Determination of Reservoir Permeability Based on Irreducible Water Saturation and Porosity from Log Data and FZI (Flow Zone Indicator) from Core Data

2014 ◽  
Author(s):  
M. Fazel Alavi ◽  
M. Fazel Alavi ◽  
M. Fazel Alavi
Keyword(s):  
Water Saturation ◽  
Flow Zone ◽  
Log Data ◽  
Core Data ◽  
Reservoir Permeability ◽  
Irreducible Water Saturation

Defining irreducible water saturation using global characteristics envelopes and novel correlations

2016 ◽  
Vol 56 (1) ◽  
pp. 1 ◽  
Author(s):  
Peter Behrenbruch ◽  
Chengzhi Yuan ◽  
Nhan B. Truong ◽  
Phil Do Huu ◽  
Tuan G. Hoang
Keyword(s):  
Grain Size ◽  
Pore Structure ◽  
Water Saturation ◽  
Laboratory Data ◽  
Great Promise ◽  
Flow Zone ◽  
Structure Characteristics ◽  
Irreducible Water Saturation ◽  
Universal Correlation ◽  
Group Flow

Irreducible water saturation plays a significant role in estimating hydrocarbon initially-in-place and petroleum recovery. Yet, laboratory measurements for determining irreducible water saturation take considerable time and money. For this reason available data may not cover all requirements, giving rise to the practise of using correlations to fill in gaps. Described in this paper are the reasons for irreducible water saturation being an elusive parameter that not only depends on pore structure characteristics but also the type of experiment and laboratory procedures, as well as changing plug conditions during experimentation. This paper reviews traditional methods, as well as recent and novel approaches to quality assure laboratory data and for correlating irreducible water saturation for prediction. To gain insight into the dependence of irreducible water saturation on detailed pore structure characteristics, most notably grain size and sorting, the usefulness of global characteristics envelopes is explored (Behrenbruch and Biniwale, 2005). In this multidimensional plot, irreducible water saturation is plotted against porosity, permeability, hydraulic radius, porosity group, flow zone indicator (grain size) and sorting, giving an insightful overview of the interdependence of parameters. The second part of this paper compares novel correlations with commonly used correlations. Traditional and more recent correlations are covered, from simple correlations versus the logarithm of permeability to more sophisticated approaches using more variables, including porosity and others. Most notably, it is shown that an approach of correlating irreducible water saturation with grain size (or flow zone indicator [FZI]) and sorting shows great promise. Data from two Australian fields are used to demonstrate the methodology, showing a significant increase in fitting accuracy. This approach may eventually lead to a universal correlation.

scholarly journals Permeability Determination of Tertiary Reservoir/Ajeel Oil Field

2020 ◽  
Vol 26 (7) ◽  
pp. 206-216
Author(s):  
Rihab Abbass Deabl ◽  
Ahmad A. Ramadhan ◽  
AbdulAali A. Aldabaj
Keyword(s):  
Neural Network ◽  
Economic Value ◽  
Oil Field ◽  
The Other ◽  
Log Data ◽  
Neural Network Method ◽  
Core Data ◽  
The Neural Network ◽  
Network Method

This paper discusses the method for determining the permeability values of Tertiary Reservoir in Ajeel field (Jeribe, dhiban, Euphrates) units and this study is very important to determine the permeability values that it is needed to detect the economic value of oil in Tertiary Formation. This study based on core data from nine wells and log data from twelve wells. The wells are AJ-1, AJ-4, AJ-6, AJ-7, AJ-10, AJ-12, AJ-13, AJ-14, AJ-15, AJ-22, AJ-25, and AJ-54, but we have chosen three wells (AJ4, AJ6, and AJ10) to study in this paper. Three methods are used for this work and this study indicates that one of the best way of obtaining permeability is the Neural network method because the values of permeability obtained being much closer to the values of K-core than the other methods. From this study we obtained many values of permeability for all depths from top to bottom for three wells in Ajeel Field as explained by figures below.

