shortcourse_part4

Shallow Subtidal Nearshore Grainstone

Permit: 14181 Depth: 11,238 ft

Average Porosity: 16.3%, up to 20.9%

GM Permeability: 7.6 md, up to 9.81 md

Shallow Subtidal Nearshore Grainstone

Deeper Subtidal Lime Mudstone

Permit: 13472Depth: 11532 ft

Deeper Subtidal Lime Mudstone

Subtidal Microbially-Influenced Wackestone

Permit: 14181 Depth: 11149 ft

Subtidal Microbially-Influenced Packstone


Subtidal Microbially-Influenced Packstone

Subtidal Peloidal Thrombolite Boundstone


Subtidal Peloidal Reticulate Thrombolite

Boundstone





Average Porosity: 10.8%, up to 22.2%

GM Permeability: 196 md, up to 2,834 md


Transgressive Subtidal Lime

Mudstone


Transgressive Subtidal Lime Mudstone


Transgressive Subtidal Lime Mudstone

N/S Contact

SmackoverLime

Mudstone

Norphlet Sandstone/

Breccia

Norphlet/Smackover (N/S) Contact


N/S Contact

Subsurface Observations I

Thrombolites can develop on crystalline basement rocks (thickness of 58 m and area of 6.2 km2) or on an encrusted and/or cemented sedimentary rock surface (thickness of 11 m and area of 13 km2) in inner ramp settings.

Cessation of thrombolite buildup growth is due to changes in the environment, such as the establishment of a higher energy environment or an increase in the influx of siliciclastic sediments.

Thrombolites occur in deposits of the transgressive systems tract to the lower part of the regressive systems tract.

Subsurface Observations II Grainstone reservoirs overlie thrombolite boundstone

reservoirs directly or somewhat higher in the stratigraphic section. Porosity in the boundstone reservoirs ranges from 3 to 29% and permeability ranges up to 2800 md. Porosity in the grainstone reservoirs ranges from 8 to 21% and permeability ranges up to 10 md.

Diagenesis is a critical factor in preserving, enhancing and/or creating porosity and connectivity in the grainstone and boundstone reservoirs. Boundstone reservoirs have higher quality because of the nature of the porosity and associated increased connectivity that results in higher productivity. Favorable diagenesis is facies dependent.

Subsurface Case Studies-Upper Jurassic and Lower Cretaceous

Lower Cretaceous Example

Gulf Coast Interior Salt Basins

Gulf Coast Interior Salt Basins

STRAT, Mancini and Puckett, 2005

Location Map

Aptian Shelf Margin

GCAGS, Mancini et al., 2005

LK Shelf Profile

GCAGS & MMS, Mancini et al., 2005; AAPG, Tyrrell and Scott,1987

Core Description & Wireline Log

McAlpin well

GCAGS, Mancini et al., 2005

Thrombolite with Caprinids &

Stromatoporoids

McAlpin coreDepth: 17693 ft

Peloidal Fabric & Microsparite CrystalsMcAlpin core, Depth: 17693 ft

Brecciated Wackestone in Lime Mudstone

Matrix

McAlpin core Depth: 17697 ft

Dispersed Peloidal ClustersMcAlpin core, Depth: 17697 ft

Clotted Texture of Thrombolite

McAlpin coreDepth: 17709 ft

Amalgamated Peloidal ClustersMcAlpin core, Depth: 17709 ft

Terrigenous Silt-Sized GrainsMcAlpin core, Depth: 17709 ft

Bioturbated Thrombolite

McAlpin CoreDepth: 17710 ft

Distinct Peloidal ClustersMcAlpin core, Depth: 17710 ft

Indistinct Peloid ClustersMcAlpin core, Depth: 17710 ft

MICROBIAL CARBONATE FACIES AND RESERVOIRS

Exploration Strategies (Jurassic-Cretaceous Microbialites)

Ernest A. ManciniUniversity of Alabama

Acknowledgements for Funding Support

National Energy Technology Laboratory, Office of Fossil Energy, U. S. Department of Energy

