Reservoir characterisation using hybrid optimisation of genetic algorithm and pattern search to estimate porosity and impedance volume from post-stack seismic data: A case study

Abstract

In the current study, a seismic inversion based on a hybrid optimisation of genetic algorithm (GA) and pattern search (PS) is carried out. The GA is an approach to global optimisation technique that always converges to the global optimum solution but takes much time to converge. On the other hand, the PS is a local optimisation technique and can converge at local or global optimum solution depending on the starting model. If these two techniques are used together (here termed hybrid optimisation), they can enhance one's benefit and reduce the drawbacks of others. The present study developed a methodology to combine GA and PS in a single flowchart and utilise seismic reflection data exclusively to predict porosity and impedance volume in inter-well regions. The algorithms are initially tested on synthetically created data based on the wedge model, the coal coking model, and the 1D convolution model. The performance of the algorithm is remarkably acceptable, according to the error analysis and statistical analysis between the inverted and the anticipated results. After that, the field post-stack seismic data from the Blackfoot field, Canada, is transformed into impedance and porosity using a developed hybrid optimisation technique. The inverted/predicted sections show very high-resolution subsurface information with impedance varying from 6000 to 14000 m/s×g/cc and porosity varying from 5 to 40% in the region. The error decreases from 1.0 to 0.5 for impedance inversion, whereas it varies from 1.4 to 0.5 for porosity inversion within 3000 iterations, which cannot be achieved by a single optimisation technique. The findings also demonstrated a sand channel (reservoir) anomaly with low impedance (6000–9000 m/s×g/cc) and high porosity (12–20%) in between 1040 and 1060 ms time intervals. This study provides evidence that subsurface parameters like acoustic impedance or porosity may be promptly and affordably determined using seismic inversion based on hybrid optimisation. The developed methodology is very helpful in finding subsurface parameters in a limited time and cost, which cannot be achieved only by global or local optimisation.