A scaled experiment for the verification of the SeaBed Logging method

Seabed Logging (SBL), a tool that uses Marine Controlled Source Electromagnetic (CSEM) method to specifically explorer and map conceivable hydrocarbon-bearing prospects. In spite of the fact that the CSEM technique has been utilized by the scholarly community forever three decades. The focal thought of SBL is the controlling of electromagnetic vitality in thin resistive layers inside conductive dregs. Regardless of whether it has been notable for quite a while that electromagnetic signs can engender from a conductive formation to another by means of resistive areas, for example, air or resistive parts of the lithosphere, the application to hydrocarbon investigation has not been created as of not long ago. This may be because of the vulnerability of getting any critical reaction from thin resistive layers, for example, hydrocarbon stores since electromagnetic vitality is profoundly lessened in conductive silt. In this way, amid the early improvement period of the SBL procedure, a scaled research experiment was performed to approve if a thin resistive layer (e.g. hydrocarbons) covered inside conductive media (e.g. dregs) could be remotely recognized by utilizing electric dipoles as sources and receivers. Information from this analysis were well contrasted with a forward modelling code. However, the analysis cant be applied in the stratified media with challenging sediments, oil and sea water is present. This research have presented the consequences of the main scaled SBL analysis by introducing the major contituents of the SBL surveys with respective forward modelling.

D035 On the Signal Propagation in Marine CSEM L.O. Løseth* (Statoil ASA formerly Dept. of Physics NTNU) & L. Amundsen (Statoil ASA) SUMMARY In marine CSEM (controlled source electromagnetics) and SBL (SeaBed Logging) one explores the subsurface by emitting low-frequency signals from an electric dipole source close to the seabed. The main goal is to determine and characterise possible thin resistive layers within the conductive surroundings beneath the seabed (Eidesmo et al. 2002). A typical geological model from an exploration case includes a sea-surface interface a seabed interface and a thin resistive layer. The electromagnetic (EM) response from a plane

It is well known that no single geophysical method can provide a completepicture of the earth and its properties and recently integrated interpretationand joint inversion of multiple data types has become a much studied topic(Chen et al, 2007; Harris et al, 2009; Jegen et al, 2009; de Stephano et al,2011). The seismic method is in many situations the tool of choice: it isgeneral and widely applicable, and can provide detailed images of sub-surfacestructure and stratigraphy from which complex geological models can beconstructed. If seismic methods can provide the answer to the question ofinterest then this is undoubtedly the tool to use. However although seismicdata are extremely sensitive to the changes in lithology occurring at theboundaries between geological units, they are less sensitive to fluid changeswithin these units. This is because acoustic and elastic properties of theearth show only small changes when the fluid content or saturation is changed. These changes can in some circumstances be detected and used to provideinformation on fluid distribution. In other situations this is difficult orimpossible to do with certainty, and complementary geophysical methods must beemployed to meet the reservoir characterization goal. In many situations electrical resistivity is driven by the properties anddistribution of fluids in the earth. Commercial hydrocarbon deposits may bemany times more resistive than surrounding lithologies. This change inresistivity caused by variations in fluid content and saturation can, inprinciple, be detected using CSEM tools (See Constable & Srnka 2007 for areview of CSEM technology). However when only CSEM data are considered, structural resolution is poor because of the diffusive nature of the EM fields, and the results can be ambiguous because the effect of an increase in porefluid resistivity cannot be distinguished from the effect of a decrease inporosity. The presence of frustrating resistors in the section (for exampletight carbonates, cemented sandstones or volcanics) can also complicate theinterpretation. Well-log data provide a range of measurements, including both resistivity andacoustic/elastic properties as well as a range of further properties. Apetrophysicist analyzing this well log data will take all of these measurementsand integrate them together to provide an interpretation of the lithology andfluid properties. The resistivity measurement in particular provides keyinformation on the fluid content at the well bore. However such informationcannot provide any constraint on the variation of properties away from thewell, across a reservoir. For any given geophysical question, the most robust answer will be obtained byusing the tool, or combination of tools best suited to the task, andintegrating the resulting data within a rock physics framework, to provide ashared earth model that is geologically reasonable, and consistent with each ofthe geophysical data types available. Careful integration of multiple datatypes can allow the strengths in one method to compensate for the weaknesses inanother. Here we consider three data types: seismic, controlled source electromagnetic(CSEM), and well log data. The workflow applied is shown in figure 1. CSEM dataare first inverted to provide a measure of resistivity. Because of the poorstructural resolution of CSEM data taken in isolation, this inversion isconditioned with seismic structural information. From the results, thetransverse resistance (the vertically integrated resistivity), which is wellconstrained by the CSEM method, can be calculated within the intervals ofinterest.

