Advancements in 4D Seismic Monitoring for Carbon Storage

The Sleipner project in the North Sea is the world's first commercial project focused on storing carbon dioxide (CO2) to help reduce emissions. Since 1996, over 19 million tonnes of CO2 from gas production have been injected into a specific underground layer. To ensure this process is safe and effective, the site is closely monitored with regular seismic surveys-basically taking "pictures" of the ground using sound waves.

#What is 4D Seismic Inversion?

4D seismic inversion is a technique used to track fluid movement underground over time. It provides important information for various applications, including oil recovery and CO2 storage. However, analyzing seismic data can be quite tricky because of noise and inconsistencies in the data collected at different times. To create accurate models of the subsurface, it's essential to add helpful information into the analysis process.

#The Role of Seismic Data

Seismic surveys send sound waves into the ground and measure how they bounce back. By analyzing these waves, researchers can infer what types of materials and fluids are present underground. Over the years, seismic methods have been improved, but they still face challenges due to the limited frequency of sound waves and the noise that can obscure the results.

#The Proposed Method

To tackle these challenges, a new combined approach called joint inversion-segmentation (JIS) was developed. This method works to improve the results of 4D seismic data analysis by integrating various types of information to provide clearer and more detailed models of the underground environment. In practical terms, this means that JIS can help identify changes in the subsurface more accurately than older methods.

Using the Sleipner dataset, which includes multiple seismic surveys over several years, JIS can analyze these surveys together to reduce noise and highlight significant changes that happen over time. The results show that this method can create high-resolution models, revealing not just where the CO2 is but also how it affects the surrounding rock layers.

#The Importance of Accurate Monitoring

Accurately monitoring the movement of CO2 is crucial for the success of carbon storage projects. If CO2 were to escape or cause geological issues, it would defeat the purpose of the storage effort. By employing advanced techniques like JIS, researchers can ensure that the injected CO2 behaves as expected and remains safely trapped underground.

#How the Method Works

The JIS technique begins with the creation of models based on initial data, which are then refined through the process. This involves correcting for differences in the data collected during the surveys and aligning them in a meaningful way. By applying regularization terms-mathematical tools to guide the analysis-the JIS approach can better filter out noise and improve the clarity of the results.

The output of JIS provides a clear picture of how the CO2 plume expands and interacts with the surrounding environment. This helps in identifying potential risks and confirming that the process is working correctly.

#Benefits of Joint Inversion-Segmentation

1. High-Resolution Models: JIS can create very detailed Acoustic Models of the subsurface, allowing for better insight into the geological features and fluid movements.

2. Noise Reduction: By using data from multiple surveys together, JIS can reduce the impact of unclear data and highlight genuine changes that occur over time.

3. Segmentation for Analysis: The method also allows researchers to classify areas based on how the acoustic properties changed, making it easier to interpret the results.

#The Sleipner Dataset

The Sleipner dataset consists of seismic data collected over several years, allowing researchers to track changes in the subsurface continuously. The surveys cover a large area and provide a comprehensive view of the changes resulting from CO2 injection. By focusing on two specific surveys-one from 1994 and another from 2001-researchers were able to apply the new JIS method and observe significant results.

#Well-to-Seismic Tie

To ensure the seismic data aligns with actual conditions in the field, researchers use well logs-measurements taken directly from drilling sites. By correlating this data with the seismic surveys, they can create a time-depth relationship, making it easier to interpret the seismic data accurately.

#Correcting Time Mismatches

Between the initial and later surveys, time shifts can occur-these are differences in time for seismic waves to travel due to changes in the underground conditions. The JIS approach corrects these time shifts, allowing for a clearer comparison between the two surveys.

#Efficient Computation

Handling large datasets can be challenging. The JIS method takes advantage of modern computing power, especially GPUs (graphics processing units), which can process information faster and more efficiently than traditional CPUs. This enables the analysis of complex data to occur at a much quicker pace.

#Results and Insights

The application of the JIS method to the Sleipner dataset showed several advantages. The acoustic impedance models created were not only more detailed but also demonstrated significantly less noise than traditional methods. This makes it easier for researchers to identify how the carbon dioxide plume evolves over time.

#Conclusion

The joint inversion-segmentation method is an effective approach for 4D seismic inversion, especially in monitoring carbon storage projects like Sleipner. By improving the resolution and clarity of the data, JIS contributes to safer and more effective CO2 storage practices. This ultimately supports efforts to reduce greenhouse gas emissions and combat climate change.

By integrating advanced computational techniques and thorough data analysis, researchers can provide more reliable assessments of underground fluid dynamics, ensuring the safety and success of such environmental initiatives.