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Improving Seismic Imaging by Reducing Surface Waves

A new method enhances seismic imaging by reducing noisy surface waves.

Faezeh Shirmohammadi, Deyan Draganov, Ranajit Ghose, Eric Verschuur, Kees Wapenaar

― 6 min read


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Seismic imaging is like trying to see what’s underneath the ground from the surface. It’s super helpful for things like finding oil, monitoring earthquakes, and figuring out what’s going on below our feet. However, there’s a big problem. Surface Waves, which are like noisy party crashers, often drown out the important signals we want to hear. These surface waves can mimic the sounds of the reflections we actually want to capture. As a result, it’s tough to get a clear picture of what’s happening below.

The Plan: Silencing the Noisy Neighbors

We have come up with a nifty two-step plan to reduce these pesky surface waves. First, we turn our receivers into virtual sources using a method called seismic interferometry. This helps us figure out what the surface waves sound like. Then, we subtract these estimated waves from our data to clear up the reflections we want to see. We even add a twist: we use the results we just got as the starting point for another round of this process. So, think of it like a video game where you level up-each round you play gets you closer to the ultimate goal.

The Playground: Where We Tested Our Idea

We tested our approach on a 2D seismic reflection dataset from Scheemda, located in the Groningen province of the Netherlands. By comparing what we did with the original data, we could see just how well our fancy trick worked. Spoiler alert: we found a way to significantly reduce the surface waves, making it much easier to see the reflections and understand what lies below.

The Noise Problem

Seismic surveys are often plagued by surface waves, which can be annoying. These waves travel through the ground and produce noise that can clutter our data, hiding the reflections that are crucial for making images of what’s beneath. It's like trying to hear your favorite song at a concert where someone is singing off-key right next to you.

Traditional Solutions: The Old School Ways

In the past, people used a few traditional methods to deal with surface waves. They might use filters that focus on certain frequencies, but these can sometimes miss the mark. Imagine using a strainer to catch big lumps but letting the small stuff fall through. Not ideal! When surface waves get scattered, it becomes even trickier to remove them.

Enter Seismic Interferometry

Now, here comes seismic interferometry, or SI for short. It’s a technical name for a clever trick. This method helps retrieve surface wave data by crossing signals from different sources. Think of it like eavesdropping on a conversation to pick up on the main topics being discussed. We can then use this information to subtract the surface waves from our original recordings.

Recursive Interferometric Surface-Wave Suppression (RISS)

We’ve put a twist on SI with our method, which we call Recursive Interferometric Surface-Wave Suppression, or RISS. Sounds fancy, right? But really, it just means we apply our process a couple of times to keep refining the data. Each iteration helps us get closer to the clean reflections we want. Picture it like peeling an onion; each layer you remove brings clarity to what’s inside.

Our Field Study in Scheemda

In our quest to rid the seismic data of surface waves, we headed to Scheemda. In 2022, we set up our equipment, which included a vibrator as the source and geophones to record the data. We made sure everything was in the right spot to capture the seismic waves efficiently. Think of it like setting up a perfect stage for a concert to ensure everyone can hear the music being played.

The Seismic Process: Step by Step

  1. Collecting Data: First, we collected the seismic data using our vibrator as the source. The geophones acted like ears, listening for any waves that traveled through the ground.

  2. Retrieving Surface Waves: We applied seismic interferometry to find out where the surface waves were hiding in our recordings. It’s like pulling back the curtain to see what’s making all that noise.

  3. Subtracting Surface Waves: After identifying the surface waves, we adaptively subtracted them from our original recordings. This step is crucial because it allows us to silence the noisy surface waves while keeping the important reflections intact.

  4. Iterating the Process: Instead of stopping after one round of subtraction, we repeated the process using the cleaned data as a new starting point. This is where the recursive part comes in, allowing us to refine the results even further.

  5. Final Adjustments: After applying our technique, we made some final adjustments to enhance the clarity of the reflections for better interpretation.

The Results: What We Found

After applying RISS to our data from Scheemda, we were thrilled with the results. The surface waves were suppressed significantly, resulting in clearer images of the subsurface structures. It’s a bit like cleaning the windows of a house; suddenly, everything outside becomes a lot easier to see.

How Does RISS Stack Up Against Other Methods?

To see how our method compared, we looked at traditional techniques like surgical muting and f-k filtering. While surgical muting can be helpful, it often fails to remove surface waves completely. F-k filtering can also cause issues, as it’s tricky to set the right parameters for frequency ranges. Our RISS approach stood out as being purely Data-driven, which means it adapts to the data without needing guesswork.

Conclusion: The Future of Seismic Imaging

In the end, our Recursive Interferometric Surface-Wave Suppression technique turned out to be a very effective way to enhance seismic imaging. By using data-driven methods, we not only improve the quality of seismic reflections but also make the process more efficient.

So next time you hear about seismic imaging, remember: we’re not just making noise-we're making waves, quietly!

Acknowledgements

We thank the funding agencies that made this research possible and our tech partners who provided the necessary equipment. Also, a shout-out to the people of Groningen for letting us set up our seismic playground in their backyards!

Data Availability

If you're curious and want to check out the data we used or the codes we developed, they are available online for anyone interested in diving deeper into the world of seismic imaging. Just look for the 4TU.ResearchData repository, and you’ll find our work waiting for you!


This article explored the world of seismic imaging and the innovative methods developed to enhance the clarity of subsurface reflections by tackling the challenge posed by surface waves. With our Recursive Interferometric Surface-Wave Suppression method, we hope to pave the way for clearer and more effective seismic imaging in the future, making underground mysteries a little less mysterious. It's been a seismic adventure, and the journey is only just beginning!

Original Source

Title: Recursive Interferometric Surface-wave Suppression For Improved Reflection Imaging

Abstract: High-resolution seismic reflections are essential for imaging and monitoring applications. In seismic land surveys using sources and receivers at the surface, surface waves often dominate, masking the reflections. In this study, we demonstrate the efficacy of a two-step procedure to suppress surface waves in an active-source reflection seismic dataset. First, we apply seismic interferometry (SI) by cross-correlation, turning receivers into virtual sources to estimate the dominant surface waves. Then, we perform adaptive subtraction to minimise the difference between the surface waves in the original data and the result of SI. We propose a new approach where the initial suppression results are used for further iterations, followed by adaptive subtraction. This technique aims to enhance the efficacy of data-driven surface-wave suppression through an iterative process. We use a 2D seismic reflection dataset from Scheemda, situated in the Groningen province of the Netherlands, to illustrate the technique's efficiency. A comparison between the data after recursive interferometric surface-wave suppression and the original data across time and frequency-wavenumber domains shows significant suppression of the surface waves, enhancing visualization of the reflections for following subsurface imaging and monitoring studies.

Authors: Faezeh Shirmohammadi, Deyan Draganov, Ranajit Ghose, Eric Verschuur, Kees Wapenaar

Last Update: 2024-11-04 00:00:00

Language: English

Source URL: https://arxiv.org/abs/2411.02620

Source PDF: https://arxiv.org/pdf/2411.02620

Licence: https://creativecommons.org/licenses/by/4.0/

Changes: This summary was created with assistance from AI and may have inaccuracies. For accurate information, please refer to the original source documents linked here.

Thank you to arxiv for use of its open access interoperability.

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