Pore pressure has proven to be one of the key drivers in the success of drilling and completing wells in the multi-stacked plays of the Delaware Basin petroleum system. Prediction of reservoir pressures and identification of abrupt changes in pressure regimes have become essential to the industry for economic success and for safety reasons. Pressure data coupled with petrophysical rock properties have yielded additional insights to the petroleum system across the Delaware Basin in southeastern New Mexico and Texas.
This paper describes the workflow used for generating a three-dimensional (3D) regional pore pressure model of the Delaware Basin for all geologic intervals. The 3D model was built using a database of over 23,700 mud weight recordings, Drill Stim Test (DST) ISIP readings and Diagnostic Fracture Injection Test (DFIT) pressures from over 4,000 vertical wells. Cross checked with petrophysical logs that deviated from normal compaction trends (NCT) help verify the extent and depths of pore pressure throughout the basin. This data was checked and then geostatistically distributed throughout an earth model. This process yielded three properties typically used by drilling engineers for well planning: Mud weight (ppg), pore pressure (psi), and pressure gradient (psi/ft) for any location in the 3D model. The 3D model was validated by cross-checking it against actual drilling reports and mud weights from horizontal wells.
Using this model, predictions for abnormally pressured zones can be extracted along the planned wellbore, thus helping to avoid drilling and completion challenges. The model also demonstrates a distinct lithologic change preceding a large pressure spike, indicating a regionally identifiable sealing stratigraphy. This may help to explain the differences in pressure regimes across the Delaware Basin.
This paper looks at using predictive modeling of the present-day pore pressure in the Delaware Basin as a key driver to understanding drilling risks, well performance, fluid volumes, and well stimulation techniques. Prediction and identification of pore pressure regimes has proven to be an essential component for the industry for safety, mud systems, fracture stimulation designs, and production success within multiple basins (Loughry et al., 2015). With the higher costs associated with drilling and completions, an operator may not want to perform a Diagnostic Fracture Injection Test (DFIT) or Drill Stem Test (DST) with every well due to the expense and time involved. DFIT's require isolation of zones, long shut-in times and a yield small radius of investigation (Friedrich and Monson, 2013). Accurate collection of DST's also requires additional time for testing in low permeability unconventional reservoirs.
There are, however, numerous mud weights recorded on mud logs throughout the basin, as well as hundreds of log suites containing acoustic curves to leverage and to fill in data gaps. This paper demonstrates a workflow to combine widely available data types with the smaller dataset of highly accurate measurements into a 3D earth model of pore pressure. This aids in the prediction of abrupt changes while drilling and completing wells.