Optimization of seismic inversion for acoustic impedance estimation using a hybrid simulated annealing approach: A case study from F3-block, the Netherlands
摘要
The present research introduces a new methodology that combines simulated annealing (SA) and the quasi-Newton method (QNM) to enhance the prediction accuracy of impedance in the inter-well region. SA is employed to explore potential global optimum solutions with ample time and computational resources, while QNM serves as a local optimization technique focusing on refining solutions in the vicinity of the initial model. To address the limitations and leverage the strengths of both methods, the study integrates SA and QNM into a unified approach. The proposed technique involves applying a specific iteration of SA followed by QNM optimization, utilizing the initial model estimated by the former method. The effectiveness of this hybrid optimization approach is tested using synthetic data and real data from the F3-block in the Netherlands. Results indicate that the inverted impedance closely aligns with the modelled impedance under the hybrid optimization approach, outperforming SA, both with synthetic and real data. Statistical analysis reveal excellent performance within a reasonable computational time. Specifically, correlation coefficients for synthetic and real impedance cases are 0.99 and 0.88, respectively, while RMS errors are 0.11 and 0.26. Additionally, the hybrid optimization approach predicts impedance volume in the inter-well region, demonstrating superior subsurface information resolution compared to SA.
Research highlightsDeveloped a hybrid SA–QNM optimization framework that enhances global exploration and local convergence in acoustic impedance inversion. Achieved superior accuracy, with correlation coefficients of 0.99 (synthetic) and 0.88 (real) and significantly reduced RMS errors. Demonstrated improved inter-well impedance prediction and higher subsurface resolution over conventional simulated annealing.