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ABSTRACT In any industry the decision on whether or not to embark on a project depends on the economic expectations of the project. In this study we use Bayesian theory to demonstrate how the Expected Monetary Value (EMV) of seismic data can be calculated before a seismic survey is initiated. The procedure is illustrated on a hydrocarbon detection problem, on 4D cases, and on a structural resolution problem. Applying this procedure for calculating EMV one might compare a seismic project on an equal footing with any other projects competing for available funds. This approach can be used both to prioritize different 4D alternatives as well as different ordinary seismic tenders, thus making sure that the survey acquisition or processing alternative that in fact is best for the problem at hand is selected and not necessarily that which is cheapest. Before a survey is initiated, 4D or ordinary surveys, this methodology might be used to help estimate how much an oil company actually could pay for such a survey, which would be useful information both for the receiver and producer of a tender.
Introduction Controlled Source Electro-Magnetic imaging (CSEM) is a recently developed technology that maps subsurface resistivity variations (Eidesmo et al., 2002). It uses a horizontal electrical dipole (HED) which emits a low frequency electromagnetic (EM) signal into the underlying seabed and downwards. As the upper sediments are effectively partial conductors, the penetration of EM fields is limited by the so-called skin-depth. In practice this means that the technique requires a low frequency EM source, typically between 0.25 - 10 Hz, to allow penetration to about 2500-3000m into the subsurface. At low frequencies, Maxwell's equations for the electric field component reduce effectively to a diffusion process leading to strong dispersion.
- Africa > South Africa > Western Cape Province > Indian Ocean (0.25)
- North America > United States (0.18)
- Research Report > New Finding (0.41)
- Research Report > Experimental Study (0.41)
Integrated Prospect Evaluation Using Electromagnetic, Seismic, Petrophysical, Basin Modeling,and Reservoir Engineering Data
Harvey, Elizabeth Lorenzetti (Shell International E&P Inc.) | Skogly, Odd-Petter (Shell International E&P Inc.) | Burke, Tracy (Shell International E&P Inc.) | Amado, Luiz (Shell International E&P Inc.)
ABSTRACT A deepwater prospect in the Campos Basin, Brazil, was evaluated using a combination of geophysical and geological technologies including controlled-source electromagnetic data, seismic amplitude-vs.-offset and inversion data, basin- and prospect-scale modeling of hydrocarbon generation and migration, and petrophysical input to reservoir engineering models. The integration of these disciplines produced a consistent story for the prospect that reduced the uncertainty of the interpretation. Key uncertainties were the presence of reservoir and the presence, quality, and producibility of hydrocarbons. Many of the analyses, considered alone, were inconclusive or highly uncertain. Combining the analyses increased confidence in the interpretation, and several scenarios were dropped. For example, seismic forward modeling results using petrophysical trend data were ambiguous regarding the presence of reservoir and hydrocarbons. Reservoir engineering and offset well data suggested a likelihood of heavy oil with a seismic response similar to brine. Seismic amplitude-vs.-offset analysis indicated a weak response at the crest of the structure. Seismic inversion results supported the presence of reservoir, but indicated a wet response in all but the most crestal areas of the prospect. Prospect-specific basin modeling indicated that hydrocarbon migration into the prospect was unlikely, although an oil discovery was located only a few kilometers away. Electromagnetic data were acquired over the prospect and showed a negative response. This result was used to downgrade scenarios that could not be discounted with other data types. The integration of these data and methods has served to downgrade a prospect that has been in the exploration portfolio inventory for several years.
- Geology > Sedimentary Basin (1.00)
- Geology > Geological Subdiscipline > Stratigraphy (0.53)
- Geology > Geological Subdiscipline > Economic Geology > Petroleum Geology (0.51)
- Geology > Rock Type > Sedimentary Rock (0.50)
- Geophysics > Seismic Surveying > Seismic Processing (0.72)
- Geophysics > Seismic Surveying > Seismic Modeling > Velocity Modeling > Seismic Inversion (0.71)
- Reservoir Description and Dynamics > Reservoir Characterization > Seismic processing and interpretation (1.00)
- Reservoir Description and Dynamics > Reservoir Characterization > Geologic modeling (0.90)
- Reservoir Description and Dynamics > Reservoir Characterization > Exploration, development, structural geology (0.70)
Detecting Hydrocarbon Reservoir With Seabed Loggingtm In Deepwater Sabah, Malaysia.