Minerals Management Service, U. S. Department of Interior

Reports at http://egrpttc.geo.ua.edu

Acknowledgements

Figures included in this presentation are from the Bulletin of the American Association of Petroleum Geologists (AAPG), Transactions of the Gulf Coast Association of Geological Societies (GCAGS), Stratigraphy (STRAT), Geological Survey of Alabama Reports (AGS), Alabama State Oil and Gas Board Reports (SOGB), US Department of Energy Reports (DOE), and US Minerals Management Service Reports (MMS). These figures are included with permission of these societies, agencies, and organizations. Information from the dissertation research of William C. Parcell and Juan Carlos Llinas is included in this presentation.

Microbial Buildup Models in GOM

Bioherms (Eastern and Central Gulf Smackover fields) vs Pinnacles (Western Gulf Cotton Valley/Haynesville fields)

Mixed Skeletal/Metazoan-Microbial Buildups (Walker Creek Field/Central Gulf) vs Microbial Dominated Buildups (Eastern Gulf fields)

Microbial Buildups on Crystalline Paleohighs (Appleton Field Complex) vs Microbial Buildups on Encrusted and Cemented Stratigraphic Surfaces (Little Cedar Creek Field)

Microbial Buildups on Submergent Paleohighs (Appleton Field) vs Emergent Paleohighs (Vocation Field)

Bioherms and Pinnacles

Geometry of Microbial Buildups

Seismic Expression of Bioherm

Seismic Expression of Pinnacle Jabaloyas Microbial Pinnacle, Spain, 52 ft high

Rocha Microbial Bioherm, Portugal, 98 ft high, 0.9 sq. mi.

AAPG, Mancini et al., 2008; Llinás, 2004

30 m

Aptian Shelf Metazoan (Rudist)-Microbial & Slope Microbial

Buildups

LK Skeletal-Microbial & Microbial Buildups

GCAGS, Mancini et al., 2005; Tyrrell and Scott,1987

Shelf Rudist-Microbial

Slope Microbial

LK Rudist-Microbial Buildup-Shelf

Main Pass 253

1654-6 well

Offshore GOM

Depth: 15,610 ft

LK Microbial Buildup-Slope

McAlpin core Depth: 17,709 ft

Baffler-binder representative of firm substrate, increased background sedimentation rate, low to moderate water energy, and fluctuating environmental conditions

Amalgamated Peloidal ClustersMcAlpin core, Depth: 17,709 ft

Low & High Relief Paleohighs

Microbial Buildups Over Paleohighs

AAPG, Mancini et al., 2000

High Relief Feature

Low Relief Feature

Microbial Buildups Developed on Encrusted and Cemented

Sedimentary Substrate

Thrombolite Pinnacle BuildupsArroyo Cerezo, Spain

Pinnacle Buildup

Arroyo Cerezo, Spain

Encrusted and Cemented Surface

Arroyo Cerezo, Spain

Sequence Stratigraphy

Comparative Sequence Stratigraphy


Distribution of Thrombolite Buildups


Isopach Map –Thrombolite Boundstone Facies


Seismic Expression

Seismic Illustrating Thrombolite Buildups


Bioherm Interpreted from Seismic Data

AAPG, Mancini et al., 2008; Llinas, 2004

Pinnacle Interpreted from Seismic Data

AAPG, Mancini et al., 2008; Llinas, 2004

Diagenesis

Dendroidal Thrombolite Reservoir

Appleton Field coreDepth: 12,971 ft

Dendroidal Thrombolite

Appleton Field

Depth: 12,970 ft

Reticulate Thrombolite Reservoir

NW Appleton Field coreDepth: 13,144 ft

Reticulate Thrombolite

NW Appleton Field

Depth: 13,139 ft

Non-Reservoir LK Thrombolite Facies

McAlpin coreDepth: 17,709 ft

Amalgamated Peloidal ClustersMcAlpin core, Depth: 17,709

Observations Through the use of information resulting from the

characterization and modeling of microbial buildups and associated potential reservoir facies from outcrop and subsurface case studies, a more effective exploration strategy can be formulated for the recognition and delineation of potential microbial buildups and potential reservoir facies in the subsurface of the interior salt basins in the Gulf of Mexico.

