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Petrophysics model (water saturation) output from view: a 3D gridding model, b horizontal slice SGS, c color-coded according to water saturation of the Saar Formation in the study area
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The Masila area is located in the Hadhramaut region in east central Yemen. Oil was first discovered in the area in late 1990 with commerciality being declared in late 1991. Oil production began in July 1993. By the end of December 1999, the daily production rate was set at 210,000 stock tank barrels/day (STB/D) of very low gas-oil ratio (GOR) oil u...
Citations
... The Say'un-Masilah Basin is thought to be among the most important oil-producing sedimentation basins in the Yemen (Naji et al. 2010a;Hakimi et al. 2011a, b). This basin belongs to the Hadramawt governorate in eastern Yemen, which includes several blocks (Block 10, Block 53, Block 32, and Block 14) as shown in Fig. 1B. ...
... The Pre-rift mega sequence lies between the Precambrian and Middle Jurassic, which is characterized by intensively folded and metamorphosed rocks. (Naji et al. 2010a;As-Saruri et al. 2010). The Syn-rift mega sequence distinguishes the sediments that are thicker and close to rifting while thinner away from rifting. ...
This work attempts to solve the knowledge gap in the Sharyoof oil field within Block 53, Say’un-Masilah basin, eastern Yemen using acquired wells logs data. In this area, the Qishn Sandstone is considered to be the major member of the Qishn Formation, which exhibits good reservoir features. To determine the traps of hydrocarbons, this Member was divided into S1A, S1B, S1C, and S2 sub-units bounded by shale and carbonate layers. Thus, the principal objective of this study is the establishment of the lithological components for the Sa’ar and Qishn Formations in addition to the determination of hydrocarbon entrapment style in Qishn sandstone Members from the Sharyoof oil field. In this study, the used data were collected from six wells covering gamma-ray, caliper, deep and shallow later loge resistivity, photoelectric absorption index, and porosity tools (density, neutron, and sonic). The obtained results reveal that lithology is mainly composed of dolomite for Sa’ar Formation; sandstone interbedded with limestone, dolomite, and shale belonging for Qishn clastic Member, and limestone for Qishn Carbonates Member. Petrophysical parameters were integrated within the reservoir to identify the best potential hydrocarbon traps. The statistical analysis of petrophysical parameters showed that S1A and S1C are the best sub-units illustrating high porosity and hydrocarbon saturation, which ranges between 15–22%, and 60–87%, respectively. These sub-units highlighted low clay volume, which is less than 23%. The S2 sub-unit demonstrates an effective porosity of up to 22%, a water saturation comprised between 12% and 100%, and shale volume that ranges between 0% and 25%. Horizontal isoparametric maps have demonstrated that hydrocarbon saturation increases with increasing porosity and decreasing clay volume toward the north and south–west for unit S1A, northwards only for S1C, and north-southwestwards for S2. Consequently, these findings support the proposition of new drilling wells in these directions. Alternatively, besides proposing a new drilling position, the originality of the present work lies in the identification of the lithological characteristics of the Qishn Formations. As such, this research can be used as a baseline study.
... Producible quantities of oil are found in a number of different reservoirs including the Precambrian granitic basement (Archean) and the Saar Fm. (Lower Cretaceous), as well as the Qishn Fm. (Beydoun et al., 1993;Omran and Al-Areeq, 2014). The most successful reservoir is sand of the Qishn Fm. (Lashin, 2016;Naji et al., 2010;Khamis, 2017;Hakimi et al., 2018;Vorobev et al., 2019). ...
The main aim of the present study is the characterization of the Qishn Formation in Sharyoof oil field locating within the Masila basin, by applying the 3D static modelling techniques. The present study was initiated by the seismic structural interpretation, followed by building a 3D structural framework, in addition to analysing well logs data. The results are then used for constructing 3D facies and petrophysical models. The Qishn Formation exhibits depth values within the range of 400-780 m below sea level in the Sharyoof oil field, with a general increase towards the SSE direction. It is dissected by a set of high dip angle normal faults with a general ENE-WSW trend. It is also folded as a main anticline with an axis that is parallel to the fault trend, formed as a result of a basement uplift. According to the facies models, the Qishn Formation comprises 43.83% limestone, 21.53 % shale, 21.26% sandstone, 13.21 % siltstone and 0.17% dolomite. The Qishn Carbonates Member has low porosity values making it a potential seal for the underlying reservoirs. While the Upper Qishn Clastics S1A and C have good reservoir quality and S1B has fair reservoir quality. The Upper Qishn Clastics S2 and S3 have also fair reservoir quality, while the Lower Qishn Clastics zone has good reservoir quality. The water saturation decreases towards the west and east directions and increases towards north and south direction. The total OOIP of the Upper Qishn clastics is 106 million STB within S1A, S1C and S2 zones. Drilling of development wells is recommended at the eastern part of the study area, exhibiting good trapping configuration, in addition to the presence of potential seal (Upper Qishn Carbonates Member) and reservoir (Qishn clastics Member) with high porosity and low water saturation.
