The Maui Field is bounded in the west by the reverse Whitiki Fault and in the east by the normal Cape Egmont Fault (Figure 1). The Maui sub-basin is considered as the main source of the hydrocarbon that migrated into the Maui Field. A wide range of lithofacies is presented in the TaranakiBasin. We focus on the Eocene Kapuni which comprises three main formations, i.e., the Mangahewa (C-sand), Kaimiro (D-sand), and Farewell (F-sand) (King et al., 2008). The deposition environments of the Kapuni Group consist of coastal plain, marginal marine, and shallow marine to offshore that formed the thick sandstone layers. The coastal plain environment encounters the fluvial channel, overbank, and Marsh/floodplain facies. The marginal marine environment contains facies including estuarine, distributary, tidal channel beach, back beach, back-barrier bar, tidal sand-bar, flood tidal-delta sandflat, mudflat, embayment, and lagoon. The shallow marine depositional setting encounters shoreface, shoreline, and mouth-bar facies. The offshore deposited shelf mudstone, storm-generated sandstone, and offshore barrier facies (Table 1) (King et al., 2008). Coals in the Pakawau and Kapuni groups are considered as the most potential petroleum source rocks in the TaranakiBasin.
Both Kingdom (Version 8.8) and Petrel software 2012 (64-bit), windows- based three-dimensional interactive system, were used for seismic data interpretation and well log analysis. The workstations allow the user to work with any of its interpretation packages to generate more detailed and convincing results. The package used here included 2d/3dPAK. EarthPAK, LogPAK. SynPAK, and VuPAK. The 2d/3dPAK was used extensively during interpretation. This package allows the user to interpret the horizon and fault and also generate structural maps.
Three-dimensional seismic integrated with well log data were used to interpret the architecture of the Miocene period Moki Formation in the Maari Field. The main reservoir in the Maari Field is the Moki reservoir, which consists of sandstone. The sandstone in the formation is interbedded with a thin layer of siltstone and claystone. The Moki Formation is the most important formation in the Maari Field for producing oil. The source rock of the TaranakiBasin is upper Late Cretaceous, comprised of coals and clay mudstone of the Rakopi groups. The wells, Maui-4, Moki, Maari-1, and Maari-2, are producing oil from the Moki reservoir. The Kea-1 well, which is located in the north portion of the Maari Field, is dry because the elevation of the Moki oil-water contact is too low. Based on seismic data and well log analysis, the following main conclusions can be reached:
The major problem I address in part II is how to characterize a carbonate reservoir with variable pore types from poststack seismic inversion. The dataset used is borehole logs and poststack seismic volume from Yuanba gas field, Sichuan Basin, China. The target strata is the Feixiangguan Foramtion of Permian, which is deeply buried up to 6000 meter. The combined result of deposition and diagenesis on Feixiangguan carbonates increases the pore type variations in the rock to such an extent that pore structure together with porosity has a major control on rock properties. Based on this understanding, it is not wise and accurate to estimate porosity directly from impedance inversion. What reservoir parameter can be more accurately predicted based on poststack impedance inversion, considering the wide availability of poststack seismic data? What is the geological meaning of this reservoir parameter? These two questions are addressed in this part.
NZ straddles an active tectonic plate boundary and as such its coastal communities are vulnerable to earthquake and tsunami hazards (NIWA, 2009). Recent incidents with NewZealand, such as the Canterbury and recent Central North Island earthquakes, as well as the potential for tsunami/earthquake events originating in the Pacific Rim to affect NZ waters have highlighted that these events can occur and impact upon planned activities. The impacts of such incidents on off-shore temporary activities such as exploration well drilling are, however, considered to be limited, particularly given the anticipated water depths within the Project Area. Drilling is also planned for an area that is relatively flat and stable, hence the likelihood of subsidence is considered to be low. Potential impacts resulting from natural disaster events could include spills (oil and fuel) and/or vessel sinking, both of which are considered to have high severity of impacts. However, such an occurrence is considered to be extremely unlikely and the overall significance is considered to be ALARP.
In this paper provisions of existing codes are compared with the draft code. The draft code considers various parameters like convective and impulsive loadings on liquid retaining structure, it is found to be covering many facets related to seismic loading. There are many parameters common in both the codes while the draft codes needs calculations of horizontal shear force, shear moment, sloshing wave height, time period etc. in impulsive & convective modes in addition to other parameters. To Study the design of elevated water tank the staging system seismic force calculation of IS 1893- 1984 and 1893-part II (draft code) for 3 tanks of 1000 Cum, 2000 Cum, 3000 Cum capacity of cylindrical and Intz type where design manually. Concluding remarks of this work are 1) Horizontal seismic coefficient in impulsive and convective mode is to found more in 1000 Cum as compared to 2000 Cum and 3000 Cum tank. 2) Total base Shear in convective and impulsive mode found to be more in 2000 Cum, 3000 Cum. 3) Time period in case of convective mode is found to be varying between 4 sec to 17 sec. For medium soil condition Sa/g is calculated using formula 1.36/T, resulting in very low values of Sa/g.