Choo, C.K. (Sarawak Shell Berhad) | Rollett, E. (Sarawak Shell Berhad) | Gallegos, Ida (Sarawak Shell Berhad) | Rosenquist, M. (Shell International Exploration and Production) | Ghaffar, Kamal A. Abd. (PETRONAS Management Unit) | Wong, H.F. (PETRONAS Management Unit)
Summary SeaBed LoggingTM (SBL), a technique that utilises Controlled-Sourced Electromagnetic (CSEM) fields to probe subsurface resistivity, has been applied in Malaysia to decrease the critical risk of having blown traps in thrusted anticlines. Integration of this technology with pre-drill prospect evaluation techniques has successfully de-risked the recent Alpha* discovery. Besides helping to add material reserves, this technology continues to de-risk nearby prospects and improves Shell’s drilling successes in the basin. Introduction The depositional setting in DW Sabah consists of a number of large, sandy Miocene turbidite basin floor fans separated by shale-dominated intervals. The primary play type is the thrust fault play, where retention capacity of the top seal is considered the critical risk factor. Seismic data over some of the crestal areas is poorly imaged due largely to complex crestal faulting coupled with the presence of shallow gas/hydrates. In areas downdip of these prospects where seismic quality improves, rock properties modeling indicates that seismic amplitudes cannot distinguish residual saturation gas from high saturation oil. In a structural setting where the traps could potentially be blown, seismically there is no way to differentiate the presence of economic gas or oil and residual hydrocarbon in the target reservoirs. Hence, other non-seismic options such as electromagnetic (EM) techniques were explored, which is where SBL is introduced. Methodology With its deep waters and shallow targets, deepwater Sabah is ideal to test the SBL technology. A bigger SBL response is expected over larger structures, but with most of the prospects in deepwater Sabah being long and narrow, modeling work predicts a smaller but still detectable anomaly. Resistive hydrates are present in the near surface and these must be carefully considered, but interpretation of multiple frequencies and long offset imaging techniques can reduce the effect of hydrates on reservoir interpretation. Seafloor topography can also complicate the interpretation of EM data. SBL Acquisition In 2004, a SBL acquisition program was planned to test the viability of the technology by acquiring data over geologically favourable target reservoirs, and to de-risk other high-ranked prospects in the basin. Pre-acquisition 2D modeling was performed on these prospects to predict the SBL response using known rock properties (shale and hydrocarbon resistivity). Two 2D SBL traverses were acquired over recent discoveries and both showed anomalies as expected from modelling exercise. The success of these calibration surveys led to SBL data being used as a credible tool for evaluation of exploration prospect like Alpha, the prospect discussed below. Conclusion Calibration of the SBL processing with well results of the Alpha prospect has shown the possible potential of the methodology as a non-seismic imaging tool of the subsurface. The imaging result proves to be the “decision-tool” in making reasonable risk statements on the critical risk factors. Nevertheless, results have to be integrated with other evaluation techniques so as to maintain geological soundness. By applying proper pre-acquisition modeling followed by imaging processing and cautious interpretation, the SBL methodology will result in better pre-drill predictions and drilling successes in the deepwater Sabah Basin.
