A Multi-Point Geostatistical Seismic Inversion Method Based on Local Probability Updating of Lithofacies

In order to solve the problem that elastic parameter constraints are not taken into account in local lithofacies updating in multi-point geostatistical inversion, a new multi-point geostatistical inversion method with local facies updating under seismic elastic constraints is proposed. The main improvement of the method is that the probability of multi-point facies modeling is combined with the facies probability reflected by the optimal elastic parameters retained from the previous inversion to predict and update the current lithofacies model. Constrained by the current lithofacies model, the elastic parameters were obtained via direct sampling based on the statistical relationship between the lithofacies and the elastic parameters. Forward simulation records were generated via convolution and were compared with the actual seismic records to obtain the optimal lithofacies and elastic parameters. The inversion method adopts the internal and external double cycle iteration mechanism, and the internal cycle updates and inverts the local lithofacies. The outer cycle determines whether the correlation between the entire seismic record and the actual seismic record meets the given conditions, and the cycle iterates until the given conditions are met in order to achieve seismic inversion prediction. The theoretical model of the Stanford Center for Reservoir Forecasting and the practical model of the Xinchang gas field in western China were used to test the new method. The results show that the correlation between the synthetic seismic records and the actual seismic records is the best, and the lithofacies matching degree of the inversion is the highest. The results of the conventional multi-point geostatistical inversion are the next best, and the results of the two-point geostatistical inversion are the worst. The results show that the reservoir parameters obtained using the local probability updating of lithofacies method are closer to the actual reservoir parameters. This method is worth popularizing in practical exploration and development.

Operação Lava Jato: Impactos no Mercado Segurador de Responsabilidade Civil de Executivos

ABSTRACT Context: triggered in 2014, the Car Wash Operation (CWO) belongs to a process of changing the legal context, in the sense of greater responsibility and penalization of public and private companies’ decision makers for acts practiced in the exercise of their functions, object of the Directors’ and Officers’ liability insurance coverage (D&O). Objective: to evaluate the relationship between the growth in the revenues of D&O insurance premiums and the developments of the OCW in Brazil, under the hypothesis of a change in the perception of economic agents exposed to risks covered by D&O insurance, in a process known as probability updating. Methods: official monthly data for all active insurers, arranged longitudinally between 2003 and 2017, and using two-stage regression method for panel data. Results: the OCW had a positive effect not only to the probability of offering this type of insurance, but also to increase the volume of D&O premiums; these results are consistent with the probability-updating hypothesis. Conclusion: the OCW resulted in an increase in revenues of D&O premiums, but there was a negative relationship between OCW and the entire insurance market, suggesting significance of this operation in the sector retraction observed since its outbreak.

Operation Car Wash: Impacts on the Executives' Liability Insurance Market

ABSTRACT Context: triggered in 2014, the Car Wash Operation (CWO) belongs to a process of changing the legal context, in the sense of greater responsibility and penalization of public and private companies’ decision makers for acts practiced in the exercise of their functions, object of the Directors’ and Officers’ liability insurance coverage (D&O). Objective: to evaluate the relationship between the growth in the revenues of D&O insurance premiums and the developments of the OCW in Brazil, under the hypothesis of a change in the perception of economic agents exposed to risks covered by D&O insurance, in a process known as probability updating. Methods: official monthly data for all active insurers, arranged longitudinally between 2003 and 2017, and using two-stage regression method for panel data. Results: the OCW had a positive effect not only to the probability of offering this type of insurance, but also to increase the volume of D&O premiums; these results are consistent with the probability-updating hypothesis. Conclusion: the OCW resulted in an increase in revenues of D&O premiums, but there was a negative relationship between OCW and the entire insurance market, suggesting significance of this operation in the sector retraction observed since its outbreak.