scholarly journals Hydraulic flow unit classification from core data: case study of the Z gas reservoir, Poland

2021 ◽  
Vol 62 (3) ◽  
pp. 29-36
Author(s):  
Keyword(s):  
Flow Unit ◽  
Reservoir Rock ◽  
Hydrocarbon Production ◽  
Reservoir Rocks ◽  
Hydraulic Flow ◽  
Flow Units ◽  
Porosity And Permeability ◽  
Homogeneous Section ◽  
Hydraulic Flow Units

Permeability and porosity are essential parameters for estimating hydrocarbon production from reservoir rocks. They are combined in an additional factor, the Flow Zone Index (FZI), which is the basis for defining the hydraulic flow unit (HFU). Each HFU is a homogeneous section of a reservoir rock with stable parameters that allow for media flow. Hydraulic flow units are determined from the porosity and permeability of core or well logs. The simple statistical methods are applied for HFU classification and then improve permeability prediction. This paper also shows how to quickly apply the global hydraulic elements (GHE) method for HFU classification. The methodology is tested on the Miocene formation of a deltaic facies from the Carpathian Foredeep in South-Eastern Poland.

scholarly journals New Reservoir Grading Method for Tight Gas Reservoir – One Case Study in Kekeya Block, Tuha Basin, China

2015 ◽  
Vol 8 (1) ◽  
pp. 167-171
Author(s):  
Fangfang Wu ◽  
Jinchuan Zhang ◽  
Liuzhong Li ◽  
Jinlong Wu
Keyword(s):  
Flow Unit ◽  
Reservoir Evaluation ◽  
Flow Units ◽  
Core Dataset ◽  
Tight Gas Reservoir ◽  
Set Up ◽  
Productivity Prediction ◽  
Hydraulic Flow Units ◽  
New Reservoir

Tight sand reservoir is usually characterized by high heterogeneity and complex pore structure, which makes the permeability calculation a big challenge and leads to difficulties in reservoir classification and productivity evaluation. First, five different Hydraulic Flow Units and respective Porosity-permeability relations were built based on core dataset from Kekeya block, Tuha Basin; and then with BP Neutron Network method, flow unit was classified for un-cored intervals using normalized logging data, and permeability was calculated accordingly. This improved the accuracy of permeability calculation and helped a lot on un-cored reservoir evaluation. In addition, based on porosity, permeability and flow unit type, a new reservoir grading chart was set up by incorporating the testing or production data, which provides important guidance for productivity prediction and reservoir development.

scholarly journals Application of Seismic Attribute Technique to estimate the 3D model of Hydraulic Flow Units: A case study of a gas field in Iran

2018 ◽  
Vol 27 (2) ◽  
pp. 145-157 ◽  
Author(s):  
Mohamad Iravani ◽  
Mahdi Rastegarnia ◽  
Dariush Javani ◽  
Ali Sanati ◽  
Seyed Hasan Hajiabadi
Keyword(s):  
3D Model ◽  
Seismic Attribute ◽  
Gas Field ◽  
Hydraulic Flow ◽  
Flow Units ◽  
Hydraulic Flow Units

scholarly journals KLASIFIKASI PETROFISIKA TIPE BATUAN UNTUK MEMPREDIKSI KUALITAS RESERVOAR PASIR SERPIHAN PADA FORMASI TALANG AKAR, CEKUNGAN ONWJ

2020 ◽  
Vol 4 (3) ◽  
pp. 28-40
Author(s):  
Feni Priyanka ◽  
Ordas Dewanto ◽  
Bagus Sapto Mulyatno ◽  
Riezal Ariffiandhany
Keyword(s):  
Property Values ◽  
Type Method ◽  
Reservoir Rocks ◽  
Petrophysical Property ◽  
Flow Units ◽  
A Value ◽  
Geological Conditions ◽  
Porosity And Permeability ◽  
Hydraulic Flow Units

