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FWS 2005 L12 – Data AnalysisCourtesy of ExxonMobil Lecture 12 0 Ma68 Ma60 Ma48 Ma38 Ma29 Ma18 Ma10 Ma Burial History Slope Non- Marine Near- shore Coastal.

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Presentation on theme: "FWS 2005 L12 – Data AnalysisCourtesy of ExxonMobil Lecture 12 0 Ma68 Ma60 Ma48 Ma38 Ma29 Ma18 Ma10 Ma Burial History Slope Non- Marine Near- shore Coastal."— Presentation transcript:

1 FWS 2005 L12 – Data AnalysisCourtesy of ExxonMobil Lecture 12 0 Ma68 Ma60 Ma48 Ma38 Ma29 Ma18 Ma10 Ma Burial History Slope Non- Marine Near- shore Coastal Plain Sand Fairway Basin A A Synclinal Spill Point Low Map View Cross-Section View Trap Analysis Synclinal Spill Point Controls HC Level

2 FWS 2005 L12 – Data AnalysisCourtesy of ExxonMobil Objectives & Relevance Relevance: Demonstrate some of the scientific methods we use to determine where to drill Objective: Introduce some types of analyses that are used to mature a lead into a prospect once the geologic framework is established

3 FWS 2005 L12 – Data AnalysisCourtesy of ExxonMobil Overview of Data Analysis Once the geologic framework is complete, we can: Analyze present-day conditions Where are potential traps? How much might the trap hold (volume)? What are the key uncertainties & risks? Look for geophysical support DHI and AVO analysis Model basin fill When/where have HCs been generated? How have rock properties changed with time?

4 FWS 2005 L12 – Data AnalysisCourtesy of ExxonMobil Outline 1.Time-to-Depth Conversion 2.Identify Sand Fairways 3.Identify Traps 4.Geophysical Evidence –Direct HC Indicators (DHIs) –Amplitude versus Offset (AVO) 5.Basin Modeling –Back-strip stratigraphy (geohistory) –Forward model (simulation)

5 FWS 2005 L12 – Data AnalysisCourtesy of ExxonMobil 1. Time-to-Depth Conversion Horizons & Faults in units of 2-way time (milliseconds) Horizons & Faults in units of depth (meters or feet) Well Data calibration Velocity Data derived from seismic processing Time-to-Depth Conversion

6 FWS 2005 L12 – Data AnalysisCourtesy of ExxonMobil 1.Time-to-Depth Conversion 2.Identify Sand Fairways 3.Identify Traps 4.Geophysical Evidence –Direct HC Indicators (DHIs) –Amplitude versus Offset (AVO) 5.Basin Modeling –Back-strip stratigraphy (geohistory) –Forward model (simulation) Outline

7 FWS 2005 L12 – Data AnalysisCourtesy of ExxonMobil 2. Identify Sand Fairways Reflection Geometries ABC codes EODs environments of deposition Well Data calibration Interval Attributes Seismic Attribute Maps Sand Fairways For key seismic sequences, namely potential reservoir intervals

8 FWS 2005 L12 – Data AnalysisCourtesy of ExxonMobil Example: Nearshore Sands Basin Slope Non- Marine Near- shore Coastal Plain Coastal PlainNearshoreSlope Basin

9 FWS 2005 L12 – Data AnalysisCourtesy of ExxonMobil Outline 1.Time-to-Depth Conversion 2.Identify Sand Fairways 3.Identify Traps 4.Geophysical Evidence –Direct HC Indicators (DHIs) –Amplitude versus Offset (AVO) 5.Basin Modeling –Back-strip stratigraphy (geohistory) –Forward model (simulation)

10 FWS 2005 L12 – Data AnalysisCourtesy of ExxonMobil 3. Identify Traps Use depth (or time) structure maps, with fault zones, to look for places where significant accumulations of HC might be trapped: Structural traps –e.g., anticlines, high-side fault blocks, low-side roll-overs Stratigraphic traps –e.g., sub-unconformity traps, sand pinch-outs Combination traps (structure + stratigraphy) –e.g., deep-water channel crossing an anticline

11 FWS 2005 L12 – Data AnalysisCourtesy of ExxonMobil Structural Traps – A Simple Anticline A A Synclinal Spill Point Controls HC Level Synclinal Spill Point Low If HC charge is great HCs migrate to anticline Traps progressively fills down When HCs reaching the trap is greater, the trap is filled to a leak point Here there is a synclinal leak point on the east side of the trap AA

