reservoir zonation
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2022 ◽  
Vol 12 (1) ◽  
Author(s):  
Mimonitu Opuwari ◽  
Blessing Afolayan ◽  
Saeed Mohammed ◽  
Paschal Ogechukwu Amaechi ◽  
Youmssi Bareja ◽  
...  

AbstractThis study aims to generate rock units based on core permeability and porosity of OW oilfield in the Bredasdorp Basin offshore South Africa. In this study, we identified and classified lithofacies based on sedimentology reports in conjunction with well logs. Lucia's petrophysical classification method is used to classify rocks into three classes. Results revealed three lithofacies as A (sandstone, coarse to medium-grained), B (fine to medium-grained sandstone), and C (carbonaceous claystone, finely laminated with siltstone). Lithofacies A is the best reservoir quality and corresponds to class 1, while lithofacies B and C correspond to class 2 and 3, which are good and poor reservoir quality rock, respectively. An integrated reservoir zonation for the rocks is based on four different zonation methods (Flow Zone indicator (FZI), Winland r35, Hydraulic conductivity (HC), and Stratigraphy modified Lorenz plot (SMLP)). Four flow zones Reservoir rock types (RRTs) were identified as RRT1, RRT3, RRT4, and RRT5, respectively. The RRT5 is the best reservoir quality composed of a megaporous rock unit, with an average FZI value between 5 and 10 µm, and HC from 40 to 120 mD/v3, ranked as very good. The most prolific flow units (RRT5 and RRT4 zones) form more than 75% of each well's flow capacities are supplied by two flow units (FU1 and FU3). The RRT1 is the most reduced rock quality composed of impervious and nanoporous rock. Quartz is the dominant framework grain, and siderite is the dominant cement that affects flow zones. This study has demonstrated a robust approach to delineate flow units in the OW oilfield. We have developed a useful regional petrophysical reservoir rock flow zonation model for clastic reservoir sediments. This study has produced, for the first time, insights into the petrophysical properties of the OW oilfield from the Bredasdorp Basin South Africa, based on integration of core and mineralogy data. A novel sandstone reservoir zonation classification criteria developed from this study can be applied to other datasets of sandstone reservoirs with confidence.


2021 ◽  
Author(s):  
Mimonitu Opuwari ◽  
Blessing Afolanyan ◽  
Saeed Mohammed ◽  
Paschal Ogechukwu Amaechi ◽  
Y Bareja ◽  
...  

Abstract This study aims to generate rock units based on core permeability and porosity of an oil field in the Bredasdorp Basin offshore South Africa. In this study, we identified and classified lithofacies based on sedimentology reports in conjunction with well logs. Lucia's petrophysical classification method is used to classify rocks into three classes. Results revealed three lithofacies as A(sandstone, coarse to medium-grained), B (fine to medium-grained sandstone), and C (carbonaceous claystone, finely laminated with siltstone). Lithofacies A is the best reservoir quality and corresponds to class 1, while lithofacies B and C correspond to class 2 and 3, which are good and poor reservoir quality rock, respectively. An integrated reservoir zonation for the rocks is based on four different zonation methods (Flow Zone indicator (FZI), Winland r35, Hydraulic conductivity (HC), and Stratigraphy modified Lorenz plot (SMLP)). Four flow zones were identified as high(HFZ), moderate (MFZ), Low (LFZ), and tight (TFZ), respectively. The HFZ is the best reservoir quality composed of a megaporous rock unit, with an average FZI value between 5 to 10µm, and HC from 40 to 120 mD/v3, ranked as very good. The most prolific flow units (HFZ and MFZ zones) form more than 75 % of each well's flow capacities. The TFZ is the most reduced rock quality composed of impervious and nanoporous rock. There appears to be a slight increase of illite in the tight and low zones that block pore throats, thereby decreasing permeability. Therefore, illite has a dominant effect on flow zones. Quartz is the dominant framework grain, and siderite is the dominant cement that affects flow zones. This study has demonstrated a robust approach to delineate flow units in an oilfield. A novel sandstone reservoir zonation classification criteria developed from this study can be applied to other datasets of sandstone reservoirs with confidence.


2021 ◽  
Vol 26 (1) ◽  
pp. 143-150
Author(s):  
Randi FItriadi ◽  
Niken Tunjung Murti Pratiwi ◽  
Rahmat Kurnia

Jatigede reservoir is a new reservoir in West Java Province. There is not much information about phytoplankton and nutrients in this reservoir. The aim of the research was to study the relationship between phytoplankton community and nutrient in the reservoir. The research was conducted during the dry season, from September to October 2018. Analyzed parameters were phytoplankton abundance, diversity and dominance index, orthophosphate, nitrite, nitrate, and ammonium. Reservoir zonation was divided by cluster analysis. The relationship between phytoplankton and nutrients was analyzed by principal component analysis and Pearson’s correlation test. Phytoplankton in Jatigede Reservoir consisted of Bacillariophyceae, Chlorophyceae, Cyanophycea, Dinophyceae, and Euglenophyceae within 20333‒25308 cell/L. Nitrate concentration ranged within 0.6684‒3.6115 mg/L. Nitrite concentration ranged between 0.0544‒0.2301 mg/L and ammonium ranged within 0.00538‒0.2460 mg/L. The strongest correlation between phytoplankton and nutrients were shown by Cyanophyceae and Dinophyceae, especially with the concentration of orthophosphate, nitrate, nitrite, and ammonium (r > 0,78).   Keywords: Cyanophyceae, orthophosphate, nitrate, nitrite


2019 ◽  
Vol 25 (12) ◽  
pp. 49-61
Author(s):  
Adnan Ajam Abed ◽  
Sammer Mohammed Hamd-Allah

Characterization of the heterogonous reservoir is complex representation and evaluation of petrophysical properties and application of the relationships between porosity-permeability within the framework of hydraulic flow units is used to estimate permeability in un-cored wells. Techniques of flow unit or hydraulic flow unit (HFU) divided the reservoir into zones laterally and vertically which can be managed and control fluid flow within flow unit and considerably is entirely different with other flow units through reservoir. Each flow unit can be distinguished by applying the relationships of flow zone indicator (FZI) method. Supporting the relationship between porosity and permeability by using flow zone indictor is carried out for evaluating the reservoir quality and identification of flow unit used in reservoir zonation.  In this study, flow zone indicator has been used to identify five layers belonging to Tertiary reservoirs. Consequently, the porosity-permeability cross plot has been done depending on FZI values as groups and for each group denoted to reservoir rock types. On the other hand, extending rock type identification in un-cored wells should apply a cluster analysis approach by using well logs data. Reservoir zonation has been achieved by cluster analysis approach and for each group known as cluster which variation and different with others. Five clusters generated in this study and permeability estimated depend on these groups in un-cored wells by using well log data that gives good results compared with different empirical methods.


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