We have found how the effects of the air wave in marine controlled-source electromagnetic (CSEM) methods gradually vanish in the sea for shallow waters, and how at the same time they gradually grow below the seafloor, in an effort to comprehend existing detectability definitions. The transition from sea to land is smooth because the sea becomes a thin conductive layer when the water depth is smaller than the skin depth in the sea. We consider the problem of detecting resistive layers at depth associated with hydrocarbon reservoirs, particularly in shallow-water explorations and, specifically, on how the air wave affects detection. Our analysis is based on an integral representation of the electric field in terms of its sensitivity to changes in the electrical conductivity of a 1D profile. Two-dimensional images of the integrands are obtained by plotting the integrand as a function of depth for different offsets. Results include the expected growth of the inhibiting effect of the sea as the water depths decrease. However, we also find that this happens up to a point and that from then on its effect decreases to zero. Regarding the resistive layer at depth, its importance grows to a constant as the water depth decreases to zero. As a function of offsets, there appear first the direct current effects. The induction zone is next and is dominated by contributions from the underlying formations. The third zone, which corresponds to the air wave, is largely dominated by contributions from the sea. The fourth and last zone is the plane-wave asymptote. All four classical zones identified in marine CSEM are also present in land CSEM.

The new emerging technique for finding resistive layers in the subsurface which can be hydrocarbon-saturated reservoirs using Marine controlled source electromagnetic (CSEM) is called seabed logging (SBL). It uses a mobile horizontal electric dipole (HED) source which generates ultra low frequency (0.1 – 10 Hz) but powerful electromagnetic signal while being towed at about 30 – 40m above an array of seafloor electric field receivers. These arrays of receivers will receive signal in the form of direct waves, air waves, reflected waves and refracted waves and is measured in the form of amplitude and phase. The amplitude and phase of this signal depend on the resistivity of the mediums that they travel. Hydrocarbon is known to have high resistivity value of 30 – 500Ωm, in contrast to conductive sea water of 0.5 – 2 Ωm and sediments of 1 – 2Ωm. This paper will investigate and discuss the effect of these receivers readings in term of direct waves, air waves, reflected waves and guided waves as we increased the frequency value from 0.01Hz to 10Hz. Using simulator that has been developed using MATLAB software we will set up a forward model that contains air, sea water, sediments and hydrocarbon reservoir with their predefined resistivity values. From here we shall discuss the trend on wave amplitude obtained at different frequency values.

This paper presents a 1D modeling of electromagnetic waves for sea bed environment developed using MATLAB software. This paper focuses on two main areas; the first is on the simulator that is able to model plane layer modeling of the sea bed environment, by setting the deep of sea water, sediments and size and location of the hydrocarbon trap. This model shall be used as a forward modeling of sea bed environment. The second focus is on the effect of electromagnetic waves called direct waves, reflected waves and refracted waves on the sea bed environment where potential hydrocarbon is present. Our work is based on Sea Bed Logging (SBL) application that uses marine controlled source electromagnetic (CSEM) sounding technique to detect and characterize hydrocarbon bearing reservoirs in deep water areas. SBL uses a mobile horizontal electric dipole (HED) source called transmitter and an array of seafloor electric field receivers. The transmitter transmits a low frequency electromagnetic signal from 30m - 40m above the sea bed into water layer and to underneath the sea bed. The array of the receivers will receive the signal in the form of direct waves, air waves, reflected waves and refracted waves and is measured in the form of amplitude and phase. These signals depend on the resistivity structure beneath the sea bed. Hydrocarbon is known to have high resistivity value of 30 – 500 Ωm in contrast to sea water layer of 0.5 – 2 Ωm and sediments of 1-2 Ωm. These signals were plotted to show the Electric Field amplitude verses offset (AVO) and comparisons were made.

