{"schema_version":"1.0","canonical_url":"https://patentable.app/patents/US-10519766","patent":{"patent_number":"US-10519766","title":"Reservoir modelling with multiple point statistics from a non-stationary training image","assignee":null,"inventors":[],"filing_date":"2012-07-18T00:00:00.000Z","publication_date":"2019-12-31T00:00:00.000Z","cpc_codes":["G06T"],"num_claims":4,"abstract":"A multiple point simulation technique for generating a model realization of a subterranean formation having different facies is described which uses a non-stationary training image which reflects facies spatial trends across the formation. The realization is formed by sequentially populating each cell; a facies pattern of neighboring cells is identified for each cell in the model grid, and then corresponding facies patterns identified in the training image. The probability of a target cell in the model grid having a given facies is calculated based on the proportion of occurrences of the corresponding facies pattern where the central cell has that facies. The contribution of each corresponding facies pattern occurrence in the training image to this proportion or probability is weighted according to the distance between its central cell and the training image cell corresponding in location to the target cell in the model grid."},"analysis":{"summary":null,"layman_explanation":null,"technical_analysis":null,"business_analysis":null,"faqs":null,"topics":[],"tech_cluster":null},"seo":{"title":"Reservoir modelling with multiple point statistics from a non-stationary training image","description":"A multiple point simulation technique for generating a model realization of a subterranean formation having different facies is described which uses a non-stationary training image which reflects faci","keywords":[]},"attribution":{"source":"Patentable","source_url":"https://patentable.app","canonical_url":"https://patentable.app/patents/US-10519766","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-10519766","citation_suggestion":"Patentable. \"Reservoir modelling with multiple point statistics from a non-stationary training image\" (US-10519766). https://patentable.app/patents/US-10519766","copyright_holder":"Nomic Interactive Technology LLC"},"links":{"html":"https://patentable.app/patents/US-10519766","json":"https://patentable.app/api/llm-context/US-10519766","site":"https://patentable.app","llms_txt":"https://patentable.app/llms.txt"},"generated_at":"2026-05-30T08:43:59.353Z"}