Opuwari et al_LASUFOC_2017

Slides:



Advertisements
Similar presentations
Interactive Petrophysics What’s New IP3.4
Advertisements

Electrical resistivity measurements and their uses in marine soils.
Title Petrophysical Analysis of Fluid Substitution in Gas Bearing Reservoirs to Define Velocity Profiles – Application of Gassmann and Krief Models Digital.
Geological and Petrophysical Analysis Of Reservoir Cores
Lesson 20 Abnormal Pressure
LABORATORY DETERMINATION OF POROSITY
Tim Armitage.  Shale Gas Reservoir's  The problems with Shale Reservoirs  What is needed to Create a usable model  Possible solutions to Porosity.
Deep Gas Reservoir Play, Central and Eastern Gulf
Formation Evaluation (Lecture) Subsurface Methods 4233
Basic well Logging Analysis – Log Interpretation
Pioneer Natural Resources
Rock & Fluid Properties Dr. Eissa Mohamed Shokir
Unconventional Petrophysical Analysis in Unconventional Reservoirs
Electrical Properties
Some basic Log interpretation
Ron Cherry, Maged Fam and Emiliano López
Reservoir Characterization Capstone Project Semester 1 PNG 490 – Team 26 April 29 th 2014.
Go and look behind the Ranges – Something lost behind the Ranges.
Sediment Properties Determined through Magnetotellurics
GL4 E1 KI 2c Sedimentary rocks exhibit differences in texture: –Grain angularity –Sphericity –Size –Sorting Which reflect: –Derivation (original rocks)
RESERVOIR PETROPHYSICS
Improved Permeability Measurement using T 2 Bin-Distribution and Bulk Volume Irreducible from Nuclear Magnetic Resonance Tools Case Study: Granite Wash,
Well Log Interpretation Basic Relationships
Fluid Saturation Introduction
1 SPE Distinguished Lecturer Program Primary funding is provided by The SPE Foundation through member donations and a contribution from Offshore Europe.
POROSITY DETERMINATION
Rock & Fluid Properties
Guney Formation Oil Reservoir Rock Characterization, Eregli- Ulukisla Basin Ayfer ÖZDEMİR.
Electrical Properties
CO 2 storage capacity estimates for South Africa: The uncertainties and way forward J.H.A. Viljoen, M. Cloete, F.D.J. Stapelberg and N. Hicks.
Uncertainty in AVO: How can we measure it? Dan Hampson, Brian Russell
Seismic Data Driven Reservoir Analysis FORT CHADBOURNE 3-D Coke and Runnels Counties, TX ODOM LIME AND GRAY SAND.
Thesis Topic An Integrated Petrophysical Study Using Well Logging Data for Evaluation of a Gas Field in The Gulf of Thailand Committee member : Dr. Pham.
Well Log Interpretations of Miscellaneous Oklahoma Reservoirs By Richard Andrews March 2009.
The Tools of Subsurface Analysis
Joel Ben-Awuah. Questions to Answer What do you understand about pseudo-well? When to apply pseudo-well? What are the uncertainties in reservoir modeling?
Stanford Center for Reservoir Forecasting The Stanford VI-E Reservoir: A Synthetic Data Set for Joint Seismic-EM Time- lapse Monitoring Algorithms Jaehoon.
University of the Western Cape Department of Earth Sciences Bellville, South Africa. Acknowledgements: Chris Samakinde would like to thank Inkaba yeAfrica,
Study of the Niobrara Formation in the Borie Field Abdulaziz Muhanna Alhubil, Gabrijel Grubac, Joe Lawson, Rachael Molyneux & David Scadden.
Logo here… Assessments of the Effects of Clay Diagenesis on some Petrophysical Properties of lower Cretaceous Sandstones, Offshore Orange basin, South.
LABORATORY DETERMINATION OF POROSITY
Capillary Pressure and Saturation History Capillary Pressure in Reservoir Rock .
University of Kerala, India.
Logo here… PORE PRESSURE PREDICTION OF SOME SELECTED WELLS; INSIGHT FROM THE SOUTHERN PLETMOS BASIN, OFFSHORE SOUTH AFRICA. Oluwatoyin Ayodele, Mimonitu.
Petrophysical evaluation of the Rotliegend in K15-FB-107
Petroleum Geochemistry using Wireline Logs “LogGeoChem”
Hasan Nourdeen Martin Blunt 10 Jan 2017
What is Well Logging?
Combining statistical rock physics and sedimentology to reduce uncertainty in seismic reservoir characterization Per Åge Avseth Norsk Hydro Research Centre.
5. WEIGHT VOLUME RELATIONSHIPS
Lecture items * Theory of measurement of other resistivity logs.
Establishing Patterns Correlation from Time Lapse Seismic
Well Logging Gly 326.
Petrophysical evaluation of Rotliegend Formation in K15-FA-104A
An Overview of the Unconventional Petroleum Potential of the Karoo Basins, Onshore South Africa By Sean Bevin Johnson.
PETROPHYSICS: ROCK/LOG/SEISMIC CALIBRATION
Fluid Saturations Introduction
PERMEABILITY . Some slides in this section are from NExT PERF Short Course Notes, Some slides appear to have been obtained from unknown primary sources.
RESERVOIR PETROPHYSICS
A Geologic Model 1m 75 m Perm 250 mD Sand Shale 0.1 mD 50 m Slide 16
PERMEABILITY . Some slides in this section are from NExT PERF Short Course Notes, Some slides appear to have been obtained from unknown primary sources.
Electrical Properties
Capillary Pressure and Saturation History Capillary Pressure in Reservoir Rock .
RESERVOIR PETROPHYSICS
POROSITY DETERMINATION FROM LOGS Most slides in this section are modified primarily from NExT PERF Short Course Notes, However, many of the NExT.
Electrical Properties
Upscaling Petrophysical Properties to the Seismic Scale
Capillary Pressure and Saturation History Capillary Pressure in Reservoir Rock .
Capillary Pressure: Reservoir Seal Capillary Pressure / Saturation Relationship (Sw* Model) .
QUANTITATIVE RESERVOIR CHARACTERIZATION USING ROCK PHYSICS, SEISMIC AND GEOLOGICAL CONSTRAINTS – EXAMPLES FROM SEMLIKI BASIN IN ALBERTINE GRABEN By Nakajigo.
Presentation transcript:

