Reservoir properties revisited - EBN
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Reservoir properties revisited Results of data mining in www.nlog.nl For questions contact [email protected] • Data mining exercise for publically available core plug data of the Lower Volpriehausen Sandstone Member (RBMVL) in the Netherlands from www.nlog.nl • Analysis of large data sets support generally known trends and provides excellent reference framework for more detailed reservoir property analyses. • The results of this study show the strength and bene- fit of large publicly available data sets. Porosity – Permeability trend • Large poro-perm data set has curved nature (Fig. 1 & 2). • Straight line poro-perm relaons oſten defined on lim- ited data set and result in: • Perm overesmaon in high & low poro range • Perm underesmaon in intermediate poro range • Therefore curved or bilinear funcon preferred above straight lines to describe poro-perm relaons. Porosity – Depth trend • Correcon for maximum burial depth required. • Correcon based on basin modelling study of Nelskamp & Verwey (2012). The effect is shown in Fig. 3 & 4. • Scaered data in Fig. 4 due to facies differences and diagenesis. Complicates definion of poro-depth relaon. • High porosity envelope present >>> effect of sedi - ment burial. >>> Facies and diagenesis • Two methods for definion of poro-depth trend: 1 Assign aributes for clay volume/cementaon, based on public informaon: petrography reports, core descripons etc. (Fig. 5). 2 Assign aributes for grain density, which is a good porosity indicator (Fig. 6). • Clear poro-depth trend for reservoir quality samples (Fig. 5: blue points, Fig. 6: orange & green points). Grain density (GD) analysis • Interesng: development of poro-depth relaon with increasing clay volume/diagenesis. • GD classes defined (range 2.60 – 2.75 g/cm3 , steps of 0.025 g/cm3 ) • Calculate average poro per 50m depth interval, plot vs depth. • Trend lines through each GD class (Fig. 7a) show decreasing slope with increasing GD class (Fig. 7b). • This shows that a different porosity-depth relaon should be applied for rocks with different sedimentary facies or varying amounts of early diagenesis. Example of applicability Poro-depth relaons can be used for interpolaon of well based porosity data, e.g. to create regional porosity maps. Legend Wells used Porosity [%] 0.1 - 5 5-7 7-9 9 - 11 11 - 13 13 - 15 15 - 17 17 - 19 19 - 20 20 - 22 22 - 24 24 - 26 26 - 30 30 - 34 34 - 40 Fig. 8: Porosity map of the Lower Volpriehausen Sandstone Member. Example of the applicability of poro-depth relaons. Regional porosity maps can be constructed per reservoir zone. Fig. 5: Poro-depth plot with (colour) aributes for clay volume/diagenesis based on public informaon. Fig. 3: Core plug porosity vs Present day depth. Fig. 1: Poro-perm plot, >5000 RBMVL core plug measurements. Colours display data point density. Fig. 4: Core plug porosity vs Maximum burial depth. Fig. 2: Poro-perm plot of all core plug measurements from Dutch wells (EBN, 2016). Fig. 6: Poro-depth plot, (colour) aributes for grain density. Fig. 7a: For each GD class: average porosity per 50m depth interval ploed vs depth. Fig. 7b: Slope of poro-depth relaon per GD class, as defined in Fig. 7a. North Sea Super Grp U. North Sea Grp M. North Sea Grp L. North Sea Grp Chalk Grp Rijnland Grp Niedersachsen Grp Scruff Grp Schieland Grp Altena Grp U. Germanic Trias Grp L. Germanic Trias Grp Zechstein Grp U. Rotliegend Grp L. Rotliegend Grp Limburg Grp Carboniferous Limestone Grp Farne Grp Banjaard Grp Silurian
Transcript of Reservoir properties revisited - EBN
Reservoir properties revisitedResults of data mining in www.nlog.nl
For questions contact [email protected]
• Data mining exercise for publically available core plug data of the Lower Volpriehausen Sandstone Member (RBMVL) in the Netherlands from www.nlog.nl
• Analysis of large data sets support generally known trends and provides excellent reference framework for more detailed reservoir property analyses.
• The results of this study show the strength and bene-fit of large publicly available data sets.
Porosity – Permeability trend• Large poro-perm data set has curved nature (Fig. 1 &
2).• Straight line poro-perm relations often defined on lim-
ited data set and result in:• Perm overestimation in high & low poro range• Perm underestimation in intermediate poro range
• Therefore curved or bilinear function preferred above straight lines to describe poro-perm relations.
Porosity – Depth trend• Correction for maximum burial depth required.• Correction based on basin modelling study of
Nelskamp & Verwey (2012). The effect is shown in Fig. 3 & 4.
• Scattered data in Fig. 4 due to facies differences and diagenesis. Complicates definition of poro-depth relation.
• High porosity envelope present >>> effect of sedi-ment burial.
>>>
Facies and diagenesis• Two methods for definition of poro-depth trend:
1 Assign attributes for clay volume/cementation, based on public information: petrography reports, core descriptions etc. (Fig. 5).
2 Assign attributes for grain density, which is a good porosity indicator (Fig. 6).
• Clear poro-depth trend for reservoir quality samples (Fig. 5: blue points, Fig. 6: orange & green points).
Grain density (GD) analysis• Interesting: development of poro-depth relation with
increasing clay volume/diagenesis.• GD classes defined (range 2.60 – 2.75 g/cm3, steps
of 0.025 g/cm3)• Calculate average poro per 50m depth interval, plot
vs depth.• Trend lines through each GD class (Fig. 7a) show
decreasing slope with increasing GD class (Fig. 7b).• This shows that a different porosity-depth relation
should be applied for rocks with different sedimentary facies or varying amounts of early diagenesis.
Example of applicabilityPoro-depth relations can be used for interpolation of well based porosity data, e.g. to create regional porosity maps.
LegendWells used
Porosity [%]0.1 - 5
5 - 7
7 - 9
9 - 11
11 - 13
13 - 15
15 - 17
17 - 19
19 - 20
20 - 22
22 - 24
24 - 26
26 - 30
30 - 34
34 - 40
Fig. 8: Porosity map of the Lower Volpriehausen Sandstone Member.
Example of the applicability of poro-depth relations. Regional
porosity maps can be constructed per reservoir zone.
Fig. 5: Poro-depth plot with (colour) attributes for clay volume/diagenesis
based on public information.
Fig. 3: Core plug porosity vs Present day depth.
Fig. 1: Poro-perm plot, >5000 RBMVL core plug measurements. Colours
display data point density.
Fig. 4: Core plug porosity vs Maximum burial depth.
Fig. 2: Poro-perm plot of all core plug measurements from Dutch wells
(EBN, 2016).
Fig. 6: Poro-depth plot, (colour) attributes for grain density.
Fig. 7a: For each GD class: average porosity per 50m depth interval
plotted vs depth.
Fig. 7b: Slope of poro-depth relation per GD class, as defined in Fig. 7a.
North Sea Super GrpU. North Sea GrpM. North Sea GrpL. North Sea GrpChalk GrpRijnland GrpNiedersachsen GrpScruff GrpSchieland GrpAltena GrpU. Germanic Trias GrpL. Germanic Trias GrpZechstein GrpU. Rotliegend GrpL. Rotliegend GrpLimburg GrpCarboniferous Limestone GrpFarne GrpBanjaard GrpSilurian