Figure 5.3. Seismic sections depicting the relation between faults and blocks. a) Map showing the location of seismic sections in this figure. b) Stepped profile of Horizon 1, evidencing the influence of pre‐existing faults on the mass‐failure. The small steps in the horizon irregular profile are due to fault activity, whereas high steps are due to remobilization of failed strata. The latter is confirmed by the height of the deformed block, similar to the height of the erosional step. c) section of MTD‐A1 depicting the relation between faulting and remnant strata/blocks. The remnant features show evident vertical continuity with the underlying unit, limited by the erosional surface. Notice the thicker accumulations on the eastern sector underlain by faults. d) and e) illustrate in more details the link between blocks and pre‐failure faults. The blocks commonly show their limits aligned with the faults, especially less deformed ones. Fractures are commonly identified within the bigger blocks. Rafted blocks show titled or folded internal reflections, implying lateral movement. Fault‐block alignments are less evident in this type.
grains. However, as the present southern distributional limit of M. excelsa lies only about 10 km north of the Mimi River near Pukearuhe (Clarkson and Boase, 1982) it is conceivable that the Metrosideros pollen type could also include M. excelsa. Metrosideros pollen was also abundant in pollen cores from southern coastal Taranaki at Waverley Beach and Waiau Swamp (Bussell, 1988). However, at these sites, this pollen type clearly represents M. robusta as the sites are well beyond the southern distributional limit of M. excelsa. Many other tall trees and shrubs were present in this forest community including Prumnopitys ferruginea, P. taxifolia, Elaeocarpus dentatus, E. hookerianus and Vitex lucens which were all present locally, as their pollen and seeds were found in the peat. Laurelia novae-zelandiae, Alectryon excelsus, Knightia excelsa leaves were found in the Mimi peat, and Dysoxlyum spectabile, Dodonaea viscosa, Nestegis spp., Aristotelia serrata, Ascarina lucida, Griselinia lucida, Macropiper excelsum, Urticaceae and others, were all recorded in the pollen at low levels. In addition, there would have been numerous other important species in coastal communities that are missing from the pollen record because they are either severely under-represented [e.g. Beilshmiedia tawa (rarely found in fossil records; Macphail and McQueen, 1983), Geniostoma rupestre, Melicytus ramiflorus, Melicope ternata] or included in a poorly differentiated taxonomic group of pollen (e.g. Brachyglottis repanda).
ABSTRACT: Seismic method is one of the most frequently applied geophysical methods in the process of oil and gas exploration. This research is conducted in Nias Waters, North Sumatra using one line 2D post-stack time migration seismic section and two wells data. Reservoircharacterization is carried out to obtain physical parameters of rocks affected by fluid and rock lithology. Seismic inversion is used as a technique to create acoustic impedance distribution using seismic data as input and well data as control. As final product, multi- attributeanalysis is applied to integrate of inversion results with seismic data to determine the lateral distribution of other parameters contained in well data. In this research, multi-attributeanalysis is used to determine the distribution of NPHI as a validation of hydrocarbon source rocks. In that area, there is a gas hydrocarbon prospect in limestone lithology in depth around 1450 ms. Based on the results of sensitivity analysis, cross-plot between acoustic impedance and NPHI are sensitive in separating rock lithology, the target rock in the form of limestone has physical characteristics in the form of acoustic impedance values ??in the range of 20,000-49,000 ((ft/s)*(g/cc)) and NPHI values in the range of 5-35 %. While the results of the cross-plot between the acoustic impedance and resistivity are able to separate fluid-containing rocks with resistivity values ??in the range about 18-30 ohmm. The result of acoustic impedance inversion using the model based method shows the potential for hydrocarbons in the well FYR-1 with acoustic impedance in the range 21,469-22,881 ((ft/s)*(gr/cc)).
