scholarly journals Integrated reservoir characterization and quality analysis of the carbonate rock types, case study, southern Iraq

2020 ◽  
Vol 10 (8) ◽  
pp. 3157-3177 ◽  
Author(s):  
Sameer Noori Ali Al-Jawad ◽  
Muhammad Abd Ahmed ◽  
Afrah Hassan Saleh
Keyword(s):  
Reservoir Characterization ◽  
Water Saturation ◽  
Rock Type ◽  
High Water ◽  
Quality Analysis ◽  
Reservoir Quality ◽  
High Porosity ◽  
Rock Types ◽  
Porosity And Permeability ◽  
Medium Porosity

Abstract The reservoir characterization and rock typing is a significant tool in performance and prediction of the reservoirs and understanding reservoir architecture, the present work is reservoir characterization and quality Analysis of Carbonate Rock-Types, Yamama carbonate reservoir within southern Iraq has been chosen. Yamama Formation has been affected by different digenesis processes, which impacted on the reservoir quality, where high positively affected were: dissolution and fractures have been improving porosity and permeability, and destructive affected were cementation and compaction, destroyed the porosity and permeability. Depositional reservoir rock types characterization has been identified depended on thin section analysis, where six main types of microfacies have been recognized were: packstone-grainstone, packstone, wackestone-packstone, wackestone, mudstone-wackestone, and mudstone. By using flow zone indicator, four groups have been defined within Yamama Formation, where the first type (FZI-1) represents the bad quality of the reservoir, the second type (FZI-2) is characterized by the intermediate quality of the reservoir, third type (FZI-3) is characterized by good reservoir quality, and the fourth type (FZI-4) is characterized by good reservoir quality. Six different rock types were identified by using cluster analysis technique, Rock type-1 represents the very good type and characterized by low water Saturation and high porosity, Rock type-2 represents the good rock type and characterized by low water saturation and medium–high porosity, Rock type-3 represents intermediate to good rock type and characterized by low-medium water saturation and medium porosity, Rock type-4 represents the intermediate rock type and characterized by medium water saturation and low–medium porosity, Rock type-5 represents intermediate to bad rock type and characterized by medium–high water saturation and medium–low porosity, and Rock type-6 represents bad rock type and characterized by high water saturation and low porosity. By using Lucia Rock class typing method, three types of rock type classes have been recognized, the first group is Grain-dominated Fabrics—grainstone, which represents a very good rock quality corresponds with (FZI-4) and classified as packstone-grainstone, the second group is Grain-dominated Fabrics—packstone, which corresponds with (FZI-3) and classified as packstone microfacies, the third group is Mud-dominated Fabrics—packstone, packstone, correspond with (FZI-1 and FZI-2) and classified as wackestone, mudstone-wackestone, and mudstone microfacies.

The Uniqueness of Heterogeneous Globigerina Limestone Reservoir and The Importance of Integrated Rock Type Definition for Field Development Plan: Case Study in Madura Strait, East Java

2021 ◽  
Author(s):  
E. P. Putra
Keyword(s):  
Water Saturation ◽  
Rock Type ◽  
Reservoir Rock ◽  
Reservoir Quality ◽  
Secondary Porosity ◽  
Field Development ◽  
Core Data ◽  
Type Definition ◽  
Volume Porosity ◽  
Porosity And Permeability

The Globigerina Limestone (GL) is the main reservoir of the seven gas fields that will be developed in the Madura Strait Block. The GL is a heterogeneous and unique clastic carbonate. However, the understanding of reservoir rock type of this reservoir are quite limited. Rock type definition in heterogeneous GL is very important aspect for reservoir modeling and will influences field development strategy. Rock type analysis in this study is using integration of core data, wireline logs and formation test data. Rock type determination applies porosity and permeability relationship approach from core data, which related to pore size distribution, lithofacies, and diagenesis. The analysis resulted eight rock types in the Globigerina Limestone reservoir. Result suggests that rock type definition is strongly influenced by lithofacies, which is dominated by packstone and wackestone - packstone. The diagenetic process in the deep burial environment causes decreasing of reservoir quality. Then the diagenesis process turns to be shallower in marine phreatic zone and causes dissolution which increasing the reservoir quality. Moreover, the analysis of rock type properties consist of clay volume, porosity, permeability, and water saturation. The good quality of a rock type will have the higher the porosity and permeability. The dominant rock type in this study area is RT4, which is identical to packstone lithofasies that has 0.40 v/v porosity and 5.2 mD as average permeability. The packstone litofacies could be found in RT 5, 6, 7, even 8 due to the increased of secondary porosity. It could also be found at a lower RT which is caused by intensive cementation.