- Geology > Geological Subdiscipline (1.00)
- Geology > Sedimentary Geology > Depositional Environment > Marine Environment > Deep Water Marine Environment (0.55)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock > Mudrock > Shale (0.45)
- Asia > Malaysia > Sabah > South China Sea > Sabah Basin (0.99)
- Africa > Middle East > Libya > Al Wahat District > Sirte Basin > Sabah Field (0.97)
Summary This case history demonstrates the use of AVO inversion to help find commercial quantities of hydrocarbons in a multizone carbonate and clastic reservoir environment. The study area is close to Oyen, Alberta, Canada where a small 3D was acquired to help delineate gas in the Viking and Mannville sands, and heavy oil in a porous Banff carbonate. The seismic data were processed with a controlled amplitude processing sequence resulting in prestack migrated gathers. From this, P-wave and S-wave impedance volumes along with ?p, and µp volumes were generated for cross-plot analysis. Based on this analysis an step-out well was subsequently drilled which encountered four pay zones totaling 15 meters of gross pay. Introduction The Oyen 3D seismic survey is located in southeast part of the Western Canadian Sedimentary Basin (WCSB). This area has proven reserves from both clastic and carbonate reservoirs. The 7-12 well penetrated Viking gas sands and Banff heavy oil reservoirs. In an adjacent area, wells also encountered gas in the Glauconitic and Detrital clastics above the Paleozoic unconformity. Before the acquisition of the 3D seismic survey, there existed only one 2D seismic line in the study area. On this 2D line it was impossible to differentiate changes in any of the reservoir units seismically. In order to understand the structure of the Banff reservoir, a 3D seismic survey was acquired. Further, based on successful AVO case histories on these particular reservoir units (Goodway et al., 1997, Downton et al., 1999, and Li et al., 2003) it was decided to perform AVO inversion to help determine the best location for an step-out well. Geological Setting
- North America > Canada > Alberta (1.00)
- North America > Canada > Saskatchewan (0.70)
- Geophysics > Seismic Surveying > Surface Seismic Acquisition (1.00)
- Geophysics > Seismic Surveying > Seismic Processing (1.00)
- Geophysics > Seismic Surveying > Seismic Interpretation > Seismic Reservoir Characterization > Amplitude vs Offset (AVO) (1.00)
- Geophysics > Seismic Surveying > Seismic Modeling > Velocity Modeling > Seismic Inversion (0.93)
- North America > Canada > Saskatchewan > Western Canada Sedimentary Basin > Alberta Basin > Viking Formation (0.99)
- North America > Canada > Northwest Territories > Western Canada Sedimentary Basin > Alberta Basin (0.99)
- North America > Canada > Manitoba > Western Canada Sedimentary Basin > Alberta Basin (0.99)
- (5 more...)
Introduction Kalimantan Summary In the last two decades of exploration activities in Kalimantan and Eastern Indonesia areas, the exploration campaign has found several significant discoveries with total hydrocarbon discovered around 12 BBOE. Generally, the play concepts have moved from classical target in the shallow zone to deeper targets and older ages. Unfortunately, most of the exploration activities have concentrated in the producing basins, only one activity conducted in non-producing basin, which is in the southern edge of the Aru Trough Basin-Malita Calder Graben which discovered hydrocarbon. Kalimantan area contains three Tertiary producing basins and four non-producing basins. Exploration activities in Kalimantan region can be grouped into three applied technology phases: (1) traditional exploration, (2) 2D seismic exploration period, and (3) 3D seismic exploration period. The activities also can be grouped into three exploration concepts: (1) traditional play, (2) Mio-Pliocene Deltaic system, and (3) Mio-Pliocene Deepwater system. Since the first 3D seismic run in Kalimantan, more than 370 exploration wells have been drilled; all of the wells were drilled in producing basins with average success ratio of 53%, and have been discovered around 6 BBOE reserves in place. The most promising play concept of the recent exploration in Kalimantan is Mio-Pliocene Deepwater sands of Kut ei-North Makassar Basin (West Seno, Gula, etc). Currently , the exploration in this area has applied CSEM technology to answer several pitfalls in interpretation. Eastern Indonesia contains five producing Tertiary basins and 33 non-producing basins. Almost all of the basins, mainly the producing basins, were explored by the seismic activities from 1967-2005. Most of them were triggered the discoveries of hydrocarbon fields. Discoveries in Eastern Indonesia can be grouped into three system: (1) Miocene Carbonate System, (2) Plio-Pleistocene system, and (3) Mesozoic system. There were more than 160 exploration wells drilled in the last two decades with average success ratio of 41% and discovered around 6 BBOE reserves in place. The most attractive and promising play systems are Jurassic Roabiba-Aalenian-Plover Play system (Tangguh & Abadi giant gas field), Jurassic carbonate play system (Oseil), and Miocene carbonate in collision zone play system (Tomori area). There are 57 PSC contract areas in Kalimantan and Eastern Indonesia, 41 of which contract area are still in the exploration phase. Most of the PSC areas are located in producing basins. High trend of the world’s crude oil price, high exploration success in Kalimantan & Eastern Indonesia and large new reserves discovered may boast hydrocarbon players to find next remarkable discoveries in both mature and frontier basins in Kalimantan and Eastern Indonesia area. The exploration activity in Kalimantan has found 84 oil & gas fields in the Kutei Basin (~22 BBOE), 25 oil & gas fields in the Tarakan Basin (~1.9 BBOE), and 8 oil and gas fields in the Barito Basin (~0.82 BBOE). The evolution of the exploration activity is influenced by seismic activity. In the early exploration period from late 19th century to the 1960’s, exploration focused in the land of Kalimantan. Discoveries of the Lousie, Sesanip, and Tanjung Fields were in this period.