Paleocene fluvial to marginal marine arkosic sandstones beds of the Farewell Formation are an important proven hydrocarbon reservoir in TaranakiBasin, NewZealand (Fig. 1). The Paleocene sedimentary system grades northwestward from fluvial deposits in southern TaranakiBasin, including within the Manaia Graben (Fig. 1), into marginal marine to shoreface glauconitic sandstones in central parts of the basin (known as the F-Sands in Maui Field, this study and wider onshore Taranaki Peninsula; Fig. 2) and then into shelf-marine mudrocks north of Taranaki Peninsula (Fig. 3). The fluvial succession has lower reservoir quality than the glauconitic sandstone beds due to intercalated sandstone and mudstone facies and greater depths of burial (Martin et al. 1994; O’Neill et al. 2018). The glauconitic sandstone facies (F-Sands; Fig. 2) display good reservoir quality (av. 16.2 % porosity) (STOS 1993a, 1993b; Killops et al. 2009; Strogen 2011), being a major oil reservoir in the Maui Field (Fig. 4) and other smaller fields on the Western Platform (Tui, Amokura, and Pateke; Fig. 1). The reservoir quality of the Farewell Formation and F-Sand sandstones in TaranakiBasin is controlled mainly by grain-size variations and presence of kaolinite, which is often cited as the single most important cause of reservoir quality degradation across the Paleocene of TaranakiBasin (Martin et al. 1994; Smale et al. 1999; Pollock et al. 2003; Killops et al. 2009).
In this work, 3Dseismic reflection data was analyzed to get the different seismic velocities, which are the basis of hydrocarbon exploration. A principal use of velocity functions derived from reflection velocity analyses is the correction of primary reflections in each common depth point (CDP) trace gather for NMO prior to residual static time correction and trace summation (stacking). The knowledge of the true interval velocity of each layer is needed in the hydrocarbon industry.
Two possible reservoir zones could be delineated from this well at the interval of 3930 and 3910m (Figure 49) .A strong negative deflection is apparent on the SP long and the gamma ray exhibits a short cleaning upward trend. The dirtying up trend is dominant in the log and is distinctive of a funnel shaped signature. Following this is a dirtying upward trend caused by the shale and silt laminations. The well seems to be highly saturated in water. The volume of shale in the reservoir zones is less than 50 meaning that the Vsh is not too high in the log. The Sp log depicts a negative deflection at the reservoir zones and all zones have the gas effect bounding them. The deep resistivity signature is relatively constant at 20ohm, but at a depth of 3965m there is a spike and the deep resistivity reached approximately 2000ohm which also has a corresponding lower water saturation signature depicted.
reservoir thickness, transverse change fast, impedance overlapping of reservoir and surrounding rock, which lead to difficult reservoir prediction. According to the application of the integration of seismic data, logging data, drilling, logging, testing data, the high precision earth's physical parameters can reflect the reservoir lateral variation, and depict the basic characteristics of the reservoir depict the basic characteristics of reservoir. For geophysical conditions, optimizing coherent, frequency division attribute qualitative prediction of fuyu reservoir sand body distribution rule of every sand formation. Quantitative prediction of geostatistics inversion in this research area of every sand formation sand body distribution, combine with well logging and testing data, which is well matching with the existing drilling and provide a reference for the further oil and gas exploration.
A promising strategy to define an optimum grid scaling system can be described as follows. When the lateral grid scale of a reservoir model is chosen, the seismic bin spacing is the best option because it preserves all the potential information that can possibly be extracted from the seismic data. However, the challenge is the choice of the vertical- or z-scale of the model. Seismic data typically have a lower resolution in the vertical direction than the other sources of information (e.g. well log data and core measurements). For modeling reservoir properties, the vertical scale should be related to the scale of the geological heterogeneities in the volume to be modeled. This scale is highly dependent upon the types of rock in the reservoir. It is essential to note that, while it is not the purpose of a reservoir model to include every small geological detail extracted from the geological analyses, neither large-scale nor regional information of interest is in this context. The purpose of the model is to simulate a specific volume of reservoir rocks that allow fluid flow through it. Thus, the optimal vertical scale of a reservoir model depends on the scale of the reservoir flow unit, which may vary from one or two centimeters to several meters.
Porosity is an important property of a reservoir because hydrocarbon (oil and gas) can fill in voids of porous rocks. The prediction of reservoir properties has been continuously developed for many years. The prediction of physical properties such as porosity from empirical correlations of multivariate linear regression between seismic attributes and well log data was introduced by numerous authors (Schultz et al., 1994; Russell et al., 1997; Hampson et al., 2001). A seismicattributeanalysis to estimate physical properties such as porosity, permeability and others in a reservoir were studied (Brown, 1996; Leiphart and Hart, 2001; Tebo and Hart, 2003; Calderon and Castagna, 2007).
The Kenai Group sits over the West Foreland Formation and has been divided into four formations: the Hemlock conglomerate, Tyonek, Beluga, and Sterling (Figure 5). The Kenai Group rocks are of Oligocene to Pliocene age and consist of conglomerates, coal, siltstone and sandstone. Well data indicate over 20,000 feet of Tertiary sediment north of the city of Kenai, but sediments thin significantly moving southwest towards the Seldovia Arch (Figure 3) (Fisher and Magoon, 1978; Hartman et al., 1972; Kelly, 1963). The lower part of the Kenai Group is a distinct lithologic group referred to as the Hemlock zone. The Hemlock is a poorly sorted sandstone, conglomerate, and carbonaceous shale interbedded with thin streaks of coal seams and lignite streaks (Kelly, 1963). The Hemlock zone is a significant oil reservoir throughout the Cook Inlet, although it has not proven to be a productive interval in Ninilchik field.