Improved Prediction of Reservoir Behavior Through Integration of Quantitative Geological and Petrophysical Data

1999 ◽  
Vol 2 (02) ◽  
pp. 149-160 ◽  
Author(s):  
D.K. Davies ◽  
R.K. Vessell ◽  
J.B. Auman
Keyword(s):  
Body Size ◽  
Reservoir Characterization ◽  
Rock Type ◽  
Carbonate Reservoir ◽  
High Porosity ◽  
Geometrical Characteristics ◽  
Rock Types ◽  
Flow Units ◽  
Reservoir Description ◽  
Pore Body

Summary This paper presents a cost effective, quantitative methodology for reservoir characterization that results in improved prediction of permeability, production and injection behavior during primary and enhanced recovery operations. The method is based fundamentally on the identification of rock types (intervals of rock with unique pore geometry). This approach uses image analysis of core material to quantitatively identify various pore geometries. When combined with more traditional petrophysical measurements, such as porosity, permeability and capillary pressure, intervals of rock with various pore geometries (rock types) can be recognized from conventional wireline logs in noncored wells or intervals. This allows for calculation of rock type and improved estimation of permeability and saturation. Based on geological input, the reservoirs can then be divided into flow units (hydrodynamically continuous layers) and grid blocks for simulation. Results are presented of detailed studies in two, distinctly different, complex reservoirs: a low porosity carbonate reservoir and a high porosity sandstone reservoir. When combined with production data, the improved characterization and predictability of performance obtained using this unique technique have provided a means of targeting the highest quality development drilling locations, improving pattern design, rapidly recognizing conformance and formation damage problems, identifying bypassed pay intervals, and improving assessments of present and future value. Introduction This paper presents a technique for improved prediction of permeability and flow unit distribution that can be used in reservoirs of widely differing lithologies and differing porosity characteristics. The technique focuses on the use and integration of pore geometrical data and wireline log data to predict permeability and define hydraulic flow units in complex reservoirs. The two studies presented here include a low porosity, complex carbonate reservoir and a high porosity, heterogeneous sandstone reservoir. These reservoir classes represent end-members in the spectrum of hydrocarbon reservoirs. Additionally, these reservoirs are often difficult to characterize (due to their geological complexity) and frequently contain significant volumes of remaining reserves.1 The two reservoir studies are funded by the U.S. Department of Energy as part of the Class II and Class III Oil Programs for shallow shelf carbonate (SSC) reservoirs and slope/basin clastic (SBC) reservoirs. The technique described in this paper has also been used to characterize a wide range of other carbonate and sandstone reservoirs including tight gas sands (Wilcox, Vicksburg, and Cotton Valley Formations, Texas), moderate porosity sandstones (Middle Magdalena Valley, Colombia and San Jorge Basin, Argentina), and high porosity reservoirs (Offshore Gulf Coast and Middle East). The techniques used for reservoir description in this paper meet three basic requirements that are important in mature, heterogeneous fields.The reservoir descriptions are log-based. Flow units are identified using wireline logs because few wells have cores. Integration of data from analysis of cores is an essential component of the log models.Accurate values of permeability are derived from logs. In complex reservoirs, values of porosity and saturation derived from routine log analysis often do not accurately identify productivity. It is therefore necessary to develop a log model that will allow the prediction of another producibility parameter. In these studies we have derived foot-by-foot values of permeability for cored and non-cored intervals in all wells with suitable wireline logs.Use only the existing databases. No new wells will be drilled to aid reservoir description. Methodology Techniques of reservoir description used in these studies are based on the identification of rock types (intervals of rock with unique petrophysical properties). Rock types are identified on the basis of measured pore geometrical characteristics, principally pore body size (average diameter), pore body shape, aspect ratio (size of pore body: size of pore throat) and coordination number (number of throats per pore). This involves the detailed analysis of small rock samples taken from existing cores (conventional cores and sidewall cores). The rock type information is used to develop the vertical layering profile in cored intervals. Integration of rock type data with wireline log data allows field-wide extrapolation of the reservoir model from cored to non-cored wells. Emphasis is placed on measurement of pore geometrical characteristics using a scanning electron microscope specially equipped for automated image analysis procedures.2–4 A knowledge of pore geometrical characteristics is of fundamental importance to reservoir characterization because the displacement of hydrocarbons is controlled at the pore level; the petrophysical properties of rocks are controlled by the pore geometry.5–8 The specific procedure includes the following steps.Routine measurement of porosity and permeability.Detailed macroscopic core description to identify vertical changes in texture and lithology for all cores.Detailed thin section and scanning electron microscope analyses (secondary electron imaging mode) of 100 to 150 small rock samples taken from the same locations as the plugs used in routine core analysis. In the SBC reservoir, x-ray diffraction analysis is also used. The combination of thin section and x-ray analyses provides direct measurement of the shale volume, clay volume, grain size, sorting and mineral composition for the core samples analyzed.Rock types are identified for each rock sample using measured data on pore body size, pore throat size and pore interconnectivity (coordination number and pore arrangement).