- Asia > Indonesia > Kalimantan (1.00)
- Asia > Indonesia > East Kalimantan > Makassar Strait (0.70)
- Asia > Indonesia > Sulawesi > Central Sulawesi (0.47)
- Phanerozoic > Mesozoic > Jurassic (1.00)
- Phanerozoic > Cenozoic > Neogene > Pliocene (1.00)
- Geology > Sedimentary Geology > Depositional Environment (1.00)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock > Mudrock (0.50)
- Geology > Structural Geology > Tectonics > Compressional Tectonics > Fold and Thrust Belt (0.50)
- Geology > Structural Geology > Tectonics > Plate Tectonics > Earthquake (0.45)
- Asia > Malaysia > Sulawesi > Central Sulawesi > Senoro-Toili JOB – PSC Area > Minahaki Formation (0.99)
- Asia > Malaysia > Sulawesi > Central Sulawesi > Banggai Basin (0.99)
- Asia > Indonesia > West Papua > Bintuni Basin (0.99)
- (17 more...)
Summary In the last few years Eni acquired large data sets in relatively shallow water environments using the Marine CSEM methodology. Additional efforts have been required for recording meaningful data sets and for a proper interpretation. In fact it is well known that shallow water represents a difficult environment for this geophysical application. In this paper we introduce a complete work flow aimed at optimizing the MCSEM methodology in this hostile condition. It is addressed to solve the main problems related with the acquisition, processing and interpretation steps. Synthetic tests and real applications are discussed. Introduction Marine CSEM is an electromagnetic method aimed at mapping the electrical resistivity in sub-seafloor structures with a maximum accuracy of few tens of meters and a depth of investigation of several kilometers below sea floor (Eidesmo et. Al., 1985; Kong et. Al., 2002; MacGregor et. Al., 1998; MacGregor et Al., 2000; MacGregor et Al., 2001; Greer et Al., 2003; Shina et Al., 1990, Kong and Westerdahl, 2002). A low frequency (typically 0.1-10 Hz) EM field is transmitted by a dipole source towed just above the seafloor and recorded by an array of receivers at the seabed (orthogonal electrical dipoles and magnetometers). In resistive layers, such as a hydrocarbon reservoir, the electric and magnetic field attenuation is lower than in the surrounding water saturated sediments. As a consequence the amplitude trend vs. offset can be indicative of the presence of hydrocarbon-filled sediments. In particular water depth has strong influence on the measured electric signal. This is due to the airwave effect, well explained in many papers about this methodology (Eidesmo et al., 2002; Ellingsrund et al., 2002). Airwave is generated at the sea-air interface, where the total electric field produced by the dipole source is scattered downward. This strong signal reaches the receivers located on the sea floor masking the earth response. This effect starts from an offset that depends on water depth: deeper is the water longer is the offset where the airwave starts to be predominant. In order to mitigate this problem several algorithms and techniques have been proposed. In general Up-Down separation is a set of methods aimed at subtracting the effect of the airwave generated from the water-air interface. This approach is based on the concept that, if the upward and downward diffusing components of the electric field can be separated, significant suppression of the airwave is possible. However several assumptions are required, such as that of plane waves travelling vertically. This assumption is not respected in the whole range of offset and it is dependent on water depth. Also the complexity of the subsurface geology can make this assumption invalid. Moreover also magnetic field measurements are required. As a consequence, an additional assumption is the presence of negligible noise, not only in the electric data but also in the magnetic measurements. In the reality significant problems could be caused by incoherent magnetic noise (for example internal receiver noise at the seafloor).