12 FWS 2005 L12 – Data AnalysisCourtesy of ExxonMobil Structural Traps – A Simple Anticline A A Synclinal Spill Point Low HC Migrating to Trap Controls HC Level HCs migrate to anticline Traps progressively fills down When HCs reaching the trap is small, the trap is under-filled – it could hold more Here the trap is charge-limited and is not filled to the synclinal leak point If HC charge is limited AA Only enough oil has reached the trap to fill it to this level

13 FWS 2005 L12 – Data AnalysisCourtesy of ExxonMobil Structural Traps – A Roll-Over Anticline Leak at Fault Controls HC Level Synclinal Leak Point Controls HC Level Faulted Anticline – Fault LeaksFaulted Anticline – Fault Seals A A A A AAAA Leak Point

14 FWS 2005 L12 – Data AnalysisCourtesy of ExxonMobil Stratigraphic Traps – Sub-Unconformity & Reef A A Upper Sand Lower Sand B B Upper Sand Lower Sand BBAA

15 FWS 2005 L12 – Data AnalysisCourtesy of ExxonMobil Combo Traps – Channel over an Anticline A A A A Channel Axis Channel Margin Shale StructureStratigraphy Low High A A Structure + Stratigraphy OIL Water Cross Section AA

16 FWS 2005 L12 – Data AnalysisCourtesy of ExxonMobil Outline 1.Time-to-Depth Conversion 2.Identify Sand Fairways 3.Identify Traps 4.Geophysical Evidence –Direct HC Indicators (DHIs) –Amplitude versus Offset (AVO) 5.Basin Modeling –Back-strip stratigraphy (geohistory) –Forward model (simulation)

17 FWS 2005 L12 – Data AnalysisCourtesy of ExxonMobil What Are DHIs? Seismic DHIs are anomalous seismic responses related to the presence of hydrocarbons Acoustic impedance of a porous rock decreases as hydrocarbon replaces brine in pore spaces of the rock, causing a seismic anomaly (DHI) There are a number of DHI signatures; we will look at a few common ones: – Amplitude anomaly – Fluid contact reflection – Fit to structural contours DHI = Direct Hydrocarbon Indicator

18 FWS 2005 L12 – Data AnalysisCourtesy of ExxonMobil In general: Oil sands are lower impedance than water sands and shales Gas sands are lower impedance than oil sands The difference in the impedance tends to decrease with depth The larger the impedance difference between the HC sand and its encasing shale, the greater the anomaly IMPEDANCE x 10 3 DEPTH x 10 3 FEET GASSAND OILSAND WATER SAND SHALE Data for Gulf Of Mexico Clastics Looking for shallow gas Looking for deep oil Typical Impedance Depth Trends

19 FWS 2005 L12 – Data AnalysisCourtesy of ExxonMobil DHIs: Amplitude Anomalies High AmplitudeLow Change in amplitude along the reflector Anomalous amplitudes

20 FWS 2005 L12 – Data AnalysisCourtesy of ExxonMobil DHIs: Fluid Contacts Hydrocarbons are lighter than water and tend to form flat events at the gas/oil contact and the oil/water contact. Thicker Reservoir Fluid contact event Fluid contact event Thinner Reservoir

21 FWS 2005 L12 – Data AnalysisCourtesy of ExxonMobil DHIs: Fit to Structure depth Since hydrocarbons are lighter than water, the fluid contacts and associated anomalous seismic events are generally flat in depth and therefore conform to structure, i.e., mimic a contour line

22 FWS 2005 L12 – Data AnalysisCourtesy of ExxonMobil What is AVO? We can take seismic data and process it to include all offsets (full stack) or select offsets (partial stacks) For HC analysis, we often get a near-angle stack and a far-angle stack The difference in amplitude for a target interval on near vs. far stacks can indicate the type of fluid within the pore space of the rock AVO analysis examines such amplitude differences AVO = Amplitude vs. Offset

23 FWS 2005 L12 – Data AnalysisCourtesy of ExxonMobil Some Additional Geophysics Energy Source Seismic reflections are generated at acoustic boundaries The amplitude of a seismic reflection is a function of: velocities above & below an interface densities above & below an interface θ - the angle of incidence of the seismic energy Layer N Layer N +1 Receiver θθ } Change in Impedance

