Sub-Garn Sands Blog : Part 6 – Data Integration & Reporting

Pulling out trends and relationships in our collected data

The trends and relationships between well location, stratigraphic sequence, depositional setting, diagenesis and burial depth, as a complex interplay of controls upon reservoir quality became evident as our analytical datasets were integrated and visualised as maps and charts.

We elected to map the range, and relative proportions of sedimentary facies observed within each well from cores studied at the NPD, as bubble plots drafted in Interactive Correlations (IC) software, across the 3 biostratigraphically-define timeslices.

We decided against generating time-contemporaneous reservoir polygons to illustrate sand distribution or facies between wells, as over such a vast area without seismic calibration, and given that each core section likely only represents partial records of multiple progradational events – this was considered potentially misleading. The occurrence and abundance of diagenetic cements from our petrographic modal point counts and grain size and sorting datasets, were also mapped, focusing on those responsible for either the retention or destruction of primary porosity. These included for example, pore-lining chlorite and syntaxial quartz overgrowths. Cross referencing these new facies assignments and petrographic datasets against released conventional core-analysis (CCA) data allowed us to test whether general trends in the reduction of porosity with increasing depth were positively or negatively offset across our study area by variations in grain size, facies or diagenesis.

We generated a series of reservoir quality cross-plots, applying our facies assignments to the >8,500 CCA plugs with helium porosity and >7,400 CCA plugs with uncorrected gas permeability (Kg), that fell within our core-database of >2,700m. This enables us, for example to observe the dominant facies associated with the best reservoir quality in a specific area (e.g., NCS Quad 6507), or to assess the relative importance of facies by plotting permeability against grain size and ductile content. For example, do the generally coarser distributary, delta-top and marine shoreline, Gross Depositional Environments (GDE’s) always coincide with the best reservoir properties?

Extending our understanding on Jurassic reservoir quality controls for Mid-Norway, as established in the Garn multiclient, a focus again here was to explore whether chlorite cements, which can either help preserve primary porosity if continuously pore-lining or reduce porosity if pore filling – were more prevalent in a specific wells or areas and/or coincident with specific depositional setting. If the former, this may indicate a provenance control on chlorite presence, perhaps resulting from the local formation of iron-rich precursor clays such as berthierine or odinite that may be derived from iron-rich hinterlands, such as micaceous biotite schists. With this new dataset, the project team were able to reconsider publications that propose a westerly derived source of these sands from the Grip High and Sklinna Ridge basement uplifts. The precursor clays associated with chlorite cements are generally believed to be formed in mixed-salinity settings, while sub-macroscopic bioturbation has also been proposed as a key influence hence there may be multiple factors coinciding to create this optimum environment.

It is also important to consider that burial of sands results in the decay and dissolution of detrital feldspar grains (silica and potassium ions become liberated at >2.5km depth), helping generate authigenic cements such as quartz, that can occlude pores. While being mindful that the mineralogical composition of these samples has significantly altered from its depositional state by diagenetic decay and dissolution, Quartz, Feldspar, Lithics (QFL) plots proved useful to document the composition of these samples, along with diagenetic cement plots and CCA data. The abundance of some minerals appears not to follow a general trend of increasing dissolution with depth, and these happen to coincide with high concentrations of chlorite. It’s therefore possible, that this reflects a common provenance/compositional control. To further investigate the context for chlorite presence as an aid to help licensees of this report predict its presence elsewhere, we were supported by our colleagues at Rocktype Limited who undertook chlorite polytyping for a subset of our samples using QEMSCAN.

For more information on our findings, please get in touch.