Compaction — the great unknown in basin modelling

Abstract

Decompaction routines are used in basin modelling packages to calculate sediment thickness and material properties such as thermal conductivity. However, compaction in nature is dependent on initial porosity, composition, and effective stress, and a considerable range of porosity-depth trends exists. Simple thermal modelling demonstrates that significant uncertainties (up to VRE ± 0.5) arise in predicted maturities due to this variation. Furthermore, the validity of using porosity loss as a measure of compaction is questionable because changes in solid volume can occur. Chemical reaction may increase or decrease porosity without changing sediment thickness, although an apparently smooth transition occurs from dominantly mechanical processes of porosity loss (e.g. grain rearrangement) at shallow levels to dominantly chemical processes (e.g. grain dissolution/cementation) at depth. That compaction and porosity loss are processes dependent upon effective stress, time and temperature is illustrated by the observation of overpressuring in the subsurface, comparison of experimental and natural compaction rates and analysis of porosity-depth trends for sediments of different ages. Mechanistic models of the processes involved in compaction (e.g. pressure solution) also indicate time dependency. Time-dependent models of compaction can be constructed, but these are difficult to incorporate into basin models as they cannot be run in a simple backstripping mode.

Fault Zone Resistivity Structure and Monitoring at the Taiwan Chelungpu Drilling Project (TCDP)

“…Increasing the effective porosity from 1.4 to 3.1% can account for the observed decrease in resistivity. These porosity values are reasonable and in agreement with studies of near surface materials (Giles et al 1998). Alternatively, the change in resistivity could be explained by maintaining a constant porosity, but increasing the saturation.…”

“…Measurements on the core recovered from the A-hole by Tanaka et al (2006) reported porosity values of 8% and 30% at 1000 and 1300 m depth, respectively. Porosity typically decreases exponentially with depth (Rubey and Hubbert 1959;Giles et al 1998). However, in this case, the increase in porosity with depth is likely associated with the damage zone associated with the Chelungpu Fault zone.…”

Enhanced velocity based pore pressure prediction using lithofacies clustering: A case study from a reservoir with complex lithology in Dezful Embayment, SW Iran

“…Giles et al (1998) introduced new parameter τ , and coupled the velocity to effective stress via empirical constants as:…”

“…proposed a power-law relationship between compressional velocity and effective stress by calculating the overburden stress and predict the pore pressure at offset well locations. Similarly, Giles et al (1998) introduced a compound mudline and matrix-transittime variable (Tau) as a first-order effective stress versus velocity power-law relationship. Later, Boitnott et al (2009) improved Bowers method by considering a normal compaction trend that is asymptotic to matrix velocities and can provide a better representation of the physical properties of the rocks.…”

Quantitative Modeling in the North Sea: Towards a More Confident Assessment of the Critical Risks

“…Historically basin models have only been able to simulate mechanical compaction, for example by using an elastoplastic effective-stress law (Giles et al, 1998). Normally the modeler defines this law using a porosity-depth curve such as Curve B.…”