International Business Machines Corporation

Jian Hui Chen

Wei Yan

Kun Yan Yin

Jie Wang

Jian Lu

Sheng Hui Zhan

Wan Wan Miao

Yu Zhu Xu

Xiao Bo Ren

Qi Rong Wang

Yue Liu

Tao Liu

Zhi Lin Hu

Shu Xia Cao

Shu Zhang

Xun Wu

Zi Yang Yu

A cognitive well log analysis using a computer includes receiving, by one or more processors, well log data from a plurality of well logs. One or more processors identify geometric features, specific values, and well attributes from the received well log data and embed the identified features to generate a plurality of intermediate vectors arranged based on a relevance for identifying petrophysical properties. The intermediate vectors are combined to create a fusion vector based on which the one or more processors identify reservoir layers.

Multimodal well log interpretation using deep learning models

A computer-implemented method, system, and computer program product for identifying requirements in a document. A document including requirements is received. Attribute related information in the document is identified using an attribute model. Component information in the document is identified using a component model. The attribute related information and the component information identified in the document are merged. Requirements in the document are identified from the merged attribute related information and component information. The requirements identified in the document are used to develop a product.

Document-based requirements extraction

A well log is scanned for one or more dimensions that describe one or more features of a well. Each dimension includes a plurality of values in a numerical format that represents each dimension. A missing value is detected in a first plurality of values of a first dimension of the well log. The first dimension of the well log is transformed, in response to the missing value, into a first image that visually depicts the first dimension including the first plurality of values and the missing value. Based on the first image and based on an image analysis algorithm a second image is created that visually depicts the first plurality of values and includes a found depiction visually depicting a found value in place of the missing value. The found depiction is converted, based on the second image, into a first value in the numerical format.

Image analysis well log data generation

A search engine identifies external data records that describe similar entities and may each conform to a different data format or source schema. The engine derives mappings capable of translating data values between differently formatted attributes of two source schemas and uses these mappings to identify degrees of similarity between attributes and schemas. When the search engine receives a search request, the engine translates submitted search criteria into values of a first schema's attributes and then uses the mappings to map those values onto selected attributes of other schemas. The search engine then uses each schema's selected attributes to select external data records formatted in that schema. Each selected record is assigned a match score that is weighted by the similarity of the record schema's selected attributes to the search criteria. Records are then retrieved in order of decreasing match score.

Similarity-based search engine

Similarity-based clustering search engine

Growing community of inventors

Ningbo, China

Jian Hui Chen