scholarly journals Analysis of the relationship between porosity and permeability in reservoir modeling using the petrophysical rock type approach

2020 ◽  
Vol 1 (1) ◽  
pp. 48-55
Author(s):  
Lena Maretha Salindeho
Keyword(s):  
Gamma Ray ◽  
Water Saturation ◽  
Rock Type ◽  
Carbonate Reservoir ◽  
Reservoir Modeling ◽  
Hydrocarbon Production ◽  
Rock Types ◽  
Porosity And Permeability ◽  
Hydrocarbon Fields ◽  
Reef Platform

The carbonate reservoir is one of the reservoir characters found in hydrocarbon fields in Indonesia. Carbonate reservoirs have complex porosity and permeability relationships. So it is necessary to do a special reservoir character that is different from the siliciclastic reservoir. Efforts that can be made to assist the development of this hydrocarbon field are to analyze the reservoir character in more detail using the petrophysical rock type (PRT) approach. This approach is used by combining geological elements such as the depositional environment, the petrophysical properties of the rock, as well as the fluid flow in it which is reflected by capillary pressure and water saturation. Modeling with this method is expected to be a method that can increase hydrocarbon production optimally in Xena Field. The object of research from Xena Field is Zone A2 which is included in the Parigi Formation. The Parigi Formation is one of the main hydrocarbon-producing reservoirs. The data used in this study are routine core analysis (RCAL) rock data on JLB-07, JLB-08, JLB-02, JLB-23 wells, wire log data (gamma-ray log, resistivity log, density log, neutron log) of 30 wells, and 2D seismic data. The depositional facies are divided into 2 facies, namely the margin reef platform facies and the interior platform facies. Identification of rock type (RT) using the flow zone indicator (FZI) method. The rock type in this field can be divided into 4 rock types, namely RT 1, RT 2, RT 3, RT 4 with RT 1 being able to drain the best fluid and RT 4 to drain the worst fluid. Reservoir property modeling is controlled by facies and rock type (RT) models. The margin reef platform facies are associated with RT 1 and RT 2. The interior platform facies are associated with RT 2 and RT 3.

scholarly journals An Integrated Microfacies and Well Logs-Based Reservoir Characterization of Yamama Formation, Southern Iraq

2021 ◽  
pp. 3570-3586
Author(s):  
Mohanad M. Al-Ghuribawi ◽  
Rasha F. Faisal
Keyword(s):  
Reservoir Characterization ◽  
Water Saturation ◽  
Effective Porosity ◽  
Well Logs ◽  
Petrophysical Properties ◽  
Reservoir Properties ◽  
Thin Sections ◽  
Porosity And Permeability ◽  
South Of Iraq ◽  
Southern Iraq