- Africa > South Africa > Western Cape Province > Indian Ocean (0.24)
- North America > United States > Louisiana (0.16)
- Oceania > New Zealand > South Pacific Ocean > Lau Basin (0.99)
- Oceania > Fiji > South Pacific Ocean > Lau Basin (0.99)
- Oceania > Australia > South Pacific Ocean > Lau Basin (0.99)
- Africa > South Africa > Western Cape Province > Indian Ocean > Bredasdorp Basin > Block 9 > EM Field (0.99)
Introduction Summary Amplitude anomalies observed in a seismic event can be due to lithology, over pressures and the presence of hydrocarbons. Amplitude anomalies due to either lithology or over pressures do not conform to structural contours and can easily be detected. Amplitude anomalies due to the presence of hydrocarbons on the other hand, fit with the structural geometry and also provide the spill point of the reservoir. The use of AVO as a DHI in clastic rocks is due to differences in the P-wave velocity (Vp) and S-wave velocity (Vs) in the presence of gas in a reservoir rock. While P-waves are sensitive to changes in pore fluids, Swaves are not affected by the presence of gas. Crossplotting of AVO products, e.g. Intercept vs. Gradient has proven to be even more robust indicators of hydrocarbons. Full pre-stack elastic inversion (relative and absolute) of seismic data can yield accurate information on reservoir rock properties and lithologies, with measurements of porosity and pore-fluid content. Of late, the use of “LMR” (Lambda-Mu-Rho) inversion, which estimates Lambda (incompressibility), and Mu (rigidity) from P-wave and Swave impedance estimates allows any appropriate elastic parameter (or derivatives) to be defined and cross-plotted. The case studies of four (4) wells drilled within the last 3 decades, highlight that the advances made in DHI prediction are no guarantee against the drilling of dry holes. Four wells, B1, B2, B3 & B4, were drilled based on one or more of the following: 2D, 3D, amplitude, AVO, relative pre-stack elastic inversion; these wells were dry or partially dry. This study tries to explain why, and how to minimize the risk of drilling dry holes. Methodology Geologic Setting The area studied is located in the Niger Delta in Southern Nigeria in the Coastal Swamp depobelt (Middle–Late Miocene), and consists of swamp, transition zone to shallow marine. The sedimentary units of the Niger Delta show an upward transition from marine pro-delta shales (Akata Formation) through a paralic interval of sand/shales (Agbada Formation) to a continental sequence (Benin Formation). The method used was to examine the seismic (2D or 3D), whether amplitude/AVO supported, type of inversion (relative/absolute pre-stack elastic inversion), then deduce reasons for failure. Case 2 Case 1 Well B1 was drilled in 1984 in shallow marine using 2D seismic and was dry. It encountered a channel complex between -1800 and -2300mssl (500m thick) which was not quite evident on 2D sections. The Channel-fills were made up of marine shales and silty sand streaks, hence are poor reservoirs. The maps generated from 2D sections showed a 4-way closure, while those from 3D that was later acquired in 1995 over the area showed no such closure. Reasons for failure: The well was drilled based on 2D seismic that gave false 4-way closures. No amplitude was extracted over structures to ascertain any DHI’s, and no AVO/inversion was done to determine rock properties / fluid content. Well B2 was drilled in 2004, on a 3-way hanging wall closure, supported by amplitude.
