The development of this methodology consists of integrating in a quantitative way, and in a single inversion: seismic data, information from well logs, electromagnetic soundings and gravity data to obtain a single multi-scale model of the reservoir. The method involves honoring well interpreted facies through the geostatistical model calibrated for the area, providing as result the static facies model and the permeability model required for fluid flow simulation. Although the reflection 3D seismic data is the main data to constraint the model, the method also has the potential to include gravity or Controled Source Electromagnetic data, which are important in specific cases. All the information is integrated via our knowledge network technology and includes the development of smart linkages for calibration and integration, aiming to dramatically shortening the time required in the full model building.
This project in progress aims at the total quantitative integration of the information available for the formulation of a multi-scale and multi-property model in dynamic condition (production). The methodology involves the fluid flow modeling and inversion of time lapse-data to characterize the evolution of the reservoir during production and the evaluation of development plans. It includes the development of the different modeling and inversion components, and smart linkages for calibration and integration.The methodology allows for joint inversion of the time-lapse seismic and the production history data with an update of the permebaility model and the dynamic model parameters.
These research topics are in the area of health and regulatory sciences, under consultancy and development services to IDX20. We apply advanced methods for inference in complex models to the problem of (1) quantifying the signal response of common antigen tests and (2) predicting the real-world performance of antigen tests based on the laboratory evaluation. In the former topic, the technology expands the common use of antigen test under the binary (positive-negative) interpretation to a much wider use: translating the signal intensity to viral concentration and interpretating the disease evolution by consecutive measures. In the second topic, the we anticipate the real-world performance of the antigen tests with a relational model that combines laboratory evaluations of the devices and the description of the population hability for naked-eye interpretation of the tests. These research topics involve image processing, quantitative modeling and artificial inteligence methods.
Focused Elastic Full Waveform Inversion (FWI) is a proprietary technology based on targeting the intensity of seismic waves for the characterization of reservoirs. This technology takes advantage of all seismic phases, including reflections, conversions, multiples, and surface waves, thus achieving greater precision than conventional seismic inversion. FWI is a computationally-intensive process, which we make efficient with our advanced algorithms that focusses the seismic energy over the target to obtain optimal precision on the estimated elastic parameters. The method produces a joint estimation of the medium mass density and elastic parameters with a spatial resolution commensurate to the seismic signal for adequate reservoir characterization. This technology is an Info Geosciences LLC´s property and its patent is published in the United States Patent and Trademark Office (USPTO).