Facies analysis and production classification of Frasnian age

reservoir

Investigator: Irina Knyazeva

Tyumen, 09’2011

Supervisors: Chris Elders

km

Area of interestArea of interest

Location of the area

We

st S

iber

ia

Tectonic mapTectonic map

Regional tectonic

Target Layer: Dkt – clasticUpper FrasnianLate Devonian, PaleozoicFrasnian-Tournaisian Oil&Gas complex

Chronostratigraphy

3D seismic cube3D seismic cube Core data – 7 wellsCore data – 7 wells Well log data – 27 wellsWell log data – 27 wells

Available data

Area of 3D seismic survey235 km2

Seismic interpretationSeismic interpretationCore descriptionSedimentology analysisFacies determination

Core descriptionSedimentology analysisFacies determination

Project workflow

Facies analysisFacies analysis

Palaeoenvironmen reconstructionPalaeoenvironmen reconstruction

Litho-facies differentiationLitho-facies differentiation

Macro descriptionFractional compositionCement contentMineralogical compositionPhi-K relationshipWell logs characteristics

Macro descriptionFractional compositionCement contentMineralogical compositionPhi-K relationshipWell logs characteristics

Core – Well logs tieCore – Well logs tie

3D litho-facies modeling3D litho-facies modeling

Litho-facies cubePorosity cubePermeability cubeKh map

Litho-facies cubePorosity cubePermeability cubeKh map

Output. RecommendationsOutput. Recommendations

Seismic interpretation

Well #4066Well #4066

Dkt_topDkt_top

Dkt_botDkt_bot

Fm_topFm_top

Seismic interpretation results

Bottom of reservoirBottom of reservoir

Top of reservoirTop of reservoir

Seismic interpretation results

Thickness of reservoirThickness of reservoir

Implication

Combination of these three maps shows that sedimentation rate was slower in South-East and much faster in central and North-West parts.

Core description

Structural map bottom of the reservoirStructural map bottom of the reservoir

Wells with core

#4053#4053

Facies analysis

Tid

al c

han

nel

Tid

al c

han

nel

Tid

al b

arT

idal

bar

Tid

al f

lat

Tid

al f

lat

Characteristics:- Lithology: mud, sand and less commonly conglomerate;- Cross-bedding and cross-lamination structure;- Bimodal in tidal estuaries;- Fossils content typical for shallow marine;- Fining up succession.

Tidal channel facies

Facies analysis

Tid

al c

han

nel

Tid

al c

han

nel

Tid

al b

arT

idal

bar

Tid

al f

lat

Tid

al f

lat

Tidal bar facies

Characteristics:- Lithology: from fine grained to medium grain size sand;- Sigmoidal cross-bedding associated with the tidal deltas and inlet fills;- Bidirectional current indicators.

Facies analysis

Tid

al c

han

nel

Tid

al c

han

nel

Tid

al b

arT

idal

bar

Tid

al f

lat

Tid

al f

lat

Tidal flat facies

Characteristics:- Lithology: mud and fine grain sand;- Tabular muds with thin sheets and lenses of sand;- Ripple cross-lamination and flaser/lenticular bedding;- Fossils content: shallow marine fauna and salt marsh vegetations.

Facies analysis

Up

per

sh

ore

face

Up

per

sh

ore

face

Fo

resh

ore

Fo

resh

ore

Upper shoreface facies

Characteristics:- Lithology: from fine-grained to medium grained sand;- Sedimentary structure: planar cross-bedding;- Clean good reservoir with good porosity and permeability values.

Facies analysis

Up

per

sh

ore

face

Up

per

sh

ore

face

Fo

resh

ore

Fo

resh

ore

Foreshore facies

Characteristics:- Lithology: from medium grained to very coarse grained sand;- Sedimentary structure: trough and planar cross-bedding;- Small amount of bioturbation (by Scolithos ichnofacies);- High energy deposition environment.

Ichnofauna examples

Palaeophycus.Realted to Scolithos ichnofacies. Characterized by high and low sedimentation energy foreshore. Also typical for storm affected sandstones. Can be found in brackish water

Planolites.Realted to Scolithos ichnofacies. Can be found in any type of environments: from fresh water to deep-water settings.

Chondrites.Related to Cruziana ichnofacies. Can be found in marine settings. Specific points for Chondrites ichnofacies is low oxygen conditions.

Scolithos.Usually for brackish water and marine environments. But Scolithos burrows are result from different organism livings this can be from marine to continental environments.

Asterosoma.Related to Cruziana ichnofacies. Can be found in Upper and Lower shoreface settings.

Thalassinoids.Related to Cruziana ichnofacies. Typical for brackish water environments.

