Estimation of porosity and gas hydrate saturation by inverting 2D seismic data using very fast simulated Annealing in the Krishna Godavari offshore basin, India

Abstract

Gas hydrate saturation and porosity are the two essential parameters for characterizing a gas hydrate reservoir. Generally, porosities determined at the well locations are interpolated and extrapolated over the seismic volume, which is not so appropriate to get an estimate of gas hydrate saturation. Here, we propose a method to predict both porosity and gas hydrate saturation directly by inverting seismic data using a global optimization technique known as Very Fast Simulated Annealing. Acoustic impedance, as a function of water saturation and porosity, is defined by a second‐degree polynomial equation used as a forward problem. These are used as the primary model parameters. Acoustic impedance derived from these values is then used to compute synthetic seismograms that are compared against observed traces. We demonstrate our approach on a 23.5 km two‐dimensional seismic line crossing four wells in the Krishna Godavari Basin, eastern Indian offshore. First, the proposed method is tested on well log data and then applied on post‐stack seismic data. The posterior probability density function and the correlation matrix between the model parameters (gas hydrate saturation and porosity) are calculated to measure the associated uncertainty in prediction. Inversion results illustrate that the approach can be efficiently used for the prediction of porosity and gas hydrate saturation directly from the seismic data.

Estimating elastic properties of sediments by pseudo-wells generation utilizing simulated annealing optimization method

“…They applied Long Short-Term Memory networks (LSTMs) to maximize the value of gamma rays (Huang and Trad, 2023;Kianoush et al, 2023c;Sun et al, 2023). Joshi and Ojha (2022) propose a technique to directly predict gas hydrate saturation and porosity by inverting seismic data employing a global optimization approach called very fast simulated annealing (VFSA). AI, as a process of porosity and water saturation, is specified by a second-degree polynomial formula utilized as a forward model (Babasafari et al, 2021;Guo et al, 2020;Hosseini et al, 2023c;Hosseini et al, 2023a;Hosseini et al, 2023b;Kianoush et al, 2022b).…”