International Business Machines Corporation

Petrogal Brasil S.a.

Rodrigo Da Silva Ferreira

Emilio Ashton Vital Brazil

Renato Fontoura De Gusmao Cerqueira

Viviane Torres Da Silva

Joana De Noronha Ribeiro De Almeida

Vagner Figueredo De Santana

Rogerio Abreu De Paula

Ana Fucs

Marco Daniel Melo Ferraz

Dario Sergio Cersosimo

Astrid De Jesus Torres Fernandez

Ulisses Mello

Andrea Britto Mattos Lima

Alecio Pedro Delazari Binotto

Renan Francisco Santos Souza

Renato Fontoura De Gusmão Cerqueira

Vinicius Costa Villas Boas Segura

Matheus Palhares Viana

Leonardo Guerreiro Azevedo

Michael Raghib Moreno

Juliana Jansen Ferreira

Leonardo Pondian Tizzei

Dario Sergio Cersósimo

Reinaldo Mozart Da Gama E Silva

Leonardo Silveira De Albuquerque Martins

Raphael Melo Thiago

Elton Figueiredo De Souza Soares

Bruno Felix Carvalho

Storing and retrieving subsurface rock physical property models for well drilling by generating estimated subsurface rock physical property models based on a respective set of seismic data, determining a stratigraphic classification for each model based on seismic interpretation data; storing the models associated classification in a database, determining characteristics of the seismic data used to generate the models, selecting from the database a subset of the models based on a similarity of the stratigraphic classification, determining measures of similarity between the characteristics of the seismic data used to generate each of subset of the models and a new set of seismic data and retrieving an estimated subsurface rock physical property model from the subset models based on the similarity measures.

Storage and retrieval of subsurface rock physical property prediction models using seismic interpretation

Machine teaching in an embodiment can include receiving a user annotated concept for a given image in given context. The given image can be broken into parts and classified. Relationships can be determined associated with the parts. The created relationships can be stored along with the user annotated concept in a knowledge base. One or more similar images can be annotated using the parts and relationships. A second image associated the given context can be retrieved, decomposed into parts. The parts can be classified. Relationships can be determined associated with the second image's parts. Classifications and relationships associated with the second image's parts can be compared with classifications and relationships associated with the given image's parts. Based on comparing, the second image can be annotated with the user annotated concept for the given image.

Machine teaching complex concepts assisted by computer vision and knowledge reasoning

A seismic dataset and a task to be performed with the seismic dataset may be received. A representative seismic line representative of the seismic dataset may be generated. The representative seismic line may include pixel data representative of the seismic dataset. Based on the representative seismic line, the task may be performed. The task may include at least finding an analogous geological region by searching for an analogous seismic dataset existing in a seismic database by comparing the representative seismic line with the analogous seismic dataset's representative seismic line.

Seismic data representation and comparison

A metadata-based scientific data characterization method, system, and computer program product include requesting a user input for a task to specify a rule for the task to determine a quality and a relationship of a data file in a data file database based on metadata associated with the data file, processing a user feedback of results using the rule run on the data file database and tracking the user feedback on the results in order to learn from the user feedback, and based on the learning, creating a modified rule to determine a quality and a relationship of a second data file.

Metadata-based scientific data characterization driven by a knowledge database at scale

Method, apparatus, and computer program product are provided for retrieving analogues using topological knowledge representation (TKR). In some embodiments, a TKR input query is built and/or validated using a domain-specific knowledge base (KB). A search database containing candidate analogues and corresponding pre-built TKRs is then searched to retrieve at least one analogue of the TKR input query using statistical analysis. In some embodiments, a system may build the TKR input query based on a seismic dataset. For example, the system may receive a seismic dataset, segment the seismic dataset and classify each region using a computer vision (CV) database and the KB, and build the TKR input query based on the segmented and classified seismic dataset. In some embodiments, the TKR input query may be input and/or edited by a user. For example, the TKR input query may be input and/or edited by the user and validated using the KB.

Searching for analogue subsurface structures based on topological knowledge representation (TKR)

A system, method and program product for implementing a sketch-based retrieval system. A system is disclosed that includes: an interface having a canvas for entering inputs including user generated strokes, and extracting features associated with the inputs; a hierarchy system for assigning an importance to the inputs; a matching system for retrieving matches from a database based on extracted features and importance associated with the extracted features; a feedback system that provides real-time feedback on the canvas to suggest improved inputs for the user; and a ranking system that ranks retrieved matches for output in the interface by incorporating user interaction history.

Sketch-based image retrieval using feedback and hierarchies

A method is provided, the method including: displaying an image on a display; detect a user input corresponding to one or more portions of the image; analyzing the user input to determine at least one feature vector corresponding to the user input; and determining a classification for the one or more portions of the image based at least on the at least one feature vector.

Steering seismic texture analysis algorithms using expert input

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Rio de Janeiro, Brazil

Rodrigo Da Silva Ferreira