... The structural model was built with the help of the Petrel structural framework, which represents the overall geometry of the model and is the backbone for designing the 3D grid, which contains the geological and petrophysical information and the subsequently generated reservoir properties (Naji et al., 2010). The three main processes of the structural framework modeling within this study are the fault framework, the horizon modeling, and the structural gridding processes. ...
Fluid flow is governed by primary and secondary porosity of rocks but also by their permeability. Often the values of primary porosities and permeabilities are not sufficient to allow fluids to flow from potential geothermal or hydrocarbon reservoirs. To ensure an efficient productivity, fractured reservoirs come into focus as they might provide an economically viable fluid flow. Subsurface fractured reservoirs are difficult to investigate, outcrop analogues like the one investigated help in a better understanding. The studied outcrop represents a Lower Triassic braided river succession within an arid alluvial plain, affected by the main fault of the western Rhine Graben (southwestern Germany). The research thesis was carried out with the help of terrestrial laser scanning (TLS) to generate a digital outcrop model (DOM), used to digitize data and serve as basis for the subsequent modeling in two steps. These are (i) the volumetric modeling of the investigated fault zone within the Triassic Lower Buntsandstein, and (ii) subsequent modeling of the discrete fracture network (DFN). Volumetric modeling comprises three main points: (i) the application of a fault zone facies concept, (ii) stair-stepped fault gridding, and (iii) splitting the fault zone into two geobodies, well established in structural terminology, the damage zone ‘DZ’ and the fault core ‘FC’. For the subsequent DFN calculations a thorough fracture data parametrization was carried out providing six defined fracture sets, the fracture shape, the log-normal aperture distribution, the log-normal length distribution, the P32 intensity, and fracture truncation percentages at bed boundaries (DZ only). DFN upscaling was then conducted with the “Oda” and “Oda Corrected” methods for the fracture permeability calculations. The resulting volumetric model comprises 13 fault zone facies types. Their distribution within the DZ follows the encountered beds’ morphology. Within the FC three facies distribution cases were modeled. Seven different DFN configurations were calculated, consisting of 162 fracture sets in total. Fracture permeability amounts between 190 and 720 D within the DZ and 14,130 to 55,189 D within the FC, while the fracture porosity shows values of about 0.4 % for the DZ and 2.38 % for the FC. The study shows that volumetric fault zone modeling requires a simultaneous fault facies analysis and grid construction. Because stair-stepped fault grids facilitate a high complexity but lack cell size flexibility, a thoroughly considered choice of the cell size, dependent on the smallest geological objects present, is crucial. Characterization and processing of fracture aperture constitutes the most important part of the parametrization, as different methods can lead to distinct differences in the modeled final fracture permeabilities, spanning multiple orders of magnitude, even for exactly the same values of mechanical aperture. Inclusion of fracture connectivity lowers the resultant horizontal fracture permeability by 26 to 38 %, while truncation of fractures on bed boundaries can overestimate permeability values. Although the FC shows a significantly higher fracture permeability than the DZ it is affected by extreme fracture permeability cutoffs due to the fault cores’ specific architecture, resulting in a conduitbarrier system. Fracture porosities are more insensitive to parameter changes, because of its dependence on the mechanical aperture only. The presented multi-approach thesis highlights the challenges, limitations, and great possibilities of fault zone models, to help in a better understanding of the impact fault zones might have on geothermal and hydrocarbon reservoirs, and thereby support exploration.
... The more well points there are, the more representative the variogram function is, and the more the established model is in line with the actual geological situation. In contrast, the fewer well points there are, the weaker the adaptability of the variogram value obtained from data analysis, and the less representative the random model that can be established [29,30]. ...
For 3D geological modelling of oil and gas reservoirs, well pattern density is directly related to the number of samples involved in the calculation, which determines the variation function of stochastic modelling and has great impacts on the results of reservoir modelling. This paper focuses on the relationship between well pattern density and the variogram of stochastic modelling, selects the large Sulige gas field with many well pattern types as the research object, and establishes a variogram database of stochastic models for different well pattern densities. First, the well pattern in the study area is divided into three different types (well patterns A, B, and C) according to well and row space. Several different small blocks (model samples) are selected from each type of well pattern to establish the model, and their reasonable variogram values (major range, minor range and vertical range) are obtained. Then, the variogram values of all model samples with similar well pattern densities are analysed and counted, and the variogram database corresponding to each type of well pattern is established. Finally, the statistical results are applied to the modelling process of other blocks with similar well pattern density to test their accuracy. The results show that the reservoir model established by using the variation function provided in this paper agrees well with the actual geological conditions and that the random model has a high degree of convergence. This database has high adaptability, and the model established is reliable.
