--> Improved Prediction of Sedimentation Rates and Burial History using Storm Software

2018 AAPG International Conference and Exhibition

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Improved Prediction of Sedimentation Rates and Burial History using Storm Software

Abstract

Sediment accumulation and erosion are important elements of the burial history and development of sedimentary basins. Input data to burial history models (deposit and erosion thicknesses, rock properties) are often uncertain or even unavailable due to high costs and technical difficulties. Standard backstripping methods and decompaction equations result in deterministic burial history models that do not take into account the uncertainties related to input data, nor the limitations of the methods. When using these models, the input is commonly based on assumptions and values deemed likely by the user, making the models inherently biased towards the user’s perspective. In addition, the input values are usually set without analysis of parameter interrelations that should make geological sense. All of the uncertainties and limitations might consequently lead to incorrect models and it is therefore important to revisit the present-day approach in a way that includes the burial history uncertainties. We propose an approach StoRM that quantifies burial history input uncertainties by linking stochastic theory and sedimentation modelling. This process can eliminate a large part of the unlikely values from the uncertainty ranges and predict the most likely parameter values. Moreover, the approach checks consistency in input values to ensure that the combination of the values makes geological sense. Constrained input values are used to build probabilistic burial history and sedimentation curves that can be used further for modelling of: organic content, palaeo-environments, early diagenetic processes, overpressure, and temperatures. We will present an example where the method was applied using data from the Norwegian Barents Sea. We will focus on the Mesozoic-Cenozoic burial history that was affected by active tectonism which resulted in a complex sedimentation history and several erosion episodes. Further, it will be demonstrated how the modelled sedimentation rates can be used for prediction of TOC, and method verification examples will be given.