Abstract
Abstract Tertiary injectites, which are re-mobilized sandstones, represent commercially attractive targets for near-field, long-reach tie-backs to existing field infrastructure above and adjacent to producing reservoirs. Injectites exhibit exceptional porosity–permeability and productivity, such that discoveries can add incremental reserves and lift production decline in mature fields. Abundant injectites are visible on seismic data in the Tertiary of the Viking Graben, but, as some disappointing wells have established, not all are hydrocarbon-charged. The challenge is to reliably distinguish hydrocarbon-filled high porosity–permeability features from tight or dry reservoirs in a cost-effective way. Regional rock physics analysis of injectite reservoirs, using well data from fields in Norway and the UK, reveals that a combination of elastic attributes can effectively discriminate lithology and hydrocarbon presences in these reservoirs. After pre-stack conditioning, broadband seismic data correlate reliably with wells, giving confidence that pre-stack seismic is faithfully imaging the elastic properties of the subsurface in lower Tertiary target intervals. Informed by rock physics analysis, a combination of broadband seismic elastic attributes is used to predict sand presence and de-risk hydrocarbon presence in reservoirs v. water-wet targets. Hydrocarbon sand distribution predicted from relative acoustic impedance and V P / V S matches to known accumulations and identifies remaining near-field opportunities.
Highlights
This paper introduces sand injectites, their petroleum potential and their characteristics in terms of rock physical properties and elastic properties that can be derived using seismic reservoir characterization
This paper describes a quantitative interpretation (QI) workflow deployed to identify, characterize and de-risk injectites opportunities by integrating highquality pre-stack broadband data with rock physics analysis from well data from fields in the UK and Norway
Acquired multi-sensor broadband seismic pre-stack migrated data significantly improve the imaging of the Tertiary injectite reservoirs of the North Sea
Summary
The workflow for ‘sparse-spike’ seismic absolute pre-stack inversion inverts simultaneously for acoustic and shear impedances using angle stacks, wavelets calculated for each angle stack and lowfrequency models. The algorithm uses Aki–Richards equations as a convolutional model and solves a constrained, non-linear optimization at every trace by matching seismic data to quantify the absolute elastic rock properties that results in the observed AVA (amplitude variation with angle) present in the input data. Long wavelets of at least 300 ms are required to capture the low-frequency– long-wavelength component of the broadband seismic data These LFMs are required for the inversion in order to correctly scale acoustic impedance (Ip) v. Once the background trends are understood and the elastic attributes scaled, relative products are generated This is done in order to remove the uncertainties linked to the simple assumptions of the LFMs which impact the absolute values of the resultant absolute elastic attributes produced
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