In August 2008, a marine Controlled Source ElectroMagnetic (CSEM) survey was acquired by WesternGeco EM for the previous operator (Encana) of Lady Franklin and Atammik blocks offshore west Greenland. The objective of the project was to rank possible hydrocarbon prospects in the upper Cretaceous section. Therefore, the survey was designed to optimize CSEM responses based on the previous operator's interpretation within a limited budget, resulting in a pseudo-3D survey, sub-optimal to assess actual interpretation updated according to the results of the three exploration wells drilled by Cairn in the block during 2011. Independent 3D inversions of the CSEM data run before the drilling campaign suggest a consistent background resistivity over the different prospects. Drilling results confirmed the resistivity distribution as recovered by 3D CSEM inversions within the data resolution limit. After the drilling campaign, a sensitivity study was carried out in order to assess the limit at which the geological problem can be tuned by the electromagnetic data response. This showed that the resistive anomalies visible on some of the prospects in the block cannot be assessed for hydrocarbon saturation on the basis of electromagnetic data alone as they are below the resolution of the method given the non-uniqueness of the results. The present paper highlights how non-seismic data, such as electromagnetic, can provide additional information which, integrated with other geophysical and geological data, can help exploration during the different phases. The pre-drilling analysis of the resistivity distribution as recovered by 3D inversion of the data identified resistive anomalies that were interpreted as hydrocarbon indicators. The drilling results identified the geological meaning of these anomalies, which were further analyzed to include and extrapolate the new post-drilling interpretation in order to evaluate the non-drilled prospects. The sensitivity study was critical to understand the EM data limitations in this geological context before investing in a new project. Introduction Electromagnetic data are widely applied in the oil industry in order to de-risk exploration, reducing the uncertainty related to reservoir saturation (Hesthammer et al., 2012). Many success stories increased the confidence in electromagnetic data as hydrocarbon detectors: in fact, electromagnetic data provide information exclusively regarding the resistivity distribution of the underlying earth. Resistive anomalies may be related to fluid saturation, but they may also be produced by different geological features not necessarily related to fluid saturation: volcanics, carbonates, and evaporites are only some examples of lithologies characterized by high resistivity values. In addition, inversion of electromagnetic data is a non-unique problem and therefore constraining the inversion with the available geological and geophysical information is critical in order to produce a geologically meaningful model and subsequent interpretations. The limited data and frequency range (~ 0.1 to 10 Hz), the diffusive physics of CSEM, and the necessity (usually) of using a smooth stabilizer for inversion result in low resolution.

The land-based controlled-source electromagnetic (CSEM) method is an important tool in mapping subsurface resistivity contrast, especially for conductive target embedded in a resistive environment. For resistive targets on land, choosing an appropriate configuration to a specific field observation is quite confusing, due to the lack of systematic comparisons of different methods. We have conducted a comparison between the broadside and inline time-domain CSEM methods, using the short-offset transient electromagnetic (SOTEM) method and multitransient electromagnetic (MTEM) method as representatives respectively. We first compared the resolution of these methods by analyzing the relative target response and the misfit space of the designed models. We found that the inline MTEM method had advantages over the SOTEM method in resolving the thin resistive layer. We have developed a weighted joint inversion scheme to enhance the vertical resolution of the MTEM method. We then applied the methods to the investigation of a giant molybdenum deposit. The orebody, which is the real target of the exploration, does not have a conductivity contrast with its host. However, it sits on top of the granite porphyry, which is resistive compared with its surroundings, and so the granite porphyry becomes the resistive target for EM exploration. The results indicated that both methods are effective in locating large resistive target, yet the MTEM method outperforms the SOTEM method when a thick conductive overburden is presented.

Chapter 14 - Electromagnetic Methods in the Frequency and Time Domains

ABSTRACTThis paper discusses the asymptotic behaviour of the electromagnetic fields received on the sea‐bed (target response), as well as the fields distributed inside a thin resistive target, generated by a horizontal electric dipole above the sea‐bed in marine controlled‐source electromagnetics for hydrocarbon exploration. It is found that the guided wave supported by a thin resistive target can be expressed as a single‐mode exponential function. A simple closed‐form expression is derived to relate the single‐mode wavenumber of the guided wave to the model parameters: the resistivity and thickness of the target layer, the sea‐bed resistivity and the frequency. When the air‐wave is removed, the guided wave is dominant among the fields received on the sea‐bed at far offset. Hence the wavenumber of the guided wave can be calculated from the fields measured on the sea‐bed. The closed‐form expression can then be used to invert the target property from the calculated wavenumber and hence, can be considered as a hydrocarbon indicator.

