The goal of Sediment Dynamics Research Consortium (SDRC) is to provide member companies with high precision method on the prediction of depositional system behaviour and on the modeling of detrital reservoir rock structure. To accomplish this goal, theoretical and experimental research on sedimentology, a key discipline within the realm of morphodynamics, was conducted. In addition, thorough field survey and core analysis was integrated to aid theoretical and experiment works. Field trips and seminars are held regularly to update member companies with the latest knowlege in the field of sedimentology.
The project team of SDRC performs quantitative and predictive modeling of depositional systems while incoporating theoretical, experimental, and field approaches. Both microscopic and macroscopic behaviours are considered according to fluid dynmaics and morphodynamics when modeling. Flume experiment based on the law of similarity is conducted for the verification of model created. Thorough field survey is carried out on strata that could potentially form detrital reservoir rock home to petroleum and natural gas. Field survey data integrated with seismic survey and core data forms large datasets, which are analyzed with statistical approaches to extract useful information.
The three approaches mentioned above are usually combined in actual research. Among them, SDRC especially focuses on the theoretical aspect of sedimentology research. When performing modeling of depositional systems, SDRC not only utilizes exiting programs and softwares, but also develops new programs independently and shares them with member companies and the research community. Database of new findings are actively compiled so that data cumulated can be used for future modeling.
Quantitative and deterministic prediction of the behaviour of detrital depositional system can be difficult due to its complexity. Previous studies in sedimentology tend to be emperical and usually stops at a qualitative interpretation. Models proposed sometimes lack physics background, making it overly conceptual for actual applicaiton.
We aim to find the simple rules behind the seemingly complex system and apply simplificaitons accordingly when predictve models are constructed for various purposes of application. We recognize that not only theoretical investigation is needed, but the development of a model capable of characterizing detrital reservoir rocks in nature is also of great importance. In order to develop such a model, we seek to conduct a new type of sedimentology research with emphasis on the replication and prediction of real world data, utilize both the emperical and the theoretical approach.
SDRC's subject of study include various aspects of depositional systems. However, the main focus of research in the near future will be the inverse analysis of depositional systems using deep learning neural network, which aims to establish a method for reconstructing past depositional processes for its deposits.