... INTRODUCTION A crucial step in building a geological model is the assignment of petrophysical properties (porosity, permeability, fluid saturations) in the model cells between and beyond the existing well control [1]. The previous geological models of Hamra Quartzites (QH) fail to accurately classify and make estimations of the reservoir's petrophysical properties [2]. ...
A new multidisciplinary workflow is suggested to recharacterize the Hamra Quartzite (QH) formation using artificial
neural networks. This approach involves core description,
routine core analysis, special core analysis and raw logs of
fourteen wells. An efficient electrofacies clustering neural
network technology based on a self-organizing map is performed.
The inputs in the model computation are: neutron porosity,
gamma ray and bulk density logs. According to the selforganizing map results, the reservoir is composed of five
electrofacies (EF1 to EF5): EF1, EF2 and EF3 with good
reservoir quality, EF4 with moderate quality, and EF5 with bad
quality. Hydraulic flow units are determined from well logs and
core data using the flow zone indicator (FZI) approach and the
multilayer perception (MLP) method. Obtained results indicate
eight optimal hydraulic flow units. Hydraulic flow units for uncored well are determined using the MLP, the used inputs to
train the neural system are: neutron porosity, gamma ray, bulk
density and predefined electrofacies. A dynamic rock typing is
achieved using the FZI approach and combining special core data
analysis to better characterize the hydraulic reservoir behavior.
A best-fit relationship between water saturation and J-function is
established and a good saturation match is obtained between
capillary pressure and interpreted log results.
... The Masila oilfields are well known as the most important hydrocarbon province of Yemen (e.g. Mills, 1992;Beydoun et al., 1993;Putnam et al., 1997;Csato et al., 2001;Al-Areeq, 2008;Naji et al., 2010;Hakimi et al., 2011a,b) and contain 14 oilfields of various sizes, the largest of which are the Cammal, Haijah and Tawilah oilfields (Fig. 1B). Oil was discovered in the Masila oilfields in late 1990 with commercial reserves being declared in late 1991, and oil production began in July 1993. ...
... Several workers (e.g. Hatitham and Nani, 1990;Mills, 1992;Redfern and Jones, 1995;Bosence et al., 1996;Bosence, 1997;Putnam et al., 1997;Beydoun et al., 1993Beydoun et al., , 1996Watchorn et al., 1998;Cheng et al., 1999;Csato et al., 2001;Al-Areeq, 2008;Naji et al., 2010;Hakimi et al., 2010aHakimi et al., ,b, 2011aHakimi et al., ,b, 2012aAl-Areeq et al., 2011;Omran and Alareeq, 2013) have made significant contributions with regard to our understanding of the regional geology, sedimentology, tectonic evolution and petroleum prospectivity of the Sayun-Masila Basin. A few published works exist in sandstone diagenesis and reservoir quality (Hakimi et al., 2012a) of the Lower Cretaceous Biyadh sandstones in the , showing (B) location map of Masila oilfields and (C) location map for five exploration wells presented and provide core and data for the Qishn Formation. ...
Lower Cretaceous sandstones of the Qishn Formation have been studied by integrating sedimentological, petrological and petrophysical analyses from wells in the Masila oilfields of eastern Yemen. These analyses were used to define the origin, type of diagenesis and its relation to reservoir quality. The sandstones of the Qishn Formation are predominately quartz arenite to subarkose arenite with sublitharenite and quartz wackes displaying a range of porosities, averaging 22.33%. Permeability is likewise variable with an average of 2844.2 mD. Cementation coupled with compaction had an important effect on porosity destruction after sedimentation and burial. The widespread occurrence of early calcite cement suggests that the sandstones of the Qishn Formation lost significant primary porosity at an early stage of its diagenetic history. In addition to poikilotopic calcite, several different cements including kaolinite, illite, chlorite and minor illite–smectite occur as pore-filling and pore-lining cements, which were either accompanied by or followed the development of the early calcite cement. Secondary porosity development occurred due to partial to complete dissolution of early calcite cements and feldspar grains. The new data presented in this paper suggest the reservoir quality of Qishn sandstones is strongly linked to their diagenetic history; hence, the reservoir quality is reduced by clay minerals, calcite and silica cements but is enhanced by the dissolution of the unstable grains, in addition to partial or complete dissolution of calcite cements and unstable grains. Copyright © 2015 John Wiley & Sons, Ltd.
... Nowadays, the reservoir model building workflow is mainly divided into four steps: (1) definition of the reservoir boundaries (and especially the top and bottom horizons), (2) building a geologically true structural model (layering, faults, etc.), (3) population of properties (porosity, permeability) by kriging or co-kriging for instance and then (4) upscaling the model in order to obtain a reservoir model[8,22]. In this study, all steps of the workflow were conducted precisely. ...
