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Sediment Bearing Pressure Analysis using Sediment Classification Techniques in Indian Ocean Region

By: Romit Rajendra Kaware

The Indian Ocean is the world’s third-biggest body of water, with key maritime routes crisscrossing it and feeding Asia’s most significant economies. The Indian Ocean holds 16.8% of the world’s proven oil reserves and 27.9% of the world’s proven natural gas reserves. Moreover, it is home to major sea routes connecting the Middle East, Africa and East Asia with Europe and the Americas. Today, the Indian Ocean Region (IOR) is experiencing unprecedented strategic challenges, with changes in political thought processes and relations altering the region’s security scenario. The region’s marine troops and capabilities have expanded gradually to an accelerated level.

“The increasing presence of extra-regional powers and nuclear-capable states has shifted the security framework even more. Safe navigation is an essential aspect of trade and movement perspectives.”

Features on the seabed that may pose a threat to navigation, whether natural or artificial, must be detected to guarantee safe navigation. This can be done using seafloor classification, one of the main aspects being sediment classification. The sediment classification techniques help determine sediment grain size, sediment topography, and the various properties related to them. Until a few decades ago, physical samples were drilled out from the coastal waters and laboratory tested to find the composition, grain size distribution, and type of the particles in the sediment layers. This technique, however, is restricted by scale, is tedious and requires high capital.

 

Seafloor classification using acoustic remote sensing techniques, which involves using different sonars, is the main attraction nowadays due to their high coverage and limited costs. These techniques rely on the emission and capture of sound wave signals, which get distorted while propagating the various layers of sediment, marine wildlife, rocks etc. A mathematical model is equipped to interpret these distortions, which are compared with existing data from physical samples to closely match the sediment type present. All the information collected is required for proper navigation and numerous other aspects ranging from defence to biology, from construction to resource extraction etc.

 

Developing the acoustic remote sensing techniques for sediment classification has proven to be a game-changer in understanding the seabed. With acoustic systems like sonars carried by ships, submarines or AUVs, it is possible to map a large portion of seabed in a relatively short time,  consuming fewer resources than conventional physical methods. With the development of new efficient algorithms for processing the signal data, the resources and time needed is further reduced.

“The advances in the techniques used for sediment classification have led to a more comprehensive and less tedious description of the sediment topography. Even with various models and algorithms, one can’t just take up a well-established model for any region. “

There are challenges in choosing a particular technique or model for the survey. The models are based on optimising the mathematical results obtained from the model and the experimental data. The solution of the model involves solving equations which may differ from model to model, thus affecting the complexity of the model. Based on the complexity of the mathematical model, high computational resources and capital might be needed, leading to the inefficiency of the model. Moreover, there is a restriction to the model’s applicability, generally, a model would be applied in a particular region only, and application to other areas would require significant changes in the model.

 

Different oceans have different characteristics, varying in depth, temperature, topography, circulation, etc., varying with depth, temperature, topography, circulation etc., which need to be considered while deducing a suitable model. The Indian Ocean Region (IOR) pose some significant challenges. Its warm temperature renders it vulnerable to climatic fluctuations like monsoons, tsunamis, cyclones, and high winds. Moreover, the tropical littoral waters of the IOR  lead to sub-optimal performance of any kind of sonar, hampering the performance. Additionally, the rich biodiversity in the seas of IOR leads to multiple reflections of the emitted signal causing a complex signal packet at the receiver’s end. Such challenges must be tackled while solving the model to get relevant results.

“Acoustic sediment classification is crucial in a variety of domains. When the acoustic signals strike the surface of an object, the signal gets reflected, transmitted and absorbed by the media, with each media having different characteristics. “

The received signal can then determine the feature presentation at the location. This has a variety of practical applications.

 

Underwater Communication: Since sound is the medium of communication underwater, the acoustic classification technique can be used to determine the speed of sound at various locations and depths, proving to be very critical for underwater communication in submarines; Autonomous Underwater Vehicle(AUV), ships etc.

Mine Hunting: Acoustic signals can detect minerals like nickel, copper, manganese and even gold deep beneath the seafloor. Extraction of such minerals present in the Exclusive Economic Zone of a nation would enhance the nation’s industry, trade and economy.

Underwater Cable Routes: The ocean floor topography can be estimated using remote sensing acoustic techniques, helping in the route planning of the underwater communication cables, crucial for inter-continental data transfer.

Ecosystem Classification: Acoustic techniques are used for marine biological resource mapping and ecosystem management. Different species lead to various signal distortions that can be used to classify ecologically sensitive areas and marine wildlife monitoring.

Sediment Bearing Pressure: Estimating the sediment-bearing pressure, strength, and stability of the sediment layers is essential for offshore construction and exploration activities of offshore structures.

Sediment-bearing pressure estimation at the seafloor is one of the crucial applications of the Acoustic Seafloor Classification. The Indian Ocean Region consists of huge petroleum and Natural gas reserves and other valuable minerals like copper, manganese, nickel and gold. The exploration and extraction activities require the construction of offshore facilities like drilling rigs, tanks, and refineries, which are supported by foundations reaching the seabed. Sediment-bearing pressure comes into play in the proper site selection and the design of foundations and piles, which are the support structures of offshore facilities. The bearing pressure is also critical from a defence point of view for developing artificial islands, military equipment transportation and other related infrastructure. The results from the sediment classification techniques could be used to determine the parameters which are required for the sediment-bearing pressure estimation.

“Sediment classification using acoustic remote sensing techniques has led to more understanding of the seafloor than ever before. With new developments, along with the development of AUVs, it is sure that humans will get to know more about the hidden world present several thousand meters below the water surface. “

Thus, enabling us to explore and understand the lifeforms present and find answers that were left to the imagination. With the growing ambitions of the nations around the IOR, the sediment classification techniques are a significant boost for securing the nation’s defence, the continuation of international trade, marine wildlife research and leading to sustainable development.

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About The Author

Romit Rajendra Kaware

Romit Rajendra Kaware is a final year student pursuing B.Tech in Civil Engineering from IIT Delhi. He is currently a research intern at the Maritime Research Centre (MRC), his previous research includes Molecular Dynamic simulation on the silica-graphene interface.