No abstract

A B S T R A C TOf particular concern in the monitoring of gas injection for the purposes of storage, disposal or improved oil recovery is the exact spatial distribution of the gas volumes in the subsurface. In principle this requirement is addressed by the use of 4D seismic data, although it is recognized that the seismic response still largely provides a qualitative estimate of moved subsurface fluids. Exact quantitative evaluation of fluid distributions and associated saturations remains a challenge to be solved. Here, an attempt has been made to produce mapped quantitative estimates of the gas volume injected into a clastic reservoir. Despite good results using three accurately repeated seismic surveys, time-delay and amplitude attributes reveal fine-scale differences though large-scale agreement in the estimated fluid movement. These differences indicate disparities in the nature of the two attributes themselves, which can be explained by several possible causes. Of most impact are the effects of processing and migration, wave interference effects and noise from non-repeatability of the seismic surveys. This subject highlights the need for a more careful consideration in 4D acquisition, amplitude processing and use of true amplitude preserving attributes in quantitative interpretation.

This study examines the four-dimensional (4D) seismic signatures from multiple seismic surveys shot during gas exsolution and dissolution in a producing hydrocarbon reservoir, and focuses in particular on what reservoir information may be extracted from their analysis. To aid in this process, hydrocarbon gas properties and behaviour are studied, and their relationship to the fluid-flow physics is understood using numerical simulation. This knowledge is then applied to interpret the seismic response of a turbidite field in the UK Continental Shelf (UKCS). It is concluded that for a repeat seismic survey shot 6 months or more after a pressure change above or below bubble point (as in our field case), the gas-saturation distribution during either exsolution or dissolution exists in two fixed saturation conditions defined by the critical and the maximum possible gas saturation. Awareness of this condition facilitates an interpretation of the data from our field example, which has surveys repeated at intervals of 12–24 months, to obtain an estimate of the critical gas saturation of between 0.6 and 4.0%. These low values are consistent with a range of measurements from laboratory and numerical studies in the open literature. Our critical gas-saturation estimate is also in qualitative agreement with the solution gas–oil ratios estimated in a material balance exercise using our data. It is not found possible to quantify the maximum gas saturation using the 4D seismic data alone, despite the advantage of having multiple surveys, owing to the insensitivity of the seismic amplitudes to the magnitude of this gas saturation. Assessment of the residual gas saturation left behind after secondary gas-cap contraction during the dissolution phase suggests that small values of less than a few per cent may be appropriate. The results are masked to some extent by an underlying water flood. It is believed that the methodology and approach used in this study may be readily generalized to other moderate- to high-permeability oil reservoirs, and used as input in simulation model updating.

A B S T R A C TIn this study, importance is drawn to the role of engineering principles when interpreting dynamic reservoir changes from 4D seismic data. In particular, it is found that in clastic reservoirs the principal parameters controlling mapped 4D signatures are not the pressure and saturation changes per se but these changes scaled by the corresponding thickness (or pore volume) of the reservoir volume that these effects occupy. For this reason, pressure and saturation changes cannot strictly be recovered by themselves, this being true for all data interpretation. This understanding is validated both with numerical modelling and analytic calculation. Interestingly, the study also indicates that the impact of gas saturation on the seismic can be written using a linear term but that inversion for gas saturation can yield at best only the total thickness/pore volume of the distribution. The above provides a basis for a linear equation that can readily and accurately be used to estimate pressure and saturation changes. Quantitative updates of the static and dynamic components of the simulation model can be achieved by comparing thickness or pore volume-scaled changes from the simulator with the corresponding quantities on the inverted observations.

Summary In seismic history matching, we (the authors) obtained a computer-assisted history match to conventional production data but also include the spatio-temporal information offered by time-lapse (4D) seismic to further constrain the model. Good predictive models can only be found with a suitable search of the space of uncertain parameters, such as permeability, porosity, net: gross, and fault transmissibility. We present a method of history matching that speeds up the search process. By using streamlines in place of a finite difference simulator, a factor 10 speed up in simulation can be obtained. The model accuracy is slightly diminished, affecting both the predicted well data along with saturations and pressures used to predict the 4D signal. We show how to reduce any bias effects by calibrating the model error and including it in the misfit calculation. The method has been applied to the United Kingdom Continental Shelf (UKCS) Nelson field using 6 years of production history and 2 seismic surveys. The field is maintained above bubble point and is ideal for streamline simulation. We compared the use of the finite difference simulator with the streamline method in history matching, when we changed net:gross and vertical permeability properties. By addressing the mismatch in seismic data, together with production, we improved our predictive capability. A proper parameter search increases the reliability of predictions made by using simulations and has great benefits for reservoir management. Decisions regarding water and gas handling, well maintenance, and optimization of production can be made with greater confidence and new wells can be planned with reduced risk.