     The Yamama Formation includes important carbonates reservoir that belongs to the Lower Cretaceous sequence in Southern Iraq. This study covers two oil fields (Sindbad and Siba) that are distributed Southeastern Basrah Governorate, South of Iraq. Yamama reservoir units were determined based on the study of cores, well logs, and petrographic examination of thin sections that required a detailed integration of geological data and petrophysical properties. These parameters were integrated in order to divide the Yamama Formation into six reservoir units (YA0, YA1, YA2, YB1, YB2 and YC), located between five cap rock units. The best facies association and petrophysical properties were found in the shoal environment, where the most common porosity types were the primary (interparticle) and secondary (moldic and vugs) . The main diagenetic process that occurred in YA0, YA2, and YB1 is cementation, which led to the filling of pore spaces by cement and subsequently decreased the reservoir quality (porosity and permeability). Based on the results of the final digital  computer interpretation and processing (CPI) performed by using the Techlog software, the units YA1 and YB2 have the best reservoir properties. The unit YB2 is characterized by a good effective porosity average, low water saturation, good permeability, and large thickness that distinguish it from other reservoir units.

scholarly journals Petrophysical Properties of Nahr Umar Formation in Nasiriya Oil Field

2020 ◽  
Vol 21 (3) ◽  
pp. 9-18
Author(s):  
Ahmed Abdulwahhab Suhail ◽  
Mohammed H. Hafiz ◽  
Fadhil S. Kadhim
Keyword(s):  
Gamma Ray ◽  
Water Saturation ◽  
Oil Field ◽  
Well Logs ◽  
High Porosity ◽  
Reservoir Properties ◽  
Petrophysical Parameters ◽  
Resistivity Logs ◽  
Lithology Prediction ◽  
Porosity And Permeability

   Petrophysical characterization is the most important stage in reservoir management. The main purpose of this study is to evaluate reservoir properties and lithological identification of Nahr Umar Formation in Nasiriya oil field. The available well logs are (sonic, density, neutron, gamma-ray, SP, and resistivity logs). The petrophysical parameters such as the volume of clay, porosity, permeability, water saturation, were computed and interpreted using IP4.4 software. The lithology prediction of Nahr Umar formation was carried out by sonic -density cross plot technique. Nahr Umar Formation was divided into five units based on well logs interpretation and petrophysical Analysis: Nu-1 to Nu-5. The formation lithology is mainly composed of sandstone interlaminated with shale according to the interpretation of density, sonic, and gamma-ray logs. Interpretation of formation lithology and petrophysical parameters shows that Nu-1 is characterized by low shale content with high porosity and low water saturation whereas Nu-2 and Nu-4 consist mainly of high laminated shale with low porosity and permeability. Nu-3 is high porosity and water saturation and Nu-5 consists mainly of limestone layer that represents the water zone.

Reservoir Quality of the Miocene Formation Gas Deposits, Onshore Abu Dhabi

2021 ◽  
Author(s):  
Catherine Breislin ◽  
Laura Galluccio ◽  
Kate Al Tameemi ◽  
Riaz Khan ◽  
Atef Abdelaal
Keyword(s):  
Depositional Environment ◽  
Middle Miocene ◽  
Quality Analysis ◽  
Reservoir Quality ◽  
Carbonate Facies ◽  
Pore System ◽  
Thin Sections ◽  
Reservoir Architecture ◽  
Porosity And Permeability ◽  
Permeability Anisotropy