24 FWS 2005 L12 – Data AnalysisCourtesy of ExxonMobil Why Do We Care? Reflection amplitude varies with θ as a function of the physical properties above and below the interface Rock / lithologic propertiesRock / lithologic properties Properties of the fluids in the poresProperties of the fluids in the pores Examining variations in amplitude with angle (or offset) may help us unravel lithology and fluid effects, especially at the top of a reservoir Zero Offset Near Offset Full Offset Far Offset Top of Reservoir Base of Reservoir Impedance Lo Hi

25 FWS 2005 L12 – Data AnalysisCourtesy of ExxonMobil AVO Crossplot AVO Intercept (A) AVO Gradient (B) Gas AVO: Quantified with 2 Parameters We quantify the AVO response in terms of two parameters: Intercept (A) - where the curve intersects 0º Slope (B) - a linear fit to the AVO data CDP Gather: HC Leg Time Angle/Offset AVO Curve Amplitude Angle/Offset Negative Intercept Negative Slope Oil Water For some reservoirs, the AVO response differs when gas, oil and water fill the pore space

26 FWS 2005 L12 – Data AnalysisCourtesy of ExxonMobil Seismic Example Fluid Contact? Oil over Water? Fluid Contact? Gas over Oil? Alpha

27 FWS 2005 L12 – Data AnalysisCourtesy of ExxonMobil Analyzing Present-Day Conditions From present-day configurations, we can: Predict where Sand Fairways & Source Intervals Predict EODs and infer lithologies Evaluate the Trap Configuration Identify and Size Potential Traps Consider spill / leak points Consider if a Sealing Unit Exists Can shales provide top & lateral seal? Identify where a distinct HC response occurs DHI and AVO analysis Model a simple HC Migration Case Use present-day dips on stratal units Assume buoyancy-driven migration

28 FWS 2005 L12 – Data AnalysisCourtesy of ExxonMobil We Would Like to Know More We need to incorporate the element of time: When did the traps form? When did the source rocks generate HCs? What was the attitude (dip) of the strata when the HCs were migrating? What is the quality of the reservoir (Φ, k) How adequate is the seal? How have temperature and pressure conditions changed through time? To answer these questions, we have to model the basins history from the time of deposition to the present

29 FWS 2005 L12 – Data AnalysisCourtesy of ExxonMobil 1.Time-to-Depth Conversion 2.Identify Sand Fairways 3.Identify Traps 4.Geophysical Evidence –Direct HC Indicators (DHIs) –Amplitude versus Offset (AVO) 5.Basin Modeling –Back-strip stratigraphy (geohistory) –Forward model (simulation) Outline

30 FWS 2005 L12 – Data AnalysisCourtesy of ExxonMobil Basin Modeling 0 Ma 18 Ma 29 Ma 36 Ma 42 Ma Back-strip the Present-day Strata to Unravel the Basins History Time Steps are Limited to Mapped Horizons Model Rock & Fluid Properties Forward through Time Time Steps are Regular Intervals as Defined by the User

31 FWS 2005 L12 – Data AnalysisCourtesy of ExxonMobil Basin Modeling We start with the present-day stratigraphy Then we back-strip the interpreted sequences to get information of basin formation and fill For some basins, we can deduce a heat flow history from the subsidence history (exercise) Next we model basin fill forward through time at a uniform time step (typically ½ or 1 Ma) If we have well data, we check our model –Temperature data –Organic maturity (vitrinite reflectance) –Porosity Given a calibrated basin model, we predict –HC generation from source intervals –Reservoir porosity

32 FWS 2005 L12 – Data AnalysisCourtesy of ExxonMobil Simple Model of HC Migration Traps with unlimited charge Migration Path Of Spilled Oil Spillage of Excess Gas Gas separator Source Generating HCs Generate oil and gas at lower left HCs percolate into porous interval (white) Trap A fills with oil and gas – gas displaces oil Trap B fills with spilled oil and gas Seal at B will only hold a certain thickness of gas At trap B – gas leaks while oil spills Trap A Trap C Trap B

33 FWS 2005 L12 – Data AnalysisCourtesy of ExxonMobil Intro to Exercise Goal: To map the extent of the A1 gas-filled reservoir Figure 1 Inline 840 A1 Gas Sand WE

34 FWS 2005 L12 – Data AnalysisCourtesy of ExxonMobil Inline 840 Changes in Amplitude Indicate Fluid Figure 1 Gas Sand Water Sand Traces are clipped

35 FWS 2005 L12 – Data AnalysisCourtesy of ExxonMobil Fluids within the A1 Sand Inline 840 Figure 1 Extent of Gas


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