Mapping carbonate mounds in the Brazilian pre-salt fields is a major challenge for geoscientists, due to the complexity of the seismic image generated.

A customer in Eastern Europe needed an accurate assessment of effective oil-saturated thicknesses in a major development project. This case study explains how machine learning-based algorithms were used to analyze complex borehole and seismic studies employing a set of unique classification approaches embedded in Aspen SeisEarth™ and Aspen Geolog Facimage™.

Aspen OpsLink is a client-server application that provides operating companies with the ability to make rapid and informed decisions during well operations to minimize risks, minimize costs and maximize productivity. Fast and flexible access to real-time WITSML™-based operational data provides key information required by asset teams.

The Aspen EarthStudy 360 full-azimuth imaging and characterization system provides 360 degrees of insight into the subsurface. The system is designed to deliver a complete set of data that enables geoscientists to obtain accurate subsurface velocity models, structural attributes, medium properties and reservoir characteristics.

Fluvial depositional environments play a major role in hydrocarbon reservoirs and have therefore received considerable attention in the domain of reservoir modeling.

In the upstream oil and gas industry, multiphase metering is a central part of many processes, such as reservoir management, field development, operational control, flow assurance and production allocation. Industrial Internet of Things (IIoT) systems unlock online production monitoring and allow field operators to monitor their wells continuously and in real-time.

Pore pressure prediction and poroelastic modeling help understand the mechanical properties of the subsurface and are regularly used in industries such as oil and gas, geothermal, and CO2 storage.

The rapid and nonintrusive deployment of seismic sensors for near-surface geophysical surveys can make data acquisition more efficient, in a wide variety of environmental and surface-terrain conditions.

Successful reservoir management is inextricably linked to the field’s production system and a complete evaluation of the system’s behavior throughout the reservoir lifecycle. There is also a need for operators to communicate between multiple technical domains from reservoir characterization, flow simulation and network simulation to processing facilities.

Detection and characterization of fractures in reservoirs is important for maximizing hydrocarbon productivity and recovery efficiency. Seismic attributes like coherency and curvature that are derived from reflection seismic data are used to detect faults and fractures. In advanced seismic fracture detection technology, Automatic Fault Extraction from diffraction seismic data effectively detects finer scale features.