SATURATION EXPONENT AS A FUNCTION OF RESERVOIR HETEROGENEITY AND WETTABILITY IN THE TAMBAREDJO OIL FIELD, SURINAME

2021 ◽  
Author(s):  
Elias R. Acosta ◽  
◽  
Bhagwanpersad Nandlal ◽  
Ryan Harripersad ◽  
◽  
...  
Keyword(s):  
Oil Recovery ◽  
Water Saturation ◽  
Variable Parameter ◽  
Oil Field ◽  
High Resistivity ◽  
Reservoir Properties ◽  
Core Data ◽  
The Core ◽  
Irreducible Water Saturation ◽  
Saturation Exponent

This research proposed an alternative method for determining the saturation exponent (n) by finding the best correlations for the heterogeneity index using available core data and considering wettability changes. The log curves of the variable n were estimated, and the effect on the water saturation (Sw) calculations and the Stock Tank Oil Initially In Place (STOIIP) in the Tambaredjo (TAM) oil field was analyzed. Core data were employed to obtain the relationship between n and heterogeneity using cross-plots against several heterogeneity indices, reservoir properties, and pore throat size. After filtering the data, the clay volume (Vcl), shale volume, silt volume, basic petrophysical property index (BPPI), net reservoir index, pore grain volume ratio, and rock texture were defined as the best matches. Their modified/improved equations were applied to the log data and evaluated. The n related to Vcl was the best selection based on the criteria of depth variations and logical responses to the lithology. The Sw model in this field showed certain log readings (high resistivity [Rt] reading ≥ 500 ohm.m) that infer these intervals to be probable inverse-wet (oil-wet). The cross-plots (Rt vs. Vcl; Rt vs. density [RHOB]; Rt vs. total porosity [PHIT]) were used to discard the lithologies related to a high Rt (e.g., lignites and calcareous rocks) and to correct Sw when these resulted in values below the estimated irreducible water saturation (Swir). The Sw calculations using the Indonesian equation were updated to incorporate n as a variable (log curves), comparing it with Sw from the core data and previous calculations using a fixed average value (n = 1.82) from the core data. An integrated approach was used to determine n, which is related to the reservoir’s heterogeneity and wettability changes. The values of n for high Rt (n > 2) intervals ranged from 2.3 to 8.5, which is not close to the field average n value (1.82). Specific correlations were found by discriminating Swir (Swir < 15%), (Swir 15%–19%), and Swir (> 19%). The results showed that using n as a variable parameter improved Sw from 39.5% to 36.5% average in the T1 and T2 sands, showing a better fit than the core data average and increasing the STOIIP estimations by 6.81%. This represents now a primary oil recovery of 12.1%, closer to the expected value for these reservoirs. Although many studies have been done on n determination and its effect on Sw calculations, using average values over a whole field is still a common practice regardless of heterogeneity and wettability considerations. This study proposed a method to include the formation of heterogeneity and wettability changes in n determination, allowing a more reliable Sw determination as demonstrated in the TAM oil field in Suriname.

An Approach for Exploring the Application of the Flow Zone Index Concept in Describing Petrophysical Properties Using Available SCAL Data Relative Permeability

2021 ◽  
Author(s):  
Efeoghene Enaworu ◽  
Tim Pritchard ◽  
Sarah J. Davies
Keyword(s):  
Relative Permeability ◽  
Water Saturation ◽  
Petrophysical Properties ◽  
Residual Oil ◽  
Flow Zone ◽  
Oil Saturation ◽  
Residual Oil Saturation ◽  
Core Samples ◽  
Irreducible Water Saturation ◽  
Permeability Data

