Reservoir properties prediction

Reliable information about structural plan and reservoir properties is a prerequisite for drilling planning and reserves estimation. The many years of experience of PetroTrace employees in various oil and gas provinces enables effective integration, analysis and interpretation of all available geological and geophysical information in the region under study. High-tech methods of volumetric imaging, horizon and fault tracing, attribute analysis and inversion increase the speed and accuracy of structural and dynamic interpretation.


AVO analysis

AVO analysis

AVO anomalies (in red) interpreted as hydrocarbon presense

AVO analysis allows to study changes in the amplitudes of the reflected seismic wavefield depending on the angle at which the target boundary is illuminated. Such changes have a regular character, and the anomalous behavior of amplitudes depending on the reflection angle is associated with variations in the lithological composition of rocks and the presence of hydrocarbons in the reservoir formation. Moreover, in contrast to the attribute analysis performed on summarized data, AVO-attributes evaluation is performed on seismograms and allows to more effectively distinguish the influence of the material composition and fluid saturation of the reservoir on wave field amplitudes, thereby increasing the reliability of interpretation.


Inversion

Inversion

Gas deposit (blue) outlined by inversion

Seismic inversion realizes the transition from wave field amplitudes to the spatial distribution of elastic properties of rocks and is the main tool for quantitative prediction of the material composition and filtration-volume parameters of a reservoir based on seismic data. PetroTrace has a wide arsenal of different inversion algorithms applicable in various geological conditions and our specialists perform the entire cycle of work necessary for inversion conversions: from modeling of elastic properties and justification of forecasting possibility on well data to obtaining cubes and maps of reservoir properties of target formations. Seismic inversion results are used to build digital geological, hydrodynamic and geomechanical models of the intervals of interest.


Attribute analysis

Attribute analysis

Channel system found as a result of attribute analyses

The results of attribute analysis reduce the risks of predicting reservoir parameters and provide a more complete picture of the geologic structure of the interval under study. The use of a single seismic attribute cannot characterize a reservoir with sufficient confidence. To increase the reliability of property prediction, PetroTrace geophysicists apply technologies of automatic multi-attribute classification, RGB blending and neural networks, which allows to obtain maps and parameter cubes based on a set of informative seismic attributes.


Abnormally high reservoir pressure forecast

Abnormally high reservoir pressure forecast

3D distribution of reservoir pressure

Information about the depth and lateral distribution of abnormally high pore pressure areas can significantly reduce risks, timing and costs of drilling. The PetroTrace team has all the necessary tools and experience to abnormally high reservoir pressure forecast due to the integration of downhole data and high-resolution interval velocity arrays obtained during seismic processing. As a result of the project, geologists and drillers have a predictive pressure cube at their disposal, from which pressure profiles for any planned well paths and pressure maps for all target intervals can be constructed.


Fracture prediction

Fracture prediction

Using mutiple attributes to prdict fractures from seismic data

Rock fracture prediction plays an important role in evaluating the filtration-volume properties of carbonate and unconventional oil and gas reservoirs. PetroTrace geophysicists predict fracturing from full-azimuth seismic data by combining geometric attributes, azimuthal anisotropy parameters and diffuse wavefield components. Fracture information extracted from seismic data is further used to build geological and hydrodynamic models of productive formations to make effective decisions on their development plans.