Schlumberger Technology Corporation

Sai Venkatakrishnan

Youxiang Zuo

Lei Jiang

Kang Wang

Yingwei Yu

Ryan Sangjun Lee

Sylvain Chambon

Mohammad Khairi Hamzah

XiaoWei Sheng

James P Belaskie

Lixiang Sun

Suchart Chokthanyawat

A method includes acquiring data during rig operations where the rig operations include operations that utilize a bit to drill rock and where the data include different types of data; analyzing the data utilizing a probabilistic mixture model for modes, a detection engine for trends and a network model for an inference based at least in part on at least one of a mode and a trend; and outputting information as to the inference where the inference characterizes a relationship between the bit and the rock.

Real-time well construction process inference through probabilistic data fusion

Disclosed are methods and apparatus obtaining in-situ, real-time data associated with a sample stream obtained by a downhole sampling apparatus disposed in a borehole that extends into a subterranean formation. The obtained data includes multiple fluid properties of the sample stream. The sample stream includes native formation fluid from the subterranean formation and filtrate contamination resulting from formation of the borehole in the subterranean formation. The obtained data is filtered to remove outliers. The filtered data is fit to each of a plurality of models each characterizing a corresponding one of the fluid properties as a function of a pumpout volume or time of the sample stream. Based on the fitted data, a start of a developed flow regime of the native formation fluid within the subterranean formation surrounding the borehole is identified.

Data extraction for OBM contamination monitoring

Growing community of inventors

Beijing, China

Sai Venkatakrishnan