Since the late 1990s, the continuous development and application of the Controlled-Source Electromagnetic (CSEM) technology have vastly improved its usage in exploration (e.g., Constable, 2010; Loseth et al., 2015; Zach et al., 2009). CSEM inversion results are the main input for interpretation of resistivity data, especially potential fluid anomalies. Complementary to other geophysical methods, e.g. Amplitude versus Offset (AVO), it can therefore be a valuable tool in hydrocarbon exploration. Yet, the unconstrained nature of the subsurface and non-unique¬ness of inversions is a tough predicament. For example, several features in the subsurface could cause high resistivity, such as abundant limestone, salt, basalt, mature source rocks or hydro¬carbon-filled sandstones (Baltar and Barker, 2015). As a result of enhanced data quality, data processing and inversion capabilities, together with improved workflows and accumulated experience, CSEM interpretation has become increasingly more robust (Buland et al., 2011; Karman et al., 2013; Loseth et al., 2014). The 3D Gauss-Newton (GN) inversion algorithm is a more robust method compared to other inversion types. GN thus provides a new, powerful methodology for generating marine CSEM resistivity images. Nonetheless, it has formerly been com¬putationally exhaustive to apply. With the Hoop area, Barents Sea, recently being nominated for the Barents Sea exploration licensing round, a tight deadline was given for the CSEM inversion of an expansive 11,000 km2, over 130 blocks (refer to Figure 1). Adopt¬ing the flexible and agile cloud system into the CSEM workflow, it has improved the 3D GN work efficiency and provided overall consistent results when compared with other CSEM inversion schemes. This paper will illustrate how a systemic workflow of CSEM 3D GN inversions together with efficient cloud computing, could lead to a more consistent interpretation of this data.

A numerical study was conducted to investigate the governing physics of galvanic source electromagnetic (EM) methods for terrestrial and marine exploration scenarios. The terrestrial exploration scenario involves the grounded electric dipole source EM (GESTEM) method and the examination of how the GESTEM method can resolve a thin resistive layer representing underground gas and/or hydrocarbon storage. Numerical modeling studies demonstrate that the loop transient EM (TEM) and magnetotelluric (MT) methods are insensitive to a thin horizontal resistor at depth because they utilize horizontal currents. In contrast to these standard EM methods, the GESTEM method generates both vertical and horizontal transient currents. The vertical transient current interacts with a thin horizontal resistor and causes charge buildup on its surface. These charges produce a measurable perturbation in the surface electric field at early time. The degree of perturbation depends on source waveform. When the GESTEM method is energized with step-off waveform, the perturbation due to a thin horizontal resistor is small. This is because the step-off waveform mainly consists of low frequency signals. An alternative is taking the time-derivative of the step-off responses to approximate the impulse response which includes higher frequency signals. In order to improve degree of perturbation especially due to a localized small 3-D resistor, the diffusion angle of the vertical transient current, 45 should be considered to make vertical currents coupled to a resistive target efficiently. The major drawback of the GESTEM method lies in the fact that GESTEM sounding can not be interpreted using 1-D inversion schemes if there is near-surface inhomogeneity. The marine exploration scenario investigates the physics of marine frequency-domain controlled source EM (FDCSEM) and time-domain controlled source EM (TDCSEM) methods to explore resistive hydrocarbon reservoirs in marine environments. Unlike the marine MT (MMT) method, these two methods are very sensitive to a thin hydrocarbon reservoir at depth because their sources generate vertical as well as horizontal currents. As for the FDCSEM method, the normalized EM peak response occurs where the airwave starts to dominate the seafloor EM response in the background model. This point is a function of source frequency, seawater depth and seafloor resistivity. The peak magnitude of the normalized EM response depends on whether the high concentration of vertical currents can reach and interact with the reservoir effectively. Noise levels of the EM receivers are important factors for successful FDCSEM and TDCSEM survey design. The major benefit of using magnetic field responses over electric ones is that the noise level of magnetic receiver theoretically allows for greater surface coverage compared to that of the electric receiver. Like the GESTEM method, the TDCSEM method also requires the use of a proper transient EM pulse such that the relatively high frequencies are produced. The impulse response of the TDCSEM method is characterized by two-path diffusion of the EM signal. The initial response is caused by faster signal diffusion through the less conductive seafloor, while the later arrivals result from slower diffusion through the more conductive seawater. Therefore, at larger separations, the effects of the seafloor and seawater are separable. This can be useful in reducing the airwave problem associated with the FDCSEM method in shallow marine environments.

