Standards in 4D feasibility and interpretation

Abstract

Standards for 4D seismic feasibility estimation and interpretation aim to simplify the 4D seismic interpretation process, facilitate understanding of results, and accelerate learning between projects and between disciplines. Standards encode those best practices that have proved to have a more or less universal relevance in the subject area and provide a convenient starting point for individuals and teams new to 4D interpretation. Standards are about casting a result into a familiar format. The main result is a quality improvement of the integration process between different disciplines; a side effect is the efficiency improvement and time saving from increased skill levels within each discipline. There are currently accepted 4D standards in the fields of F = 4D feasibility (fluid effects) P = poststack processing I = seismic inversion and 4D A = 4D interpretation and attributes S = simulator-to-seismic The primary user group is subsurface professionals in asset teams, in particular reservoir engineers, geologists, and geophysicists. Although 4D seismic is seen as a tool originating in the geophysical domain, the fact that it is about observing reservoir dynamics makes it of primary interest to reservoir engineers and geologists alike.

Scale effects on modelling the seismic signature of gas: results from an outcrop analogue

“…To quantify the 4D signature, we compute the normalized difference root mean square (NdRMS) defined as the difference of the root mean square (RMS) of the monitor and base volumes through the equation (Stammeijer and Hatchell ): where M and B stand for monitor and baseline trace, respectively. As explained by Stammeijer and Hatchell (), this attribute preserves the polarity of change and is suitable to compare changes occurring at the reservoir level to changes at other levels. In our case, we use the NdRMS to capture the differences between monitor and baseline traces for different levels of upscaling and additional effects from multiples (Fig.…”

“…10), shown for angle stacks 0°-10°, 10°-20°, 20°-25°. To quantify the 4D signature, we compute the normalized difference root mean square (NdRMS) defined as the difference of the root mean square (RMS) of the monitor and base volumes through the equation (Stammeijer and Hatchell 2014):…”

“…where M and B stand for monitor and baseline trace, respectively. As explained by Stammeijer and Hatchell (2014), this attribute preserves the polarity of change and is suitable to compare changes occurring at the reservoir level to changes at other levels. In our case, we use the NdRMS to capture the differences between monitor and baseline traces for different levels of upscaling and additional effects from multiples (Fig.…”

LoFS Processing for 4D Attributes at the BC10 Field – Offshore Brazil

“…This included all processing from reformatting the raw SEG-D field data thru final 4D volumes. The processing flow developed and applied to the LoFS data has proven to be very effective and has resulted in NdRMS values at reservoir level of 2.5% for the down-going wavefield per the description of 4D attributes by Stammeijer and Hatchell (2014 …”

Tertiary deep-marine reservoirs of the North Sea region: an introduction

“…During production, the pore fluids, pore pressure and temperature change in the reservoir, and these affect the seismic response. In principle, if seismic surveys are acquired at different times over a producing field, amplitude and time differences between the reservoir seismic responses can be used to infer production-related changes in the reservoir (Stammeijer & Hatchell 2014): for example, the movement of the OWC, the advance of the water flood, swept areas of the field and locations of the bypassed oil (Moore 2014;Rose & Pyle 2014). These can be used to identify infill drilling targets to support late-life production decline, to calibrate static and dynamic reservoir simulation models, and to increase ultimate recovery.…”