Integrated Services

Load and quality control all the available well information needed for production modeling. Primary well data typically consists of well logs for geologic interpretation and petrophysical analysis, wells with velocity control for seismic interpretation and velocity modeling, and horizontal wells with production and completion data. Following the QC (quality control) of the well information, a rigorous interpretation of the formation tops is performed, making sure the markers are consistently picked at each well. After defining reservoir zones and surrounding formations, the seismic is tied to the wells using available sonic information. If sonic data are not available, either sonic or density can be estimated from the petrophysics. Obtaining accurate well-ties is essential to further analysis, since any errors that occur at this stage will propagate, causing significant problems later in the workflow. Following well-ties and error analysis, formation tops, seismic time interpretations, and well velocity control are integrated to build the velocity model. In parallel, a large number of both post-stack and pre-stack seismic attributes are computed. Finally, the integrated velocity model is used to convert all seismic interpretations and attributes from time to depth. 

Load and QC all relevant deviation surveys, perforation locations, stages, completion and production data. Stage and completion information is used to define productive zones for integrating with the geoscience data.

Integrating the geoscience and engineering data begins by extracting 3-D seismic attributes along each wellbore at or near the stage locations using a determined statistical sampling method. The extracted attributes are correlated with a range of production metrics, completion data and well data to determine the degree to which variables are correlated. This allows the interpreter to understand the individual relationships each variable has with production and what type of transformation may be needed in the multivariate analysis. The goal for this stage is to leverage the integration, allowing the statistics to highlight the meaning of various relationships between production and seismic attributes. The result of multivariate analysis is to identify the Key Performance Indicators (KPI’s) and combined them to create a 3-D seismically-calibrated predictive model of cumulative production (or any other response metric). The integrated  workflow can be repeated and the models can be carried forward throughout the life of a particular reservoir or field.