Abstract: This disclosure describes systems and methods for determining spatial distributions of petrophysical properties in a subsurface formation. A method includes obtaining input data including petrophysical data, geophysical data and geological data of the subsurface formation; selecting input features from the input data; forming a training dataset including the input features and corresponding labeled data representing a target petrophysical property of the subsurface formation; training, using the training dataset, an ensemble machine learning model; and determining a spatial distribution of the target petrophysical property based on the trained ensemble machine learning model.

Abstract: Methods and systems for generating heterogeneity indices for reservoirs is provided.

Abstract: Systems and methods include a computer-implemented method for performing well placement and configuration. Two-dimensional (2D) target entry (TE) points are generated in an area of interest (AOI) for wells to be drilled in an oil reservoir, where the 2D TE points are positioned according to a defined well length resolution. A single lateral is designed for each well using the 2D TE points, where each single lateral is designed with a different length, completion zone, azimuth, and orientation. Using the single laterals, a dynamic reservoir simulation is executed for the wells to be drilled in the oil reservoir, including rotating between different three-dimensional (3D) configurations for each 2D TE. A 3D configuration for each 2D TE is selected for each lateral and based on executing the dynamic reservoir simulation.

Abstract: Methods and systems for generating heterogeneity indices for reservoirs is provided.