Abstract Understanding reservoir architecture is key to comprehend the distribution of reservoir quality when evaluating a field's prospectivity. Renewed interest in the tight, gas-rich Middle Miocene anhydrite intervals (Anh-1, Anh-2, Anh-3, Anh-4 and Anh-6) by ADNOC has given new impetus to improving its reservoir characterisation. In this context, this study provides valuable new insights in geological knowledge at the field scale within a formation with limited existing studies. From a sedimentological point of view, the anhydrite layers of the Miocene Formation, Anh-1, Anh-2, Anh-3, Anh-4 and Anh-6 (which comprise three stacked sequences: Bur1, Bur2 and Bur3; Hardenbol et al., 1998), have comparable depositional organisation throughout the study area. Bur1 and Bur2 are characterised by an upward transition from intertidal-dominated deposits to low-energy inner ramp-dominated sedimentation displaying reasonably consistent thickness across the area. Bur3 deposits imply an initial upward deepening from an argillaceous intertidal-dominated to an argillaceous subtidal-dominated setting, followed by an upward shallowing into intertidal and supratidal sabkha-dominated environments. This Bur3 cycle thickens towards the south-east due to a possible deepening, resulting in the subtle increase in thickness of the subtidal and intertidal deposits occurring around the maximum-flooding surface. The interbedded relationship between the thin limestone and anhydrite layers within the intertidal and proximal inner ramp deposits impart strong permeability anisotropy, with the anhydrite acting as significant baffles to vertical fluid flow. A qualitative reservoir quality analysis, combining core sedimentology data from 10 wells, 331 CCA data points, 58 thin-sections and 10 SEM samples has identified that reservoir layers Anh-4 and Anh-6 contain the best porosity and permeability values, with the carbonate facies of the argillaceous-prone intertidal and distal inner ramp deposits hosting the best reservoir potential. Within these facies, the pore systems within the carbonate facies are impacted by varying degrees of dolomitisation and dissolution which enhance the pore system, and cementation (anhydrite and calcite), which degrade the pore system. The combination of these diagenetic phases results in the wide spread of porosity and permeability data observed. The integration of both the sedimentological features and diagenetic overprint of the Middle Miocene anhydrite intervals shows the fundamental role played by the depositional environment in its reservoir architecture. This study has revealed the carbonate-dominated depositional environment groups within the anhydrite stratigraphic layers likely host both the best storage capacity and flow potential. Within these carbonate-dominated layers, the thicker, homogenous carbonate deposits would be more conducive to vertical and lateral flow than thinner interbedded carbonates and anhydrites, which may present as baffles or barriers to vertical flow and create significant permeability anisotropy.

Factors Controlling Porosity Permeability Relationship for Reservoir Quality Prediction: A Case Study of Malay Basin Reservoir, Malaysia

2021 ◽  
Author(s):  
Fadzlin Hasani Kasim ◽  
Budi Priyatna Kantaatmadja ◽  
Wan Nur Wan M Zainudin ◽  
Amita Ali ◽  
Hasnol Hady Ismail ◽  
...  
Keyword(s):  
Reservoir Characterization ◽  
Visual Analysis ◽  
Mineral Dissolution ◽  
Rock Properties ◽  
Reservoir Quality ◽  
Hydrocarbon Potential ◽  
Lower Grade ◽  
Reservoir Properties ◽  
Reservoir Evaluation ◽  
Porosity And Permeability

Abstract Predicting the spatial distribution of rock properties is the key to a successful reservoir evaluation for hydrocarbon potential. However, a reservoir with a complex environmental setting (e.g. shallow marine) becomes more challenging to be characterized due to variations of clay, grain size, compaction, cementation, and other diagenetic effects. The assumption of increasing permeability value with an increase of porosity may not be always the case in such an environment. This study aims to investigate factors controlling the porosity and permeability relationships at Lower J Reservoir of J20, J25, and J30, Malay Basin. Porosity permeability values from routine core analysis were plotted accordingly in four different sets which are: lithofacies based, stratigraphic members based, quartz volume-based, and grain-sized based, to investigate the trend in relating porosity and permeability distribution. Based on petrographical studies, the effect of grain sorting, mineral type, and diagenetic event on reservoir properties was investigated and characterized. The clay type and its morphology were analyzed using X-ray Diffractometer (XRD) and Spectral electron microscopy. Results from porosity and permeability cross-plot show that lithofacies type play a significant control on reservoir quality. It shows that most of the S1 and S2 located at top of the plot while lower grade lithofacies of S41, S42, and S43 distributed at the middle and lower zone of the plot. However, there are certain points of best and lower quality lithofacies not located in the theoretical area. The detailed analysis of petrographic studies shows that the diagenetic effect of cementation and clay coating destroys porosity while mineral dissolution improved porosity. A porosity permeability plot based on stratigraphic members showed that J20 points located at the top indicating less compaction effect to reservoir properties. J25 and J30 points were observed randomly distributed located at the middle and bottom zone suggesting that compaction has less effect on both J25 and J30 sands. Lithofacies description that was done by visual analysis through cores only may not correlate-able with rock properties. This is possibly due to the diagenetic effect which controls porosity and permeability cannot visually be seen at the core. By incorporating petrographical analysis results, the relationship between porosity, permeability, and lithofacies can be further improved for better reservoir characterization. The study might change the conventional concept that lower quality lithofacies does not have economic hydrocarbon potential and unlock more hydrocarbon-bearing reserves especially in these types of environmental settings.