Abstract— Saldanadi Gas Field, a part of greater Rukhia Structure located at northeastern part of Bangladesh, is one of the producing gas fields of the country. Integrating seismic and wire line log data this structure has been modeled by the Petrel software. Structural model, facies model, property model including porosity, permeability models have been generated using various algorithms present in the software. For the purpose of these modelings all the 12 seismic lines (SD-01, SD-02-RESI, SD-03-RESI, SD-04-RESI, SD-05-RESI, SD-06-RESI, SD-07-RESI, SD-08-RESI, SD-10-RESI, SD-10- mig, SD-12-RESI, SD-14-RESI) were interpreted and time map was generated. T-Z curve was used for time to depth conversion and depth map was also created. Three gas sands identified by BAPEX are Upper Gas Sand (UGS), Middle Gas Sand (MGS) and Lower Gas Sand (LGS). Among these three gas sands Upper Gas Sand (UGS) and Lower Gas Sand (LGS) are the study zones of this research work. Wire-line log data was used to correlate Gas Sand Zones between wells Saldanadi-1 and Saldanadi-2. Fault modeling was not performed as no fault was identified in any of the seismic sections.
the statistical topological property of the visibility networks to describe the carbide content in the microstructures. Image analysis of the SEM images of the RLH specimens is an interesting approach. With MR, GP and NN, we predict the carbide content in the microstructures. Finally, we present a new hybrid system of intelligent systems. For measured and predicted parts of carbides of the LHR specimens data, we calculated Kendall correlation coefficient. The best results for prediction give us NN, because the Kendall correlation coefficient (0.021) is most close to experimental data (0.131). Table 3 presents the topological properties of the 3D visibility network and attributes of RLH specimens. In this way, we can see how the attributes of speed and temperature influence the topological structures of visibility graphs in 3D space. Table 6 presents the statistical properties of the topological properties of the extreme number, number of edges, and triadic census type 16 to 300 of the 3D visibility network for RLH specimens. Firstly, we calculated the basic statistical properties of the mean, standard deviation, standard error, median, geometric mean, and harmonic mean of the topological properties of visibility graphs in 3D space of RLH specimens. We found significant positive relationships between the kurtosis, Fisher’s G2, the coefficient of variation, the coefficient of dispersion,
In this paper, we proposed another form of deep learn- ing, a linguistic attribute hierarchy, embedded with linguistic decision trees, for spam detection. A case study was carried out on the SMS message database from the UCI machinelearning repository. It has been shown that the decomposition of features plays an important role in the construction of the linguistic attribute hierarchy, which directly affects the performance of decision making by the constructed linguistic attribute hierarchy. In the experiments, three decompositions of features (attributes) were investigated, and the LAHs were constructed based on strategies for the three decompositions semantically. The performance of LAHs for different decom- positions were examined in term of sensitivity, specificity, accuracy and ROC curve. According to the experimental results, the LDT with the highest sensitivity should stay in the top layer, different to the layers where other LDTs with lower sensitivity in order to obtain a high sensitivity of the LAH, but in order to obtain large area under ROC, all LDTs should be placed in the bottom layer of the LAH. However, without decomposition, a single LDT trained by the full set of features cannot obtain a larger area under ROC than an LAH could have. The experimental results show that the features related to the benefits and finance have important impact on the sensitivity of identifying spam messages. This observation matches the convention of human knowledge. The process of experiments has demonstrated the use of a hierarchy of linguistic decision tree approach for deep learning of feature impact on spam detection. Hence, an LAH, embedded with LDTs, provides a transparent approach to in-depth analysing feature impact to the spam detection. This approach can not only improve the performance of spam detection when the semantic attributes are constructed to a proper hierarchy, but also efficiently tackle ‘curse of dimensionality’ in spam detec- tion with massive attributes. The automatic knowledge based decomposition of features and the optimisation of linguistic attribute hierarchies and high performance spam detectors will be the future work.
Selecting modeling defined, on the one side, typically analyzed the geological situation and the prospect from the point of view of the possible presence of hydrocarbon deposits, on the other hand, sufficient study as the geometry of the individual layers and the distribution of the elastic properties and density. Problems arising in the implementation of this simple computational scheme have been linked to the fact that the seismic record is limited in frequency, both below and above [9, 10, 11].