Having access to all datatypes in a single platform enables knowledge to be captured and utilized with the pressure and stress workflows ensuring consistency allowing for the geological uncertainties to be captured appropriately. The seamless interaction between pre-drill modelling to real-time monitoring ensures no loss of information for safe and cost effective well delivery.
Propagate 1D models into 2D/3D using a wide selection of geostatistical and inversion models. Articulate decisions and maximize safety using best-in-class workflows to effectively communicate well planning and trajectory risks using a clear visualization environment.
Pore pressure and stress models are derived from multidisciplinary approaches and as such there are many factors that need to be considered and visualized to effectively capture the uncertainty within these PPFG models. The crucial part is the risks are effectively communicated during the PPFG planning process to all teams involved. Using scenarios and stochastic modeling allows analyst to explore the uncertainty within the datasets and quickly test multiple potential outcomes.
Challenge: Pore pressure prediction works best in areas where the sediments are young, rapidly deposited, contain similar clay content and are within low temperature environments much like those of Tertiary deltas. The ultra-deep water blocks of Cote d’Ivoire have additional geological complexities that therefore make pore pressure prediction more challenging such as, far offset wells outside survey area, high TOC clays, high geothermal gradients, high net-to-gross.
Solution: One of the key solutions to de-risk the ultra- and deep-water Blocks is to build a geologically sensible geopressure model. Such models rely on a detailed understanding of lithologies, facies and depositional models, e.g. the presence of deep-water turbidites, slope fan channels, stratigraphic pinch-out, and rotated fault blocks. The pressure model constructed must explain the current overpressure occurrences, taking into account the local geology and analogous areas (structure, stresses, temperature, basin history, sedimentation rates, and depositional architecture). Using the model we can then sense check any seismic velocity based interpretations.
Results: Accurate prediction of facies, reservoir properties and pressure. The well was complete on time and ahead of budget with best in class drilling performance and no NPT.
Understanding the stress state in the earth is of vital importance for well plan design, completions optimisation, cap rock integrity, and wellbore stability. Finding a prospect is only part of the battle; safely drilling the well and optimising production is the end goal.
Accelerate learnings of rock mechanical properties and predict where and when those rocks will deform
Interpretation of image logs for borehole breakouts, sedimentology and fractures. Interactive geomechanical model building, analysis and scenario modelling. Key features include; surface picking and image log conditioning, static-dynamic property calibration, wellbore stability, stereonets and more.
Pre-drill estimates of pore pressure are commonly derived from well log data and seismic velocity data assuming a velocity-to-effective stress transforms is appropriate. Some of the many challenges in performing predictions with seismic velocities is down to the quality, calibration, scale, extrapolation, and the geological environment that is present. If valid then these models provide useful and intuitive ways of communicating risks between assets and business units.
Effectively communicate pressure and stress related risks with multiple stakeholders
Develop 3D models for prediction of subsurface pore pressures away from well control. Key features include; 3D model building, zone based overburden and normal compaction trends, seismic velocity calibration, stochastic pore pressure prediction, multi-realisation analysis and well planning.
Schedule a consultation with our experts to discuss how to extract better insights from your complex subsurface data.
By submitting this form, you are consenting to receive marketing emails from: Ikon Science, 1 The Crescent, Surbiton, Greater London, KT6 4BN United Kingdom, http://www.ikonscience.com. You can revoke your consent to receive emails at any time by using the SafeUnsubscribe SafeUnsubscribe® link, found at the bottom of every email.