaining accuracy, the manual interpretation phase takes center stage. During this phase, interpreters review and refine the auto-picked horizons, ensuring that they precisely capture the intricate geological features present in the seismic data. This manual adjustment is pivotal for achieving a high level of accuracy in the interpretation, as it allows experts to fine-tune the automated results based on their geological expertise.

This comprehensive approach ensures that the interpretation goes beyond the confines of typical patterns and encompasses the full spectrum of subsurface complexities. By integrating their geological knowledge with a detailed analysis of the seismic data, interpreters can uncover subtle geological details, fault lines, tuning effects, and other features critical to a comprehensive understanding of the subsurface.

The significance of manual interpretation lies in its ability to enhance precision, flexibility, and overall insight. Precision is achieved through the adjustments made by interpreters, aligning the interpreted horizons with geological realities, making sure the picks make sense. The flexibility of manual interpretation allows interpreters to adapt to complex geological conditions, recognizing patterns that may not conform to automated algorithms. Ultimately, the integration of both automated and manual interpretation contributes to a detailed understanding of subsurface structures, where the strengths of algorithms and human expertise combine to provide a refined and accurate interpretation of seismic data.

Auto-Tracking: Auto-tracking employs automatic algorithms to efficiently identify and track horizons, generating initial interpretations. This not only accelerates the interpretation process but also ensures consistency and accuracy in applications such as oil and gas exploration, where precise subsurface knowledge is essential for decision-making.

Quality Control:

Quality control of picks in seismic interpretation is a critical process aimed at ensuring the accuracy and reliability of identified seismic events, such as horizons or reflections. Mis-ties, indicating mistakes where picked events do not align accurately with the true geological features, and busts, representing more severe errors, some of which show up sometimes as 'bull's eyes” on resulting maps, the picks are scrutinized during this quality control effort. The process involves a combination of automated checks, where algorithms may flag potential discrepancies, and manual review by human interpreters. Interpreters, leveraging their geological knowledge, examine the picked events, comparing them with the seismic data to identify and rectify any inaccuracies. The significance of quality control lies in its ability to enhance the overall accuracy and reliability of seismic interpretations, contributing to more dependable results for subsequent analysis and decision-making. The documentation of identified mis-ties or busts is crucial for continuous improvement and maintaining a record of the interpretation process, fostering consistency and reliability in geological analysis .

Interpretation on Angle Stacks:

There are a few distinct benefits in considering both near offset and far offset stacks in horizon interpretation. The choice between near and far offsets depends on the specific goals of the interpretation and the geological features of interest. Following are some advantages of using near offset stacks (5-17 degrees) and far offset stacks (35-47 degrees). I present these as they are ones I am familiar with while interpreting.

Near Offset Stacks (5-17 degrees): In terms of high resolution, near offset stacks offer superior imaging capabilities for shallow subsurface structures. This heightened resolution proves particularly advantageous in the detection and characterization of features situated close to the surface, including but not limited to stratigraphic changes, faults, and geological variations. As well, near offset stacks exhibit a heightened sensitivity to variations in near-surface layers, rendering them invaluable for discerning subtle alterations in lithology and fluid content within shallow formations.

Near offset stacks also excel in the improved imaging of steeply dipping structures, providing a valuable tool for resolving intricate details of faulting and folding near the surface. This capability can be of particular significance in geological settings where the interpretation of such steeply inclined structures plays a crucial role. Additionally, the enhanced amplitude response associated with near offset stacks further contributes to their utility. This heightened response to changes in lithology, porosity, and fluid content makes near offset stacks advantageous for comprehensive reservoir characterization efforts.

Far Offset Stacks (35-47 degrees): Far offset stacks offer more detail into the subsurface and can often unveil information about geological structures situated at greater depths. This capability is instrumental for acquiring a comprehensive understanding of the overall geological framework and basin architecture. The insights gained from far offset stacks contribute significantly to unraveling the complexities of subsurface formations beyond the shallow layers.

The far offsets often play a pivotal role in the improved imaging and interpretation of deep-seated features, encompassing structures like basement formations, salt bodies, and expansive fault systems. This specialized focus on deep-seated geological elements enhances the overall ability to discern and characterize subsurface features that may influence geological processes and hydrocarbon reservoirs. The application of angle-dependent amplitude versus offset (AVO) analysis to far offset stacks proves valuable in gaining insights into the elastic properties of subsurface rocks. This analytical approach aids in distinguishing between various lithologies and holds particular significance in the identification of hydrocarbon-bearing reservoirs, this will be discussed in a future post. In regions characterized by salt tectonics, far offset stacks become indispensable for imaging structures beneath salt bodies, facilitating a comprehensive understanding of subsurface geometry in intricate geological settings.

Artificial Intelligence (AI):

As a previous post of mine mentions, AI has significantly reshaped the landscape of seismic interpretation, bringing about advancements that streamline and augment the analysis of subsurface structures. One of the primary applications of AI in this field is automated horizon tracking. Utilizing machine learning algorithms, AI can swiftly identify and track seismic horizons, expediting the interpretation process and enhancing efficiency.

AI's strength in pattern recognition is especially valuable in seismic interpretation. It can discern intricate patterns within seismic data, identifying subtle reflections and comprehending complex geological formations that may pose challenges for traditional algorithms or human interpreters. This capability contributes to a more nuanced understanding of subsurface structures.

AI also excels in data analysis and integration, efficiently processing vast datasets and amalgamating information from diverse sources. This dynamic approach, incorporating well logs, geological maps, and satellite imagery, enables a more comprehensive view of subsurface features, aiding in resource estimation and exploration optimization.

Predictive modeling is another domain where AI makes a significant impact. By leveraging historical data, AI systems can create models that assist in estimating subsurface properties, predicting geological features, and optimizing exploration strategies. This predictive capability is instrumental in decision-making processes related to resource exploration and extraction.

Quality control and error detection are enhanced through AI in seismic interpretation. Automated algorithms can identify anomalies, mis-ties, or busts in picked seismic events, ensuring the accuracy and reliability of interpretations. This contributes to the robustness of subsequent analyses and reduces the likelihood of errors influencing critical decisions.

AI not only contributes to data analysis but also improves imaging and visualization techniques. Through noise reduction and enhanced clarity of seismic images, as well as the generation of detailed 3D visualizations, AI aids in creating a more vivid and intuitive representation of subsurface geological formations.

In tandem with these automated capabilities, AI serves as an assistant for human interpreters. By suggesting potential horizons, highlighting areas of interest, and streamlining workflows, AI enables interpreters to focus on higher-level analysis, harnessing the dynamic between machine learning algorithms and human expertise.

The adaptive learning capacity of AI is a crucial aspect, allowing systems to continuously improve and adapt to new data. This adaptability proves valuable in handling diverse geological conditions and evolving challenges in subsurface exploration. As technology advances, the integration of AI in seismic interpretation not only accelerates processes but also refines the accuracy and depth of insights, opening new frontiers in resource discovery and geological understanding.

All seismic data software packages have horizon interpretation as a main function. It is a simple operation to get started but as stated above, meticulous detail has to be undertaken to uncover the geological details within the data. It is perhaps one of the most crucial steps to undertake in the analysis of seismic data.

In the end, no two interpreters are the same, every interpretation and interpreter are unique and have their own way of interpreting, find what works for you.

Next discussion will be on Fault Interpretation.

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