The information resulting from this study has potential application to deposits in other rift basins characterized by tectonic and depositional histories similar to the interior basins of the Gulf of Mexico.

Microbial Carbonate Facies and Reservoirs

Part VI –Summary & Conclusions

Wayne M. AhrTexas A&M University

© Wayne Ahr 2009

Microbial Reservoir Rocks: What Have We Learned?

“Pure” microbialites [without skeletal metazoans] may form in virtually any depositional environment but they are most “at home” in restricted settings

Microbial reservoirs are fossilized deposits that have undergone diagenesis or fracturing or both

Microbialites are not detrital; consequently they are not “Dunham rocks” except as “boundstones”

Boundstone does not distinguish between different reef types and their poroperm characteristics (Embry & Klovan, 1971)

Microbial “reefs” may consist of stromatolites, thromboliltes, leiolites, cementstones, or mixed varieties

Microbialites are composed of microfabrics [“building blocks”] that may determine the geometry of the deposit and its poroperm characteristics

© Wayne Ahr 2009

Microbial Carbonate Reservoirs: Petrophysical Characteristics

Microbial reservoir rock classification Genetic classification of carbonate porosity [Ahr, 2008] Pore types in microbial reservoirs Petrophysical rock types

Lucia (1995) Winland R 35 [by facies type] Rock types based on genetic pore classification

Defining flow units in microbialites Correlating flow units at field scale

© Wayne Ahr 2009

Microbial Reservoir Rock Classification

Classifications discussed in Part II – Aitken (1967), Ahr (1971) and Kennard & James (1986) identified the fundamental macrostructures – stromatolites and thrombolites – in most fossil microbialites.

Thrombolites may have a variety of diagnostic microfabrics that indicate depositional environments

Identification of “building blocks” – peloids, filaments, mesoclots, radiaxial calcite sparites, and fossil microbes – is essential in classification of microbial reservoirs because the building blocks may determine depositional pore characteristics and growth forms of the microbial bodies.

Rock classifications: Can they be related to porosity classifications?

© Wayne Ahr 2009

Genetic Classification of Carbonate Porosity Applied to Microbial Reservoirs

Depositional templateapplicable to microbialcarbonate reservoirs

Virtually all microbialreservoir porosity is hybrid type 1 with varying degrees ofdiagenetic overprint

12

3Capacity to flow in some microbialitesmay depend on fractures, e.g., theMississippian examplesin TX & N. Dakota

© Wayne Ahr 2009

Modified Ahr Classification Emphasizing Depositional – Diagenetic Hybrid Pore Types

“Hybrid 1 A or 1 B or 1 C” Pores

After Humbolt (2008) Ahr (2008)

© Wayne Ahr 2009

Pore Types in Microbial Reservoirs

Miss. TX [top] & N. Dakota LCC, Smackover, Alabama Vocation-Appleton, Smk., Alabama

Commonly Occurring Associations of Pore Types – Vocation Appleton Fields

Common Pore Type Associations Average Sample Porosities (%) Average MPA (µm)

interparticle, intraparticle 9.65 14.9

interparticle, intraparticle, moldic 7.2 30

interparticle, cement reduced intercrystalline 4.3 1.19

reef, solution enhanced intercrystalline 20.0 12.6

reef, solution enhanced interparticle, moldic, solution enhanced intercrystalline 12.0 8.09

reef, intercrystalline, cement reduced intercrystalline4.1 8. 39

reef, solution enhanced interparticle, solution enhanced intercrystalline, moldic, vuggy 15.4 20.63

Ahr & Morgan (2003)“Reef” = Thrombolites undifferentiated; pore types not classified by Ahr (2008) system