Rock Typing as an Effective Tool for Permeability and Water-Saturation Modeling: A Case Study in a Clastic Reservoir in the Oriente Basin

2007 ◽  
Vol 10 (06) ◽  
pp. 730-739 ◽  
Author(s):  
Genliang Guo ◽  
Marlon A. Diaz ◽  
Francisco Jose Paz ◽  
Joe Smalley ◽  
Eric A. Waninger
Keyword(s):  
Relative Permeability ◽  
Reservoir Simulation ◽  
Water Saturation ◽  
Rock Type ◽  
Permeability Model ◽  
Initial Water ◽  
Rock Types ◽  
Rock Typing ◽  
Relative Permeability Curves ◽  
Clastic Reservoirs

Summary In clastic reservoirs in the Oriente basin, South America, the rock-quality index (RQI) and flow-zone indicator (FZI) have proved to be effective techniques for rock-type classifications. It has long been recognized that excellent permeability/porosity relationships can be obtained once the conventional core data are grouped according to their rock types. Furthermore, it was also observed from this study that the capillary pressure curves, as well as the relative permeability curves, show close relationships with the defined rock types in the basin. These results lead us to believe that if the rock type is defined properly, then a realistic permeability model, a unique set of relative permeability curves, and a consistent J function can be developed for a given rock type. The primary purpose of this paper is to demonstrate the procedure for implementing this technique in our reservoir modeling. First, conventional core data were used to define the rock types for the cored intervals. The wireline log measurements at the cored depths were extracted, normalized, and subsequently analyzed together with the calculated rock types. A mathematical model was then built to predict the rock type in uncored intervals and in uncored wells. This allows the generation of a synthetic rock-type log for all wells with modern log suites. Geostatistical techniques can then be used to populate the rock type throughout a reservoir. After rock type and porosity are populated properly, the permeability can be estimated by use of the unique permeability/porosity relationship for a given rock type. The initial water saturation for a reservoir can be estimated subsequently by use of the corresponding rock-type, porosity, and permeability models as well as the rock-type-based J functions. We observed that a global permeability multiplier became unnecessary in our reservoir-simulation models when the permeability model is constructed with this technique. Consistent initial-water-saturation models (i.e., calculated and log-measured water saturations are in excellent agreement) can be obtained when the proper J function is used for a given rock type. As a result, the uncertainty associated with volumetric calculations is greatly reduced as a more accurate initial-water-saturation model is used. The true dynamic characteristics (i.e., the flow capacity) of the reservoir are captured in the reservoir-simulation model when a more reliable permeability model is used. Introduction Rock typing is a process of classifying reservoir rocks into distinct units, each of which was deposited under similar geological conditions and has undergone similar diagenetic alterations (Gunter et al. 1997). When properly classified, a given rock type is imprinted by a unique permeability/porosity relationship, capillary pressure profile (or J function), and set of relative permeability curves (Gunter et al. 1997; Hartmann and Farina 2004; Amaefule et al. 1993). As a result, when properly applied, rock typing can lead to the accurate estimation of formation permeability in uncored intervals and in uncored wells; reliable generation of initial-water-saturation profile; and subsequently, the consistent and realistic simulation of reservoir dynamic behavior and production performance. Of the various quantitative rock-typing techniques (Gunter et al. 1997; Hartmann and Farina 2004; Amaefule et al. 1993; Porras and Campos 2001; Jennings and Lucia 2001; Rincones et al. 2000; Soto et al. 2001) presented in the literature, two techniques (RQI/FZI and Winland's R35) appear to be used more widely than the others for clastic reservoirs (Gunter et al. 1997, Amaefule et al. 1993). In the RQI/FZI approach (Amaefule et al. 1993), rock types are classified with the following three equations: [equations]

