Gelinsky, Stephan (Shell International E&P) | Kho, Sze-Fong (Shell International E&P) | Espejo, Irene (Shell International E&P) | Keym, Matthias (Shell Malaysia) | Näth, Jochen (BSP) | Lehner, Beni (BSP) | Setiana, Agus (BSP) | Esquito, Bench (SDB) | Jäger, Günther (SDB)
Prospects below or near shallower producing fields can be economically attractive yet also risky since reservoir presence may be uncertain, reservoir quality can be poor, and high overpressure and temperature can make drilling and logging deeper prospects difficult. Systematic integration of relevant subsurface data from thin section to basin scale allows to seismically identify reservoir presence, and to predict reservoir quality for applicable rock types via burial histories. On an intermediate well log to seismic scale, a predictive rock physics modeling approach links reservoir and seal rock properties to seismic amplitude data to polarize the prospect's geologic ‘probability of success'. Particular challenges in the offshore Brunei study were very fine-grained deposits and non-vertical tectonic stresses associated with compressional settings. Both make porosity predictions that leverage complex burial histories rather than relying on extrapolated depth trends quite challenging - yet the integrated approach remains the best option to identify deep reservoir quality sweetspots that a favorable stress and temperature history may have preserved for certain reservoir rock types in certain locations.
The prolific petroleum system offshore Brunei features two major sediment fairways, the Baram and Champion river systems, and a variety of depositional environments, ranging from high NtG topsets inboard over shallow marine slope settings to deepwater turbidites outboard (
Deep-water turbidites can hold significant amounts of hydrocarbon reserves. One principal element of reserves estimation is accurate hydrocarbon-in-place determination. In this type of reservoir this value is often difficult to obtain as turbidites are primarily composed of thinly bedded shale and sand beds. When shale and sand lamina are below a tool's vertical resolution, petrophysical properties, for example porosity, are averaged across the shale and sand lamina. Also, resistivity measured by conventional induction devices is biased toward the low-resistivity lamina-component, e.g. shale. This creates the classical low-contrast, low-resistivity predicament where quantification of hydrocarbon saturations and net-to-gross is problematic.
Tensor resistivity measurements provide both horizontal and vertical resistivities. The vertical resistivity is more representative of the high-resistivity lamina component, e.g. hydrocarbon-saturated sand. The tensor resistivity measurements are also used to measure large-volume (cubic meters) formation dip and azimuth.
Tensor resistivity and nuclear magnetic resonance data were acquired in this deep-water turbidite field. The data were used to provide a more accurate hydrocarbon-in-place value than was obtainable using conventional resistivity measurements in lowcontrast, low-resistivity shaly sand formations and to obtain formation dips and azimuths. A methodology directed at the sandlamina petrophysical properties was used. Work was performed in a total porosity system, using dry-shale density calculated by comparing nuclear magnetic resonance (NMR) porosity data with the neutron-density porosity in shale. By comparing the final analysis with core data, it is shown that the integration of tensor resistivity and NMR data accurately computes oil saturations, sand fraction porosity and net sand thickness. There is a large increase in the calculated cumulative hydrocarbon volume over conventional petrophysical approaches due to increased precision and accuracy in the sand-lamina porosity, hydrocarbon saturation, and net sand thickness determination.
Geologically, thin beds are classified as medium to thick (greater than 10 cm), thin (3-10 cm) and very thin (less than 3 cm), with the lamina less than 1 cm thick (Campbell, 1967). In contrast, petrophysical thin beds are more loosely defined as beds that are below the resolution of the measuring tool's capability of reading a true value for the bed in question; for example sandstone resistivity. For a gamma-ray device a thin bed might be about 1 m, for a high-resolution density/neutron it might be 30 cm, and for a borehole image log it could be approximately 3 cm. Very few conventional wireline logs can resolve below 10 cm without special inversion-processing methods.
In thin beds, if the bed is thick enough, the representative petrophysical measurement value is often taken at the measurement peak. The measured peaks, however, comprise some proportional average of the over- and underlying beds. In the case of alternating thin-bedded shale and sandstone, shale beds are usually conductors. Due to the averaging effect, the apparent resistivity of hydrocarbon-bearing sandstone is reduced and can result in underestimating the true hydrocarbon saturation or even missed pay.