Fresh off the back of a string of pore pressure prediction related consultancy projects and conference presentations, Glyn shares some thoughts on Rockfield’s pore pressure prediction capabilities.
The evolutionary approach
Rockfield have been involved in pore pressure prediction for many years, using our forward modelling capability to adopt a “full-physics” approach to capture the evolution of sedimentary basins through geological time, including all associated pore pressure changes.
At the most sophisticated end of the spectrum, the Thermal-Hydro-Mechanically (THM) coupled approach solves three interdependent analysis fields simultaneously, thereby capturing the complex interactions and interdependent mechanisms between mechanical deformation, fluid flow and temperature changes.
Valuable insight can be gained by applying the modelling to a 1D approach for pore pressure prediction. For example, by modelling the Canadian Anticosti basin in this manner, we capture mechanisms for overpressure generation (disequilibrium compaction, aquathermal) and hydrocarbon maturation (single phase kinetics) with evolving sedimentation, see Figure 1.
As a side-note, this 1D THM column test functionality will soon be available to trial as a self-contained package within our new Elfen FM release, along with a number of new UI features (see Figure 2)… it might even warrant a blogpost of its own so watch this space!
While useful in its own right, the 1D column approach serves as an important building block from which to pursue 2D or 3D basin-scale investigations capable of capturing important mechanisms for lateral fluid migration. In combination with far-field tectonic loading (e.g. shortening / extension, folding, faulting) and/or salt diapirisms (and associated halokinesis), the modelling provides a comprehensive representation of geological history and a pore pressure prediction tool of unrivalled sophistication.
Since forward modelling typically targets present-day structural interpretations of the sub-surface as its main form of “calibration” – for example, a complex salt morphology or faulted anticline – this implies an iterative, sensitivity-based approach. Furthermore, the parameter space is typically large, inter-dependent and sometimes uncertain.Although full-physics evolutionary model provide to most detailed assessment of geological development, the unconstrained final geometry is not a guarantee – therefore, for this level of geometric accuracy, the forward modelling may be complimented by static models.
Present Geometry constrained Static modelling
An alternative, or compliment, to the evolutionary treatment is available in the form of static geomechanical modelling. This class of model uses the present day field configuration – as deduced from seismic surveys etc. – as a fundamental input rather than a modelling outcome.
The static, finite element model captures field-wide stratigraphic variability (2D / 3D) in the form of material, stress and pore pressure contrasts estimated from available field data (e.g. sonic logs, exploratory wells etc.). Any gaps in data can be supplemented with experience or reasonable assumption and the model can be easily refined as new data becomes available. This “best-estimate” of material and stress state is applied to the model and allowed to equilibrate under gravity, whereby perturbations in stress orientation and magnitude may develop as said material and stress contrasts are resolved.
This equilibrated material and stress state is always of great interest to those engaged in drilling operations, but particularly so when in the presence of salt structures.
Salt behaves very differently to most clastic / carbonate rocks. Owing to its polycrystalline structure, it is relatively incompressible with near constant bulk density and is therefore either more or less dense than its surroundings, depending on its position within the stratigraphic column. Shallow salt bodies tend to be negatively buoyant (sinking) while deeper salt bodies tend to be positively buoyant (uplifting). Neutral buoyancy tends to typically occur at about 1500m below the mudline.
Furthermore, salt is weak and easily deformable and flows like a viscous fluid over geological / timeframes (creep). Salt is unable to sustain deviatoric (shear) stress and creeps until it achieves an isotropic state of stress. Salt viscosity and therefore creep rate is sensitive to temperature. In short, salt’s rheology and incompressibility make it inherently unstable under a wide variety of conditions.
By incorporating a geometric and material constitutive representation of the often complex 3D salt structures, the static geomechanical model provides spatial predictions of equilibrated stresses which would otherwise remain poorly constrained. Anticipation of problematic stress conditions, particularly the magnitude and orientation of the minimum stress, is vital for well planning and drilling risk assessment.
Two birds with one stone: stress and pore pressure prediction
Static geomechanical modelling of salt-dominated basins has become fairly common practice within the industry over the past decade, with ever-growing scope and levels of detail. Traditionally, these models were geared towards stress prediction alone.
However, owing to recent integration of novel concepts devised by our colleagues / frequent collaborators at UT Geofluids, static geomechanical modelling within Elfen Horizon can be expanded to serve a second, but no less important, function: advanced pore pressure prediction.
Pore pressure and stress are inextricably linked and together define the limits for safe and economic drilling. Typical industry standard pore pressure prediction, such as the Bowers or Eaton approaches, are termed Vertical Effective Stress (VES) methods.
The Bowers approach for example, is an empirical function which relates measured seismic velocity to the effective vertical stress (via porosity). Lower velocity (and hence higher porosity) than expected is indicative of undercompaction, attributable to overpressure. Pore pressure is therefore calculated as the difference between the overburden total stress σv and the velocity-derived effective vertical stress σ’v
This method is underpinned by an assumption of uniaxial strain. In more complex geological settings – such as in the vicinity of salt structures – the contribution of lateral and shear components may be significant and hence the VES method may under predict the pore pressure.
The “Full Effective Stress (FES)” method on the other hand is conducted in terms of the geomechanical model-derived full effective stress tensor and hence accounts for lateral and shear components. It follows a similar form to the Bowers equation, but invokes four additional input parameters which are related to established and measurable geological behaviour (see Figure 3). Several modelling iterations are performed, whereby the geomechanical model is updated with successive FES pore pressure predictions in order to achieve a fully reconciled stress-pore pressure solution.
To date the FES workflow has been applied to various salt-dominated prospects, with very encouraging results. On a practical level, the workflow has been refined and additional functionality integrated into the Elfen Horizon package to facilitate import of the required seismic velocity cube (in SEG-Y / point cloud format) and definition of the pore pressure prediction parameters. The analysis can be solved for ~20 million elements in a matter of hours!).
Figure 4 below illustrates some of the successes of the approach, in the form of pre-drill advanced pore pressure prediction and post-drill validation of minimum stress.
Predictions by the MES method is also shown. The MES method is an intermediate between the VES and FES which considers the role of lateral stress (via mean stress) but not shear. It is also available for calculation within the Elfen Horizon pore pressure prediction package.
The FES (and MES) technology has proved to be of significant value to the operator. Not only have the models provided assessment of specific candidate well trajectories, with tangible benefit to drilling budgets and aiding key decisions such as setting of casing depth, but they will continue to be used in planning further wells.
This class of model is particularly well-suited and valuable in an exploration setting where data is scare; in many of the models run to date, data gaps were addressed with generic input parameters and assumptions based on regional experience. Even so, predictions of minimum stress in particular proved reliable. As mentioned, the models can be continually refined as more data becomes available.
We hope this new technology will be of great interest and value to your business. If you are simulating problems within one of the application areas we’ve mentioned or you’re facing a different challenge that we can help with, then get in touch.
Share your thoughts by dropping us a line at email@example.com.