Opuwari et al_LASUFOC_2017 Petrophysical evaluation of Selected wells in the Upper Shallow Marine Reservoirs of the Eastern Bredasdorp basin, South Africa By Mimonitu Opuwari 1,Roxzanne Prinsloo1,Abuh Momoh2,Ono Daniel 3 But what happens after you graduate? How does AAPG fufill it’s self described mission of becoming essential throughout your geoscience career? Opuwari et al_LASUFOC_2017 Geoscience Seminar_ Namibia 2017

Opuwari et al_LASUFOC_2017 Outline Introduction Key Research Questions Materials & Methods Results & Discussions Concluding remarks Opuwari et al_LASUFOC_2017

Key Research questions We are ultimately trying to answer two questions? Opuwari et al_LASUFOC_2017

Key Research questions……. What is best approach to Analysis and Quantification of Sandstone Reservoir properties for fluid volumes? Opuwari et al_LASUFOC_2017

Opuwari et al_LASUFOC_2017 Introduction Petrophysical properties are the parameters that determine pore systems of potential reservoirs (Selley, 1985). These parameters includes: Percentage of shale volume Porosity Permeability Water saturation Thickness and extent of reservoir formation and depositional environment. Opuwari et al_LASUFOC_2017

Opuwari et al_LASUFOC_2017 Introduction……….. South Africa is rich in natural resources and coal generates about 90% of the country’s electricity. Although coal is in abundance in South Africa, other means of generating electricity is being explored (Petroleum Agency SA, 2010). South Africa has a number of Offshore sedimentary basins, the search for hydrocarbons in the Bredasdorp Basin, south of South Africa remains an area of interest. Opuwari et al_LASUFOC_2017

Opuwari et al_LASUFOC_2017 Study area The basin has an aerial extent of roughly 18 000 km2 and begins off the southeast of Cape Town and stretches up the south-east coast, up until west-south-west of Port Elizabeth (Wood, 1995). Opuwari et al_LASUFOC_2017 (Petroleum Agency of South Africa,2010.

Opuwari et al_LASUFOC_2017 Well Location Opuwari et al_LASUFOC_2017

Chronostratigraphic Sequence (Petroleum Agency of South Africa,2010. Opuwari et al_LASUFOC_2017

Opuwari et al_LASUFOC_2017 Materials and Methods Opuwari et al_LASUFOC_2017

Evaluation flow chart (stage I) Opuwari et al_LASUFOC_2017

Evaluation flow chart (stage II) Opuwari et al_LASUFOC_2017

Opuwari et al_LASUFOC_2017 Results & Discussions Opuwari et al_LASUFOC_2017

Opuwari et al_LASUFOC_2017 Identification of USM Reservoirs F-O3 F-O1 F-O2 Opuwari et al_LASUFOC_2017

