{"schema_version":"1.0","canonical_url":"https://patentable.app/patents/US-9619590","patent":{"patent_number":"US-9619590","title":"Uncertainty estimation for large-scale nonlinear inverse problems using geometric sampling and covariance-free model compression","assignee":null,"inventors":[],"filing_date":"2011-03-14T00:00:00.000Z","publication_date":"2017-04-11T00:00:00.000Z","cpc_codes":["G06F","G06F"],"num_claims":6,"abstract":"A method for uncertainty estimation for nonlinear inverse problems includes obtaining an inverse model of spatial distribution of a physical property of subsurface formations. A set of possible models of spatial distribution is obtained based on the measurements. A set of model parameters is obtained. The number of model parameters is reduced by covariance free compression transform. Upper and lower limits of a value of the physical property are mapped to orthogonal space. A model polytope including a geometric region of feasible models is defined. At least one of random and geometric sampling of the model polytope is performed in a reduced-dimensional space to generate an equi-feasible ensemble of models. The reduced-dimensional space includes an approximated hypercube. Probable model samples are evaluated based on data misfits from among an equi-feasible model ensemble determined by forward numerical simulation. Final uncertainties are determined from the equivalent model ensemble and the final uncertainties are displayed in at least one map."},"analysis":{"summary":null,"layman_explanation":null,"technical_analysis":null,"business_analysis":null,"faqs":null,"topics":[],"tech_cluster":null},"seo":{"title":"Uncertainty estimation for large-scale nonlinear inverse problems using geometric sampling and covariance-free model compression","description":"A method for uncertainty estimation for nonlinear inverse problems includes obtaining an inverse model of spatial distribution of a physical property of subsurface formations. A set of possible models","keywords":[]},"attribution":{"source":"Patentable","source_url":"https://patentable.app","canonical_url":"https://patentable.app/patents/US-9619590","license":"CC-BY-4.0-like","license_terms":"AI-generated analysis on this page (summary, layman_explanation, technical_analysis, business_analysis, faqs) may be reused with attribution and a visible link back to the canonical URL above. Patent abstracts, claims, and bibliographic data are USPTO public domain.","required_link":"https://patentable.app/patents/US-9619590","citation_suggestion":"Patentable. \"Uncertainty estimation for large-scale nonlinear inverse problems using geometric sampling and covariance-free model compression\" (US-9619590). https://patentable.app/patents/US-9619590","copyright_holder":"Nomic Interactive Technology LLC"},"links":{"html":"https://patentable.app/patents/US-9619590","json":"https://patentable.app/api/llm-context/US-9619590","site":"https://patentable.app","llms_txt":"https://patentable.app/llms.txt"},"generated_at":"2026-06-06T06:21:08.600Z"}