Abstract This paper describes a unique approach for exploring the Flow Zone Index (FZI) concept using available relative permeability data. It proposes an innovative routine for relating the FZI parameter to saturation end-points of relative permeability data and produces a better model for relative permeability curves. In addition, this paper shows distinct wettabilities for various core samples and validated functions between FZI and residual oil saturation (Sor), irreducible water saturation (Swi), maximum oil allowed to flow (Kro, max), maximum water allowed to flow (Krw, max),and mobile/recoverable oil (100-Swi-Sor). The wettability of the core samples were defined using cross-plots of relative permeability of oil (Kro), relative permeability of water (Krw), and water saturation (Sw). After classifying the data sets into their respective wettabilities based on these criteria, a stepwise non-linear regression analysis was undertaken to develop realistic correlations between the FZI parameter, initial water saturation and end-point relative permeability parameters. In addition, a correlation using Corey's type generalised model was developed using relative permeability data, with new power law constants and well defined curves. Other parameters, including Sor, Swi, Kro, max, Krw,max and mobile oil, were plotted against FZI and correlations developed for them showed unique well behaved plots with the exception of the Sor plot. A possible theory to explain this unexpected behaviour of the FZI Vs Sor cross plot was noted and discussed. These derived functions and established relationships between the FZI term and other petrophysical parameters such as permeability, porosity, water saturation, relative permeability and residual oil saturation can be applied to other wells or reservoir models where these key parameters are already known or unknown. These distinctive established correlations could be employed in the proper characterization of a reservoir as well as predicting and ground truthing petrophysical properties.

Determination of Irreducible Water Saturation and its Application in Analysing Water Producing after Fracturing

2014 ◽  
Vol 548-549 ◽  
pp. 1881-1884
Author(s):  
Xi Wen Zhang ◽  
Guang Sheng Cao ◽  
Li Juan Niu ◽  
Gui Long Wang
Keyword(s):  
Water Saturation ◽  
Bound Water ◽  
Well Water ◽  
Oil Well ◽  
Size Change ◽  
Irreducible Water Saturation ◽  
Before And After ◽  
Nonsteady State ◽  
State Method

Combining Semipermeable Diaphragm Method with Nonsteady State Method, Bound Water Saturation and Critical Water Saturation in Du 38 District of Daqing Fuyang Reservoir are Determined before and after Fracturing and Relationship between them is also Analyzed. the Results Show that the Fracture of Bound Water, have a Certain Influence Critical Water Saturation, and the Cracks of Bound Water, the Greater the Size Change the Greater the Value of Critical Water Saturation; Characteristics of Reservoir Microscopic Seepage is Analyzed, the Results Show that the Movable Water Potential Changes is the Main Cause of Oil well Water after Fracturing.

scholarly journals DETERMINATION CONVENTIONAL ROCK PROPERTIES FROM LOG DATA & CORE DATA FOR UPPER NUBIAN SANDSTONE FORMATION OF ABU ATTIFEL FIELD

2019 ◽  
Vol 2 (1) ◽  
pp. 29-37
Author(s):  
Adel Alabeed ◽  
Zeyad Ibrahim ◽  
Emhemed Alfandi
Keyword(s):  
Water Saturation ◽  
Rock Properties ◽  
Well Log ◽  
Log Data ◽  
Nubian Sandstone ◽  
Core Data ◽  
Hydrocarbon Reservoir ◽  
Fluid Saturation ◽  
Volume Porosity ◽  
Sandstone Formation

A reservoir is a subsurface rock that has effective porosity and permeability which usually contains commercially exploitable quantity of hydrocarbon. Reservoir characterization is undertaken to determine its capability to both store and transmit fluid. Petrophysical well log and core data, in this paper, were integrated in an analysis of the reservoir characteristics by selecting of three productive wells. The selected wells are located at Abu Attifel field in Libya for Upper Nubian Sandstone formation at depth varied form 12921 to14330 ft. The main aim of this study is to compare the laboratory measurement of core data with that obtained from well log data in order to determine reservoir properties such as shale volume, porosity (Φ), permeability (K), fluid saturation, net pay thickness. The plots of porosity logs and core porosity versus depth for the three wells revealed significant similarity in the porosity values. The average volume of shale for the reservoir was determined to be 22.5%, and average permeability values of the three wells are above 150 md, while porosity values ranged from 9 to 11%. Low water saturation 13 to 22% in the three wells indicates the wettability of the reservoir is water-wet.

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