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SOES6002: Modelling in Environmental and Earth System Science CSEM Lecture 5 Martin Sinha School of Ocean & Earth Science University of Southampton.

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Presentation on theme: "SOES6002: Modelling in Environmental and Earth System Science CSEM Lecture 5 Martin Sinha School of Ocean & Earth Science University of Southampton."— Presentation transcript:

1 SOES6002: Modelling in Environmental and Earth System Science CSEM Lecture 5 Martin Sinha School of Ocean & Earth Science University of Southampton

2 Recap and plan: l Yesterday: Layered models. Thin conductive layers. Frequency effects. Sea surface interaction and the ‘air wave’ l Today: The importance of geometry – end-on vs. broadside l Thin resistive layers – an important class of models

3 What controls signal propagation? l Signal propagation depends on: l The earth (resistivity) structure l Frequency l Both the above affect skin depths l But the transmitter is a dipole – l So it also depends on DIRECTION

4 Electromagnetic fields in the Earth

5 Geometry l The transmitter is a horizontal dipole l So signal propagation depends on horizontal angle with respect to dipole axis l Refer to this angle as ‘azimuth’ l Azimuth = 0 o – ‘end-on’ l Azimuth = 90 o – ‘broadside’

6 Plan view of source dipole axis and azimuth

7 Polarization Ellipse l The field can be decomposed physically into two non-interacting ‘modes’ l First corresponds to the radial component at the sea floor l Second corresponds to the azimuthal field at the sea floor

8 l These are orthogonal l Each component has an independent amplitude and phase l So when combined, they sweep out a ‘polarization ellipse’ l Broadside – no radial field l End-on – no azimuthal field

9 Polarisation ellipse parameters E E E E e e E E E E e e E E E E E E e e E E E E e e E E E E E E E E E E i i i i maj i i i i                                             min cos sin cos tan cos

10 Azimuthal dependence of CSEM response

11 Thin resistive layer models l Much of the ocean floor underlain by igneous (i.e. crystalline) oceanic crust – resistive l Continental margins – thick (many km) layers of sediments l High porosities, saturated with sea water – so much lower resistivities l But hydrocarbons and methane hydrates can dramatically increase resistivity – but generally only occur in isolated thin layers

12 Seawater 0.3  m Sediment 1  m Reservoir 100  m 800 m 1000 m 100 m halfspace HED source Reservoir model – 1D

13 Compare two models l 1.5 km water depth l 1 ohm-m sediments l 50 m thick resistive layer, 180 ohm- m, buried 950 m below sea floor l Transmission frequency 0.25 Hz l End-on and broadside calculations, for both model with resistive layer and model without it

14 Both geometries

15 Result l For the end-on result, the thin layer has a huge effect on the amplitude l For the broadside result, the effect on amplitude is much smaller l Can demonstrate this more clearly by dividing the result for one model by the result for the other – ‘normalizing’

16 Comparing models

17 Why use both? l So the end-on result is more sensitive than the broadside result l So why bother to use both? l Answer is – distinguishing between classes of models l Another important case – when resistivity at depth is greater for some other reason e.g. porosity, salt …

18 Sediment over salt

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20 Summary l Inline and broadside responses can be sensitive to different aspects of the structure l “Broadside” corresponds to azimuth 90 and S azim in modelling code l “Inline” corresponds to azimuth 0 and S rad in modelling code

21 SOES6002: Modelling in Environmental and Earth System Science CSEM Lecture 6 Martin Sinha School of Ocean & Earth Science University of Southampton

22 Comparing polarizations l So thin resistive layers are a class of model that leads to ‘splitting’ of amplitudes between modes l Whereas thicker resistive layers are a class of model that do not l But why should this be happening? l Need to use some physics to understand our models

23 Direction of currents l We can think of the source dipole as generating two polarizations of current loops l Loops in the horizontal plane – inductively coupled between layers l Loops in the vertical plane – carrying electric current across the boundaries between layers

24 The field lines of a dipole

25 Horizontal electric dipole in layered earth

26 Seawater 0.3  m Sediment 1  m Reservoir 100  m 800 m 1000 m 100 m halfspace HED source Reservoir model – 1D

27 Horizontal current loops : ‘PM Mode’

28 Vertical current loops : ‘TM Mode’

29 Direction of currents l Think of the source dipole as generating two polarizations of current loops l Loops in the horizontal plane – ‘PM Mode’ – inductively coupled between layers, main contribution to broadside l Loops in the vertical plane – ‘TM Mode’ – carrying electric current across the boundaries between layers, main contribution to inline

30 Effect of a thin resistive layer – in-line Fields measured at the seafloor Resistive layer Uniform+resistive layer Uniform seafloor

31 Effect of a thin resistive layer – broadside. Fields measured at the seafloor Resistive layer. Uniform seafloor Uniform+resistive layer

32 Case study 1 – Does it work in practice? The first trial survey was carried out in It was a collaborative research project between SOC, STATOIL, and Scripps Institution of Oceanography, and The target was a known hydrocarbon bearing reservoir. Results were presented at the 64 th Conference of the EAGE in May 2002.

33 DASI deployment (North Atlantic, November 2001)

34 Data processing Initial processing involves extracting the component of the recorded electric field which corresponds to the known source signal and combining this with acoustically derived navigation data on source and receiver locations. The resulting amplitude and phase of the received electric field as a function of source-receiver separation and geometry form the basis for analysis and interpretation.

35 Field data from a known reservoir

36 West Africa 2000: 0.25Hz data from Line 1 Electric field strengthNormalised field strength

37 2-D effects l In this course, we are going to limit ourselves to 1-D – i.e. uniform layers l In practice, we can also run models and analyse data in 2-D and 3-D. Models are more complex, but the principles are just the same l For example, detecting the ‘edge’ of a reservoir -

38 Detecting the edge of a reservoir CSEM sounding for hydrocarbon exploration: Effect of reservoir edge. 2.5 D model Transmitting dipole aligned across the structure In-line source-receiver geometry Radial field amplitude and phase

39 1D background 1D reservoir 2D reservoir Edge effect in survey data

40 CSEM sounding for hydrocarbon exploration: Effect of the edge of the reservoir 2.5-D model, invariant direction up the page, variable direction across the page Transmitting dipole aligned up the page Component shown – amplitude of Pe max Colour contours: normalised by amplitudes from a 1-D structure with no hydrocarbon White contours: absolute field values

41 Dipole aligned parallel to edge: l Transmitter and receiver both over reservoir: response extremely similar to the 1-D case l If either transmitter OR receiver moves off the edge of the reservoir, the signal very rapidly reverts to looking like the case for no hydrocarbon

42 CSEM sounding for hydrocarbon exploration: Field trials offshore West Africa, October/November 2000

43 West Africa 2000: 2D ‘view’ of the reservoir

44 Case Study 2 l Using both geometric modes is important not only for the ‘thin resistive layer’ classes of models l Having both data types has been crucial in studies of mid-ocean ridges l Example – Lau Basin study, the Valu Fa Ridge

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47 Anatomy of an active hydrothermal system: The Valu Fa Ridge, Lau Basin, SW Pacific.


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