Summary Over the last 5 years, SeaBed Logging has gained rapid acceptance as a valuable technique to determine the presence or absence of hydrocarbons in structures defined by traditional seismic techniques. In this paper, we will use modeling and data decimation to explore some of the challenges associated with moving SBL technology into frontier exploration areas, where it can be used to • drive effective licensing strategies • focus seismic programs in the most prospective areas • improve the efficiency of expensive deep water drilling programs Introduction For over 75 years, the primary method for determining the presence of hydrocarbons at various burial depths has been the use of resistivity logs obtained using instruments delivered to the subsurface using wireline logging of a borehole. Recent work by Statoil and others has established that in the marine environment it is possible to detect buried hydrocarbons reserves prior to drilling a borehole. The controlled source electromagnetic (CSEM) technique employs a powerful source towed close to the seafloor and detectors resting on the seabed to map subsurface resisitivity volumes. The term SeaBed Logging (SBL) has been used to describe the patented application of long offset CSEM designed for the identification of hydrocarbon reserves prior to drilling. SBL has been used extensively, and successfully, to confirm the presence or absence of commercial quantities of hydrocarbons in structures identified using traditional seismic techniques(3). For this application extensive 1D and 3D modeling is employed to determine whether or not the presence of hydrocarbons in the anticipated reservoir will produce a measurable EM response. EM modeling is accurate, and thus use of the SBL technique can be restricted to those situations where accurate SBL diagnosis can be assured. It is now being proposed that EM techniques could be employed as a frontier exploration tool, which we refer to here as electromagnetic scanning. However, in the frontier environment, much less detailed geologic information may be available to support accurate modeling. Furthermore, when assessing the prospectivity of large frontier areas, high productivity and low cost are required. This means that EM scanning must be able to operate with relatively sparse source lines and receiver spacing. Before embarking on an EM scanning program, it is wise to assess the project to • determine what hydrocarbon targets will be identified … and which ones will be missed • determine the potential for observation of nonhydrocarbon related resistive anomalies • apply appropriate techniques to mitigate the risk of misclassification of resistive anomalies. In this paper, we use various modeling techniques to quantify the risks and rewards of EM scanning, as well as investigating techniques to mitigate the risks associated with sparse spatial sampling. Effective crossline aperture In practice, the SBL technique will detect resistive anomalies laterally displaced from a 2D line illustrates the wedge of detestability beneath a 2D SBL line. Due to the polarized nature of the EM phenomenon, the SBL line is less sensitive to shallow out of plane bodies, but becomes more sensitive to these bodies with increasing depth.
Combined Porosity, Saturation And Net-to-gross Estimation From Rock Physics Templates
Avseth, Per (Rock Physics Technology AS, Bergen, Norway) | van Wijngaarden, Aart-Jan (Norsk Hydro Research Center, Bergen, Norway) | Mavko, Gary (Stanford Rock Physics Laboratory, Stanford, USA) | Johansen, Tor Arne (Center of Integrated Petroleum Research, University of Bergen,Bergen,Norway)
ABSTRACT We have developed a methodology to predict net-to-gross and hydrocarbon saturation in heterogeneous reservoirs using rock physics templates. The proposed methodology contains 5 steps: 1) Estimate the dry rock elastic properties of the interbedded sandstone at high porosity end member using contact theory (Hertz-Mindlin modeling). 2) Interpolate between mineral point and high porosity end member using modified Hashin Shtrikman modelling. 3) Perform Gassmann fluid substitution to estimate the properties for brine and hydrocarbon saturated sandstone. 4) Pick a characteristic shale, and calculate elastic properties either from observed well log data, or based on contact theory. 5) Conduct Backus average upscaling for various net-to-gross where shales are interbedded with sands of varying saturation. Our modeling results show that net-to-gross and patchy saturation are linked together when the wave propagation is vertical to the the layering. Analysis of well log data from a North Sea turbidite reservoir show that part of the gas filled reservoir has seismic properties similar to homogeneous brine sands when the net-to-gross is lower than ca. 0.8. Modeling shows that horizontal well log measurements would better discriminate saturation and net-to-gross effects.
- Geology > Geological Subdiscipline > Geomechanics (1.00)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock > Sandstone (0.90)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock > Mudrock > Shale (0.78)
- Geophysics > Borehole Geophysics (1.00)
- Geophysics > Seismic Surveying > Seismic Modeling (0.46)
- Geophysics > Seismic Surveying > Seismic Interpretation (0.46)
- Reservoir Description and Dynamics > Reservoir Characterization > Seismic processing and interpretation (1.00)
- Reservoir Description and Dynamics > Reservoir Characterization > Exploration, development, structural geology (1.00)
- Reservoir Description and Dynamics > Formation Evaluation & Management > Open hole/cased hole log analysis (1.00)