[First Hit]

Datapages, Inc.Print this page

Improved Pore Pressure Prediction by Integrating Basin Modeling and Seismic Methods

Hans Martin Helset, Mikael Lüthje, and Ira Ojala
SINTEF Petroleum Research AS, Stavanger, Norway

The objective of this work is to develop improved methods for predicting pore pressure from seismic data. Analysis of seismic data is combined with basin modeling techniques in order to obtain an accurate and robust prediction of pore pressures prior to drilling. As part of the project, Previous HitvelocityNext Hit-Previous HitdepthNext Hit trend models for sedimentary rocks have been developed and calibrated.

Seismic Previous HitvelocityNext Hit data is often used for prediction of pore pressures prior to drilling. Standard methods include effective-Previous HitdepthNext Hit methods and empirical methods (e.g. Eatons method). These methods have been used with fair success in areas like the Gulf of Mexico where sedimentation rates are fairly rapid. Applying these methods in other areas, e.g. the North Sea, has been more problematic. The prediction methods typically use relations between Previous HitvelocityNext Hit and effective stress, and are designed for cases where compaction disequilibrium is the cause of overpressuring. In this work we include other pressure-generating mechanisms besides compaction disequilibrium when Previous HitusingNext Hit seismic data for pressure prediction.

The Previous HitvelocityNext Hit of seismic waves depends on the porosity and pore pressure and the burial history of the sediments. The relationship between seismic Previous HitvelocityNext Hit and pore pressure is also related to the particular mechanism that generated the pore pressure. Hence, seismic velocities of the sediments depend both on the compaction state of the sediments and on diagenetic processes. Both compressional and shear Previous HitvelocityNext Hit change with burial Previous HitdepthNext Hit. Knowledge of the Previous HitvelocityNext Hit-Previous HitdepthNext Hit relations is important when interpreting seismic data. Information provided by basin modeling can help establish the correct Previous HitvelocityNext Hit-pressure relation to use in the pore pressure analysis (Bowers 1995).

A large part of the sediment fill in sedimentary basins is made up of shales. A proper description of the shaly sequences is therefore important both for the interpretation of seismic data, and for a accurate estimation of the overburden properties.

Previous HitVelocityNext Hit- Previous HitdepthNext Hit trends
Seismic Previous HitvelocityNext Hit in shale depends both on porosity, mineral content and pore pressure. To be able to estimate pore pressures from Previous HitvelocityNext Hit data, Previous HitvelocityNext Hit-Previous HitdepthNext Hit trends for normally pressured shales must be established. Shales compact both because of external stresses (mechanical compaction), and because of diagenetic processes (chemical compaction). The most import diagenetic process in shales is the smectite illitization.

It has proven problematic to establish general Previous HitvelocityNext Hit-Previous HitdepthNext Hit trends (Storvoll et al. 2005). Hence, we have taken a model-based approach in order to make predictions away from well-control. Rock Physics based models are used for calculating velocities at a given stress and diagenesis state (Holt and Fjær 2003). Burial and diagenesis history will be calculated Previous HitusingNext Hit the basin model Pressim. Log data has been used to validate and calibrate the models.

Integrated pore pressure prediction
Traditionally, pore pressures in subsurface sediments have been predicted Previous HitusingNext Hit either methods based on analysis of seismic Previous HitvelocityNext Hit data or methods related to basin modeling. These two approaches have been used independently. Seismic methods typically use relations between Previous HitvelocityNext Hit and compaction state (effective Previous HitdepthNext Hit methods) or correlations directly between Previous HitvelocityNext Hit and pore pressure (e.g. Eatons method). These methods may work if compaction disequilibrium is the only cause of overpressuring. In this case, the compaction state of the sediments corresponds to the effective stress level.

Other pressure generating mechanisms, termed “fluid expansion mechanisms” (Bowers 1995) or “secondary pressure” (Huffman 2001), include overpressuring from diagenetic processes, hydrocarbon maturation, aquathermal expansion, and up-Previous HitdipNext Hit transfer of reservoir pressures (lateral fluid flow). Diagenetic processes include both smectite illitization in shales and quartz cementation in sandstones. These processes may alter the effective stress without a significant change in porosity. A simple use of porosity-based methods may therefore give large errors in fluid pressure predictions.

Basin modeling (Pressim) can be used to analyze the loading and unloading history of the sediments, as well as impact of diagenetic reactions. The Pressim results will then help choosing the appropriate compaction and rock physics models to use when interpreting the seismic Previous HitvelocityNext Hit data.

Data from a North Sea well has been used to illustrate the modeling approach. The reservoir is located at around 4000 m Previous HitdepthNext Hit. The overburden consists mainly of shales and claystones. The burial history and temperature history are calculated based on the lithostratigraphy for the well. The Rock Physics model is used for calculating the Previous HitvelocityNext Hit-Previous HitdepthNext Hit trend for hydrostatic pressure conditions. Both Vp, Vs and the Vp/Vs ratio for a hydrostatic pore pressure are displayed in Figure 1. These Previous HitdepthNext Hit trends incorporate effects of varying lithology, compaction and clay diagenesis.

For this well only Vp was recorded in the sonic log. The log data is shown in Figure 2 (left panel) together with the predicted normal Previous HitvelocityNext Hit trend. Deviations between the two curves can be attributed to overpressuring. The Previous HitvelocityNext Hit model is used to optimize for overpressure in order to obtain a match between observed and predicted velocities. The resulting overpressure is plotted in Figure 2 (right panel). For comparison, the actual mud weights used are included. Predictions show that the overpressure in the interval between 1500 and 2000 m may be greater than expected during drilling. Also significant deviation between predicted and observed pressures is seen around 4000 m around the reservoir. The high overpressure in the reservoir is likely to be caused by a combination of lateral fluid flow and of quartz cementation in the sandstone. These processes give late build-up of overpressure that is not reflected in undercompaction of the shales. Previous HitCalculationsNext Hit of unloading effects as well as fluid flow (not included in this example) are therefore needed to properly interpret Previous HitvelocityNext Hit data and predict pore pressure at this Previous HitdepthNext Hit.

Bowers, G. L. (1995). "Pore Pressure Estimation From Previous HitVelocityNext Hit Data: Accounting for Overpressure Mechanisms Besides Undercompaction." SPE Drilling & Completion(June 1995): 89-95.

Holt, R. M. and E. Fjær (2003). Wave velocities in shales - a rock physics model. EAGE 65th Conference & Exhibition, Stavanger, Norway.

Huffman, A. R. (2001). The Future of Pore-Pressure Prediction Previous HitUsingNext Hit Geophysical Methods. Offshore Technology Conference, Houston, Tx.

Storvoll, V., K. Bjørlykke and N. H. Mondol (2005). "Previous HitVelocityNext Hit-Previous HitdepthNext Hit trends in Mesozoic and Cenozoic sediments from the Norwegian Shelf." AAPG Bulletin 89(3 (March)): 359-381.

Figure 1. Normal Previous HitvelocityTop trend for a selected North Sea well

Figure 2. Left: predicted normal pressure trend compared with the sonic log data, right: overpressure (in Equivalent Mud Weight) predicted from the sonic log data.



AAPG Search and Discovery Article #90091©2009 AAPG Hedberg Research Conference, May 3-7, 2009 - Napa, California, U.S.A.