Abstract: Methods (and related apparatus) include obtaining data regarding a measured property. The measured property includes an amount of each of predetermined hydrocarbons in a gas sample extracted from drilling fluid exiting a wellbore having a hydrocarbon resource. An unknown characteristic of an investigated fluid property of the hydrocarbon resource is predicted utilizing the obtained input data and one or more predetermined models each built via statistical classification and regression analysis of a preexisting database containing records. Each record includes known characteristics of fluid properties of a different one of known reservoir fluids. The fluid properties include the investigated fluid property and the measured property. The investigated fluid property includes a fluid type of the hydrocarbon resource, an amount of at least one additional hydrocarbon, gas-oil ratio, or stock tank oil density.

Abstract: It involves the field of power trading technology and a method for microservice transformation of power trading function comprising the following steps: (1) divide the function in extranet trading cloud into many multiple individual micro services and divide the function in intranet trading cloud into multiple individual micro services; (2) register a node information for each individual micro service in service registry when service deployment starts; (3) extranet users and intranet users enter into extranet trading cloud and intranet trading cloud respectively through PC terminal or mobile terminal, obtain the actual network address that needs to be served from service registry, send a request to the requested service, and perform related business operation.

Abstract: The invention involves the field of power trading and especially involves a method for construction of power trading index system based on big data technology. Main steps are as follows: 1. data acquisition; 2. construction of index system: construction of index system is mainly based on cloud focus evaluation method to solve the problem of variables transformation and make data analysis through high concurrency distributed computing power of Spark memory access; 3. index calculation: adopt objective weighting approach to determine the weight of each index after index configuration and then adopt cloud focus evaluation method to calculate the weighted deviation of each index; store final evaluation result of each index into HDFS database after Spark calculation; 4. index display.

Abstract: It involves the field of power trading technology and a method for microservice transformation of power trading function comprising the following steps: (1) divide the function in extranet trading cloud into many multiple individual micro services and divide the function in intranet trading cloud into multiple individual micro services; (2) register a node information for each individual micro service in service registry when service deployment starts; (3) extranet users and intranet users enter into extranet trading cloud and intranet trading cloud respectively through PC terminal or mobile terminal, obtain the actual network address that needs to be served from service registry, send a request to the requested service, and perform related business operation.