Reservoir Physical Property and Controlling Factors for the Lower Youshashan Formation in Youshashan-Dawusi Area, Southwestern Qaidam Basin

2014 ◽  
Vol 675-677 ◽  
pp. 1363-1367 ◽  
Author(s):  
Guo Min Chen ◽  
Quan Wen Liu ◽  
Min Quan Xia ◽  
Xiang Sheng Bao
Keyword(s):  
Qaidam Basin ◽  
Sedimentary Environment ◽  
Physical Property ◽  
Controlling Factors ◽  
Reservoir Rock ◽  
High Porosity ◽  
Delta Front ◽  
Thin Sections ◽  
Rock Types ◽  
Porosity And Permeability

The core data, casting thin sections and scanning electron microscopy are used to study the clastic reservoir characteristics and controlling factors of reservoir growth. It indicated that the main reservoir rock types are lithic arkose, Feld spathic sandstone, and a small amount of feldspar lithic sandstone, and with compositional maturity and low to middle structural maturity. Moreover, the primary reservoir space types are mainly intergranular pores, secondary are secondary pores, and reservoir types belong to the medium-high porosity and permeability, and the average porosity and permeability of lower Youshashan formation are 17.70% and 112.5×10-3μm2 separately. Furthermore, the reservoir body is mainly sand body result from deposits of distributary channel and mouth bar of which belong to the braided delta front, and the planar physical property tends to be better reservoir to worse reservoir from northwest to southeast. Finally, mainly factors to control the distribution of reservoir physical property, are the sedimentary environment and lithology, were worked out.

scholarly journals Petrophysics Analysis for Reservoir Characterization of Upper Plover Formation in the Field “A”, Bonaparte Basin, Offshore Timor, Maluku, Indonesia

2016 ◽  
Vol 1 (1) ◽  
pp. 43 ◽  
Author(s):  
Sugeng Sapto Surjono ◽  
Indra Arifianto
Keyword(s):  
Reservoir Characterization ◽  
Water Saturation ◽  
Reservoir Rock ◽  
Reservoir Properties ◽  
Core Data ◽  
Class A ◽  
Rock Types ◽  
Rock Typing ◽  
Volume Porosity ◽  
Potential Reservoir

Hydrocarbon potential within Upper Plover Formation in the Field “A” has not been produced due to unclear in understanding of reservoir problem. This formation consists of heterogeneous reservoir rock with their own physical characteristics. Reservoir characterization has been done by applying rock typing (RT) method utilizing wireline logs data to obtain reservoir properties including clay volume, porosity, water saturation, and permeability. Rock types are classified on the basis of porosity and permeability distribution from routines core analysis (RCAL) data. Meanwhile, conventional core data is utilized to depositional environment interpretations. This study also applied neural network methods to rock types analyze for intervals reservoir without core data. The Upper Plover Formation in the study area indicates potential reservoir distributes into 7 parasequences. Their were deposited during transgressive systems in coastal environments (foreshore - offshore) with coarsening upward pattern during Middle to Late Jurassic. The porosity of reservoir ranges from 1–19 % and permeability varies from 0.01 mD to 1300 mD. Based on the facies association and its physical properties from rock typing analysis, the reservoir within Upper Plover Formation can be grouped into 4 reservoir class: Class A (Excellent), Class B (Good), Class C (Poor), and Class D (Very Poor). For further analysis, only class A-C are considered as potential reservoir, and the remain is neglected.

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