The Controlled-Source Electromagnetic (CSEM) method is one of the electromagnetic methods utilized in geophysical exploration. This method provides a subsurface image through the resistivity anomalies of materials encountered by electromagnetic waves. The research area is located near a major city, resulting in high electromagnetic noise. Electromagnetic noise can be categorized into two types of the noise namely periodic noise and sporadic noise. Eliminating noise is a crucial objective to enhance data quality, as it can introduce uncertainty into interpretations. Three noise removal techniques are employed: pre-stack to filter the harmonic noise, stacking to remove the sporadic noise, and post-stack for smoothing. The CSEM data used consists of signals in the time domain with a 10-second period and a 50% duty cycle. The results of applying these noise removal techniques indicate that all three methods are highly effective in noise reduction. The pre-stack technique can remove periodic noise, while sporadic noise is addressed by the stacking technique, and signal smoothing can be achieved using the poststack technique.

The controlled source electromagnetic (CSEM) method may be the most significant new technology for oil and gas exploration since the development of 3-D seismic 20 years ago. The promise for the technology lies in its ability to differentiate resistive, potentially oil-bearing intervals from surrounding, more conductive water-bearing units. The principal is the same as that used in well logging devices to identify hydrocarbon zones in well bores. The technique is not new but the capability to resolve relatively thin resistive intervals in the depth domain offers new promise to lower risk through direct hydrocarbon indicators in conjunction with modern seismic methods.We evaluated the sensing capability of the marine CSEM method to detect a thin hydrocarbon reservoir in deep, intermediate and shallow marine environments by analyzing the synthetic responses and the related physics using numerical modeling techniques. We would like to investigate the physics of marine CSEM using 1-D modeling program. The scope of investigation involved, all possible source-receiver configurations, advantages and disadvantages of frequency- versus time-domain systems, advantages and disadvantages of electric versus magnetic field measurements, a range of source-receiver separations including the coincident situation, and finally the air wave effect.

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper IPTC 16879, “Mapping Hydrocarbons Integrating Seismic With Electromagnetic and Gravity Attributes: Application in the Barents Sea,” by Paolo Dell’Aversana, Stefano Colombo, Barbara Ciurlo, Johan Leutscher, and Jan Seldal, Eni, prepared for the 2013 International Petroleum Technology Conference, Beijing, 26–28 March. The paper has not been peer reviewed. Electromagnetic attributes have been used extensively for interpreting marine controlled-source electromagnetic (CSEM) data. One of the basic attributes is called NAR (normalized-anomalous-amplitude response). Combining NAR and CSEM asymmetry represents a relatively simple way to use the benefits of both attributes jointly. This integrated approach, based on seismic data combined with electromagnetic and gravity attributes, has been applied in a complex exploration area in the Barents Sea. Introduction Inversion of geophysical data measured at surface represents a quantitative approach for estimating physical properties of hydrocarbon reservoirs and obtaining information about background geology (faults, structural trends, and lateral geological variations). This approach generally is based on the minimization of an objective function including the misfit between observed and predicted responses plus a regularization function. Inversion methods generally require long computation times and extensive use of parallel-computing resources. Moreover, they can produce nonunique solutions. A different but complementary approach for interpreting geophysical observations is based on the analysis of quantities, often called attributes, extracted from measurements by simple mathematical manipulation. Examples of electromagnetic attributes recently applied in hydrocarbon exploration are the gradient of CSEM magnitude vs. offset and the symmetry properties of the CSEM response itself. It has been demonstrated that CSEM attributes allow, at least in relatively simple scenarios, accurate and fast identification of reservoir boundaries. Also, in the gravity domain, attributes can work efficiently for rapid identification of important general features, such as basement trends, presence of fault systems, depth range of density anomalies, and lateral extension of salt domes and basalts. Attribute analysis cannot be considered a substitute of inversion, especially in complex geological settings, but instead should be considered as a complementary approach. In fact, in complicated scenarios, attributes can be used as a quick and efficient tool for preliminary identification of the main features of the model (resistivity and density boundaries, presence of faults, and approximate depth range of the target). This preliminary model can be used as a starting point for optimized inversion. In this paper, the authors show how several types of electromagnetic and gravity attributes can cooperate with seismic information for rapid delineation of the main geological trends in complex exploration areas. Moreover, the authors show how these attributes also can be complementary for identification of hydrocarbon reservoirs and for restricting the range of possible interpretive models. The authors use both synthetic tests and real examples for supporting their integrated method, which is based on combined seismic, electromagnetic, and gravity information.