Hydrocarbons were accumulated in reservoir, the reservoir has a lot of types depending on the geological conditions and the constituent mineral. In ONWJ basins, sub-basins Arjuna, Talang Akar Formation is sand splintersreservoir type. The presence of clay in a reservoir will reduce the resistivity and increase thesaturation, so it takes a multimineral analysis and the reservoir qualityclassification. In this study, physical properties (porosity, permeability, Rw, and saturation) and the quality of the reservoir can be identified through petrophysical analysis by utilizing log data and core analysis, and the rocktypeprediction(using R35 Winland or HFU method). In this study 5 wells (IX-A1, IX-13, IX-4, IX-7 and IX-8)used and found eight hydrocarbon zones, 6 are validated by the DST (drill steam test)data, androck type method that suitable is the method of HFU (hydraulic flow units) due to the coefficient of correlation between porosity and permeability shows a value of 0.75, based on the calculations, the eight types of rock is conclude, where the dominance of the rock typeis the type 12 with a pore size between 5-10 microns, type reservoir rocks in this study belong to the lithofacies distributary channel and mouthbar sand. By knowing the petrophysical property values, it can determine reservoir productivity and determine the zone eligible to be produced or not, by using curve SMLP (Stratigraphic Modified Lorenz Plot).

Integrating XRD and Well Logging Data to Establish Electro-Facies and Permeability Models for an Unconventional Heterogeneous Tight Gas Reservoir, Obaiyed Giant Gas Field

2021 ◽  
Author(s):  
Ibrahim Mabrouk
Keyword(s):  
Development Strategy ◽  
Flow Unit ◽  
Petrographic Analysis ◽  
Production Forecast ◽  
Gas Field ◽  
Hydraulic Flow ◽  
Heterogeneous Reservoirs ◽  
Flow Units ◽  
Tight Gas Reservoir ◽  
Hydraulic Flow Units

Abstract Formation evaluation in heterogeneous reservoirs can be very challenging especially in fields that extend over several kilometers in area where the permeability varies from 0.1 mD up to 1000 D within the same porosity. The porosity, hydrocarbon saturation and net sand thickness in most of Obaiyed field wells are consistent; hence, the productivity of these wells is enormously dependent on the reservoir permeability. Since the permeability is highly heterogeneous, initial production rate of the wells varies between few MMSCFD to almost one hundred MMSCFD. The huge permeability variation led to a tremendous uncertainty in the dynamic modeling, which resulted in an inaccurate production forecast affecting the field economics estimation. Understanding permeability distribution and heterogeneity in Obaiyed field is the key factor for establishing a realistic permeability model, which will lead to a successful field development strategy. Extensive work was performed to understand key factors that govern the permeability in Obaiyed using the data of 1-kilometer length of cores acquired in more than 50 wells covering different reservoir properties in the field. Core data were used to separate the reservoir into different Hydraulic Flow Units (HFU) according to Amaefule's work performed on the Kozeny-Carmen model. Afterwards, a correlation between the HFU and well logs was established using IPSOM Electro-Facies module in order to define the flow units in un-cored wells. The result of this correlation was used to calibrate a Porosity-Permeability relationship for each flow unit. The next step was examining the clay-type distribution and diagenesis in each flow unit using the petrographic analysis (XRD) results from the core xdata. All factors controlling the permeability can now be represented in hydraulic flow units which are considered as a method of measurement of the reservoir quality. Consequently, property maps were constructed showing the location and continuity of each of the flow units, leading to a more deterministic approach in the well placement process. Based on this new work methodology, a production cut-off criteria relating the reservoir productivity to both clay minerals presence and percentages was established for multiple wells scenarios. As a result, the development strategy of the field changed from only vertical wells to include horizontal wells as well which proved to be the only economic approach to produce the Illite dominated zones. This paper presents a workflow to provide a representative estimation of permeability in extremely heterogeneous reservoirs especially the ones dominated by complex clay distribution.

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