Determination of petrophysical parameters by using available data has a specific importance in exploration and production studies for oil and gas industries. Modeling of corrected permeability as a petrophysical parameter can help in decision making processes. The objective of this study is to construct a comprehensive and quantitative characterization of a carbonate gas reservoir in marine gas field. Artificial neural network is applied for prediction of permeability in accordance with other petrophysical parameters at well location. Correlation coefficient for this method is 84 %. In the study, the geological reservoir model is developed in two steps: First, the structure skeleton of the field is constructed, and then, reservoir property is distributed within it by applying new stochastic methods. Permeability is modeled by three techniques: kriging, sequential Gaussian simulation (SGS) and collocated co-simulation using modeled effective porosity as 3D secondary variable. This paper enhances the characterization of the reservoir by improving the modeling of permeability through a new algorithm called collocated co-simulation. Kriging is very simple in modeling the reservoir permeability, and also, original distribution of the data changes considerably in this model. In addition, the SGS model is noisy and heterogeneous, but it retains the original distribution of the data. However, the addition of a 3D secondary variable in third method resulted in a much more reliable model of permeability.
The complex geological structures, of the Sharyoof field in the Say'un-Masilah Basin of Yemen, make obtaining accurate information about the hydrocarbon entrapment style difficult. This situation adversely affects the efficiency of the exploration. Therefore, the present study provides a detailed character analysis of subsurface structural features as well as determines the entrapment style of Early Cretaceous age hydrocarbons (the Qishn Sandstone Reservoir) in the Sharyoof oil field. To identify accurate structural features, calculate petrophysical parameters of the Qishn sandstone member and predict their complex geometry in a 3D model, this investigation is based on the analysis of a multidisciplinary data set. The three-dimensional modeling was based on the interpretation of 2D seismic profiles and well logs data analysis. The obtained results indicate two types of a normal faults, consisting of plane faults and antithetic faults, which are oriented NE-SW and NW-SE with a thickness variation from 76 to 153 m. The intersection of these faults resulted in horst structures, in the northwest and southwestern parts, and graben and half-graben structures, in the southern and southeastern parts of the study area. The dips of these faults are between 20 and 90°. The 3D models of petrophysical parameters and the cross section extracted from the 3D model demonstrated that the Qishn sandstone reservoir has a low clay volume while having high porosity, permeability and hydrocarbon saturation values. Furthermore, the Qishn Sandstone is overlain by layers of the Qishn Carbonate Member, which has very low porosity and permeability and high clay volume, making it an effective seal. Therefore, these novel findings could be used to propose a drilling site for exploration wells within the Qishn Clastics membership.
The Say’un-Masilah basin is one of the most prolific sedimentary basins in Yemen, and therefore it has attracted the attention of geologists and geophysicists for hydrocarbon prospection and exploration. The main objective of this research is to study the structural and stratigraphic subsurface features as well as to determine the lithological contents of the Sharyoof oil field, Block 53, in the Mesozoic rift basin, eastern Yemen, using seismic and well log data. The basic inputs in this study include log data, collected from six wells, such as gamma ray (GR), caliper, deep, and shallow laterlog resistivity (LLD, LLS), micro-spherically focused log (MSFL), photoelectric absorption index (PEF), and porosity tools (density, neutron, and sonic). In addition, seismic sections including 15 lines 2D, well tops, bottom, sheck shot, well header, and deviations were used to accomplish this study objective. The obtained results from the seismic profiles interpretations demonstrated the existence of a series of normal faults dissecting most of the mapped horizons toward NE-SW (major faults) and NW-SE and W-E (secondary faults) creating several graben and horst structures. Moreover, results analysis of the well log data indicates that the main lithology content is dominated by the presence of the carbonates (limestone and dolomite) in the Sa’ar Formations and Qishn Carbonates Member while the sandstones for the Qishn Clastics, Harshiyat, and Mukalla Formations. The lithostratigraphy succession consists of rock units ranging in age from Early to Upper Cretaceous age (from Sa’ar to Mukalla Formations). Furthermore, seismic section data allowed determining the subsurface feature styles from reflections maps of both isochronous (two-way travel time) on the tops of the Sa’ar to Mukalla Formations. They reflect the occurrence of several distinct structures (anticlines, synclines, and faults), added to trends of faulting (NW-SE dissected by NE-SW). The novel contribution of the present work consists in the identification of the structural characteristics of the Lower and Upper Cretaceous formations of Block 53 using new seismic lines. Therefore, the obtained results of this study allow determining the sections and composition holding the hydrocarbon reservoir characteristics. As such, this research can be used as a reference study.
