ALBERT

Description: Using the data from over 8000 wells augmented by seismic and thermal response information, a comparison of McMurray Formation (Cretaceous) and Grosmont C member (Devonian) thermal recovery reservoirs of northeastern Alberta is provided along with a discussion of reservoir performance to date. Fluvial-estuarine McMurray Formation reservoirs perform best where bitumen-charged homogeneous lenticular sandstones at least 20 metres thick are found. These deposits are relatively rare as the formation is characterized by endemic heterogeneity mainly in the form of inclined heterolithic stratification (IHS). Most of the best McMurray steam-assisted gravity drainage (SAGD) reservoirs appear to be currently on-line and produce approximately 113 000 m 3 /day of bitumen from fourteen projects. Platform carbonate Grosmont C successions are blanket deposits 32–35 metres thick, with bitumen columns typically 15–24 metres thick, and are characterized by consistent reservoir properties facilitated by pervasive multi-scale fracturing. Although no reserves have yet to be assigned to Alberta’s bitumen-bearing carbonates by the province, recent pilot results derived from cyclic steam stimulation (CSS) operations suggest that Grosmont C reservoir performance could ultimately prove to be competitive with superior McMurray SAGD reservoirs. Under current technological and economic conditions, McMurray SAGD reservoirs appear incapable of providing the 15.9 billion m 3 of in-situ bitumen reserves (59% of Canada’s total oil reserves) ascribed to this formation by the province of Alberta as only circa 6 billion m 3 of oil-in place appears to reside within optimal reservoirs (i.e. those reservoirs at least 20 metres thick with average porosity and oil saturation values of 33% and 80%, respectively). Barring future technological breakthroughs and, or, economic improvements, future commercial development of both the Grosmont C and other carbonate reservoirs might be needed to make up for some of the potential reserve shortfall associated with McMurray Formation SAGD reservoirs.

Description: Despite geophysics is being used increasingly, it is still unclear how and when the integration of geophysical data improves the construction and predictive capability of groundwater models. Therefore, this paper presents a newly developed HYdrogeophysical TEst-Bench (HYTEB) which is a collection of geological, groundwater and geophysical modeling and inversion software wrapped to make a platform for generation and consideration of multi-modal data for objective hydrologic analysis. It is intentionally flexible to allow for simple or sophisticated treatments of geophysical responses, hydrologic processes, parameterization, and inversion approaches. It can also be used to discover potential errors that can be introduced through petrophysical models and approaches to correlating geophysical and hydrologic parameters. With HYTEB we study alternative uses of electromagnetic (EM) data for groundwater modeling in a hydrogeological environment consisting of various types of glacial deposits with typical hydraulic conductivities and electrical resistivities covering impermeable bedrock with low resistivity. It is investigated to what extent groundwater model calibration and, often more importantly, model predictions can be improved by including in the calibration process electrical resistivity estimates obtained from TEM data. In all calibration cases, the hydraulic conductivity field is highly parameterized and the estimation is stabilized by regularization. For purely hydrologic inversion (HI, only using hydrologic data) we used Tikhonov regularization combined with singular value decomposition. For joint hydrogeophysical inversion (JHI) and sequential hydrogeophysical inversion (SHI) the resistivity estimates from TEM are used together with a petrophysical relationship to formulate the regularization term. In all cases, the regularization stabilizes the inversion, but neither the HI nor the JHI objective function could be minimized uniquely. SHI or JHI with regularization based on the use of TEM data produced estimated hydraulic conductivity fields that bear more resemblance to the reference fields than when using HI with Tikhonov regularization. However, for the studied system the resistivities estimated by SHI or JHI must be used with caution as estimators of hydraulic conductivity or as regularization means for subsequent hydrological inversion. Much of the lack of value of the geophysical data arises from a mistaken faith in the power of the petrophysical model in combination with geophysical data of low sensitivity, thereby propagating geophysical estimation errors into the hydrologic model parameters. With respect to reducing model prediction error, it depends on the type of prediction whether it has value to include geophysical data in the model calibration. It is found that all calibrated models are good predictors of hydraulic head. When the stress situation is changed from that of the hydrologic calibration data, then all models make biased predictions of head change. All calibrated models turn out to be a very poor predictor of the pumping well's recharge area and groundwater age. The reason for this is that distributed recharge is parameterized as depending on estimated hydraulic conductivity of the upper model layer which tends to be underestimated. Another important insight from the HYTEB analysis is thus that either recharge should be parameterized and estimated in a different way, or other types of data should be added to better constrain the recharge estimates.