LITHOFACIES CLASSIFICATIONS A. Sandstone, medium grained, well sorted. Good B. Sandstone fine to very fine grained, moderate sorting Fair C. Very fine grained siltstone,light to medium grey, lamination Poor D. Claystone, laminated, minor bioturbation, poorly sorted. Non Reservoir Opuwari et al_LASUFOC_2017

Opuwari et al_LASUFOC_2017 Calibration of Log & Core Cluster Analysis was used to determine different lithofacies in our wells After multiple cluster combinations were run, it was apparent that 4 clusters best represent our data. Opuwari et al_LASUFOC_2017

Opuwari et al_LASUFOC_2017 FACIES A FACIES B FACIES C FACIES D With collaboration with the lithofacies, clusters were classified as FACIES A-D. Opuwari et al_LASUFOC_2017

Opuwari et al_LASUFOC_2017 Clay Volume (VCL) The following GR min. and max. parameters were applied : Well GRmin api GRmax F-O1 17.4 128.1 F-O2 21.8 132.5 F-O3 24.0 137.0 Opuwari et al_LASUFOC_2017

Opuwari et al_LASUFOC_2017 Porosity (PHI) Effective porosity was computed from the density log using the following standard equation: where: ρma - matrix density, 2.67 g/cc from histogram of core grain densities ρlog - bulk formation density from density log – g/cc ρcly - clay density, 2.65 g/cc, selected from examination of reservoir shale ρfl - pore fluid density, 0.86 g/cc, derived from cross plot of compaction corrected core porosities vs log density. Vcl - final estimated clay volume Opuwari et al_LASUFOC_2017

Opuwari et al_LASUFOC_2017 Water Saturation (SW) Water saturations were computed using the Indonesia equation: where: Φ - effective porosity – v/v a - pore geometry constant, 1.0 m - cementation factor, 2.06, from SCAL data in F-O2 n - saturation exponent, 1.81, from F-O2 SCAL data Rt - True formation resistivity Rcl - clay resistivity, 7 ohmm, from resistivity responses in shales Rw - formation water resistivity, 0.08 ohmm at reservoir temperature, 18,000 ppm NaCl equivalent salinity. Opuwari et al_LASUFOC_2017

Opuwari et al_LASUFOC_2017 Permeability (PERM) Ambient permeability predictions were derived using well based functions relating ambient core permeability to compaction corrected core porosities. A subsequent correction to in-situ conditions was applied based on overburden data: Well F-O1: kha,amb =10((-0.0847)/0.0228) Well F-O2: kha amb =10((-0.1117)/0.0248) Well F-O3: kha,amb =10((-0.0964)/0.0260) Opuwari et al_LASUFOC_2017

Flow Zone Indicator (FZI) Proposed originally by Amaefule 1993 it is a derivative of his Rock Quality Index (RQI) and Normalised Porosity (NPI) where: (where K is Permeability – mD, Φe is Effective Porosity– fractions, RQI & FZI - microns) Opuwari et al_LASUFOC_2017

Opuwari et al_LASUFOC_2017 Results of FZI Hydraulic Unit FZI (microns) RQI (microns) NPI (v/v) Ave. Permeability (mD) 1 1.25 – 2.5 0.38 0.03 – 0.267 5.4 2 0.5 – 1.25 0.08 0.10 -0.22 3.7 3 ˂ 0.5 ˂0.02 ˂0.10 ˂0.1 Opuwari et al_LASUFOC_2017

Example of Summary results Opuwari et al_LASUFOC_2017

Opuwari et al_LASUFOC_2017 Well Name Reservoir Gross (m) Net N/G Av. Phi % Av. Sw Av.Vcl Av.K mD F-O1 98.00 12.65 0.129 13.1 12.4 10 1.3 F-02 66.33 42.98 0.64 15.3 36.6 14 0.8 F-03 68.5 48.00 0.70 9.8 42.26 12.45 0.21 Opuwari et al_LASUFOC_2017

Opuwari et al_LASUFOC_2017 Well Name Average Effective KH Hydraulic Unit F-O1 1.68 2 F-02 6.57 1 F-03 4.7 3 Opuwari et al_LASUFOC_2017

Opuwari et al_LASUFOC_2017 Concluding Remarks A relationship was established between core facies and wireline log. An effective petrophysical evaluation was successfully achieved with well F-02 identified as the most productive well based on comparison of petrophysical properties. The developed model could be used as input parameter for hydrocarbon volume determination in the field. Opuwari et al_LASUFOC_2017

Opuwari et al_LASUFOC_2017 Thank you! Opuwari et al_LASUFOC_2017