Palaeoenvironment reconstruction

Sweet et al, Basic clastic facies

Mar

gin

al m

arin

e en

viro

nm

ent

Mar

gin

al m

arin

e en

viro

nm

ent

Sweetness seismic attribute

Tidal channels

Tidal bars

River

Open sea

Gary Nichols, Sedimentology and stratigraphy, lectures, 2011

Litho-facies determination

Phi, %

lgK

, mD

0 5 10 15 20

1000

100

10

1

0.1

0.01

LF2

LF1

LF3LF4

Phi, fraction

lgK

, mD

Phi-K transformPhi-K transformTNK-BP interpretation My own interpretation

LF1 < 0.0625 mm

LF2 = (0.0625 - 0.25) mm

LF3 = (0.25 - 0.5) mm

LF4 = (0.5 - 2) mm

Litho-facies determination

Litho-facies 4: lg К=8.004*lg(Phi)+9.985Litho-facies 3: lg К=7.819*lg(Phi)+9.198Litho-facies 2: lg К=5.057*lg(Phi)+5.159Litho-facies 1: lg K=3.601*lg(Phi)+2.829

Phi, %

lgK

, mD

0 5 10 15 20

1000

100

10

1

0.1

0.01

LF2

LF1

LF3LF4

Phi, fraction

lgK

, mD

Phi-K transformPhi-K transformTNK-BP interpretation My own interpretation

Litho-facies 2 overview

Cross-bedded from VFG to FG Sandstone partly

bioturbated

Cross-bedded from VFG to FG Sandstone partly

bioturbated

Core example Fractional composition Mineralogical composition

Cement content

Litho-facies properties

5,17%

77,3%

13,9%

3,63%

0

10

20

30

40

50

60

70

80

3,0-1,0 1,0-0,1 0,1-0,01 <0,01

Coarse material,

1%Feldspar,

2% Quartz, 97%

Coarse1%

Feldspar2%

Quartz88%

Sw_ir4%

Phi_ef5%

Chlorite,49%

Kaolinite2%

Mix of K&M,13%

Mica,36%

Litho-facies 3 overview

MG poor sorted quartzitic Sandstone

with some detrit

MG poor sorted quartzitic Sandstone

with some detrit

Core example Fractional composition Mineralogical composition

Cement content

Litho-facies properties

2,75%

70,43%

19,8%

7,02%

0

10

20

30

40

50

60

70

80

3,0-1,0 1,0-0,1 0,1-0,01 <0,01

Quartz, 93%

Coarse material,

2%Feldspar,

5%

Phi_ef9%

Quartz, 88%

Feldspar4%

Coarse2%

Sw_ir2%

Mix of K&M,18%

Kaolinite, 2% Chlorite,

36%

Mica, 44%

Litho-facies 4 overview

33,6%

63,2%

2,75% 0,45%

0

10

20

30

40

50

60

70

3,0-1,0 1,0-0,1 0,1-0,01 <0,01

Feldspar, 2%

Coarse material,

4%Quartz,

94%

From CG to VCG poor sorted Sandstone

with pebble size quartz, often massive structure

From CG to VCG poor sorted Sandstone

with pebble size quartz, often massive structure

Core example Fractional composition Mineralogical composition

Cement content

Litho-facies properties

Quartz84%

Feldspar1%

Coarse 3%

Sw_ir 1% Phi_ef; 11%

Mix of K&M, 23%

Kaolinite, 1%

Mica, 41%

Chlorite, 35%

Litho-facies prediction

What do we have?- 7 cored wells;- Lack of logging tools;- Poor quality well logging data;- 4 litho-facies defined base on core data;- 20 uncored wells.

ProblemLitho-facies prediction in uncored wells

SolutionStatistical technique “Fuzzy Logic”SolutionStatistical technique “Fuzzy Logic”

Donetsk anticline 35 wells

North Donetsk anticline 2 wells

Prediction results

#4053#4053#4076#4076

Core Core Prediction Prediction

Litho-facies 1 Litho-facies 2

Litho-facies 3 Litho-facies 4

StatementLitho-facies prediction using Fuzzy logic is based on assertion that a particular litho-facies type can give any log reading although some readings are more likely than others.

ResultsIn a result of prediction we get good differentiation between litho-facies and lithology prediction in uncored wells.

3D static modeling

Structural modelStructural modelDepth

3230

3260

Litho-facies cubeLitho-facies cubeCodeLF1LF2LF3LF4

Average porosity mapAverage porosity mapPorosity

0.13

0.6

Average permeability mapAverage permeability mapPermeability

1

100

3D modeling results

Output from static modeling is conductivity map kh (permeability*thickness). This map is useful to define and prove most attractive spots with highest oil rate. Kh map allows to eliminate potential productive zones and localize remaining reserves.

Prospective drilling zonesProspective drilling zonesK*h

8000

0

Conclusion

Marginal marine environment – tide dominated estuary;

5 facies and 4 petrophysical litho-facies within were defined and predicted in uncored wells using fuzzy logic technique;

Tight integration of seismic, core and well log data is realized in 3D static model that is more predictive and have lower degree of uncertainty associated with them;

Output result from static modeling is conductivity map. This map is useful to define and prove most attractive spots with highest oil potential.

Thank you for attention!

http://2.bp.blogspot.com/_Bz97zTlEL6U/TPhI9rk8aBI/AAAAAAAABuc/dZvl28QthbU/s1600/P1020294_Estuary.JPG