© Wayne Ahr 2009

Petrophysical Rock Types Depend on Pore/Pore Throat Geometry

Pinch/swell ‘tubes’ typical of intergranularpore/pore throat geometry

‘Sheet’ pore/throatgeometry typical of open intercrystallinepores in dolostones

Winland (unpublished) courtesy C. Steffensen, BP

© Wayne Ahr 2009

Pore/Throat Geometry Dictates Reservoir Performance & Recovery Efficiency (RE)

Lower RE Higher RE

© Wayne Ahr 2009

Lucia’s (1995) Rock Types

Rock types based on interparticle pores [detrital rocks or purely xlln dolostones]This classification does not include biogenic [reef] rocks such as microbialites

© Wayne Ahr 2009

Winland R35 plot to define petrophysical rock types based on facies

Note that more than one facies is included in a single Winland rock type. This method does not identifypetrophysical rock types by a distinguishing characteristic that may be correlated at field scale

© Wayne Ahr 2009

Petrophysical Rock Typing, Humbolt & Ahr (2008) “Dunham-Type Rocks”

K/Φ plot by facies - core analysis data for all samples in a study of a Permian carbonate reservoir, Texas

K/Φ plot by facies – thin section samples only K/Φ plot of same data but by genetic pore type

© Wayne Ahr 2009

Petrophysical Rock Typing: Ahr/Humbolt (2008) continued

Petrophysical rock types using facies as discriminator Same MICP data but using genetic pore type as discriminatorMethod is based on K/Φ ratio and MICP measurements

© Wayne Ahr 2009

Defining Flow Units in Microbialite Reservoirs

I define flow units as reservoir intervals with sufficient porosity and permeability to produce hydrocarbons.

Flow units may be graded as good, fair, and poor based on their combined values of Φ & k and their capillary characteristics

Genetic pore types are more likely to discriminate between good-fair-poor flow units than “facies” or “fabric”

Genetic pore types are readily identified in thin sections

© Wayne Ahr 2009

How To Correlate Flow Units At Field Scale

1. Classify the genetic pore types – purely diagenetic, hybrid type 1-A (depositional attributes dominant), and hybrid type 1-B > C (diagenetic attributes dominant) – to determine which has the most influence on reservoir quality.

2. Identify the type of diagenesis – cementation, compaction, dissolution, replacement, or recrystallization – associated with the pore types in flow units, baffles, and barriers.

3. Identify the diagenetic environment or environments in which pore alteration took place, how many episodes of change took place, and in what order of occurrence the changes took place.

© Wayne Ahr 2009

5. Diagenetic porosity may correspond to present structure, paleostructure, proximity to unconformities, proximity to facies such as evaporites or lacustrine deposits, or proximity to fracture systems that were conduits for migrating fluids.

6. Purely diagenetic porosity (e.g., dolostones in which all traces of original limestone properties have been replaced) may correspond to position in stratigraphic cycles (e.g., top, middle, or bottom of the cycle) or to horizons where evaporites, ordinary dolomites, silicates and sulfides, or saddle dolomites occur together.

4. Search for evidence of paleoaquifers, exposure surfaces, stratigraphic cycles that may include evaporites, paleosols, or karst features by comparing lithological logs from cores or cuttings with subsurface geological data (structure and stratigraphy), seismic profiles and seismic attributes, biostratigraphic data, and geochemical data. If joints or fractures are part of the pore systems, fracture geometry usually occurs in predictable patterns on faults and folds.

© Wayne Ahr 2009

Conclusions Microbialites may exist in any depositional environment but not all

environments produce sufficient volume of microbial carbonate to be reservoirs, e.g., springs, lakes, travertine dams, & most methane seeps

Microbial carbonates are not detrital except in reworked deposits, therefore they are not classified as “Dunham” detrital carbonates

Porosity is not “interparticle”; therefore Lucia’s 1995 rock-typing method is not applicable

Winland R35 rock typing method is inadequate for microbialites because pore/pore throat geometry is too variable and because most Winland tests are based on “facies”

Semilog k/Φ plots based on genetic pore types identified in thin sections provides better discrimination between good, fair, poor petrophysical rock types and corresponding flow units.

The method can be used with any rock type and any pore type including fractured reservoirs.

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