A Comprehensive Approach to Assess Remaining Oil Saturation and Sweep Efficiency in a Large Carbonate Reservoir

2016 ◽  
Author(s):  
Amer M. Al-Anazi ◽  
Tareq M. Al-Zahrani ◽  
Mustafa I. Abdulmohsin
Keyword(s):  
Carbonate Reservoir ◽  
Comprehensive Approach ◽  
Sweep Efficiency ◽  
Oil Saturation ◽  
Remaining Oil

Residual Oil Saturation Determination for EOR Projects in Means Field, a Mature West Texas Carbonate Field

2012 ◽  
Vol 15 (05) ◽  
pp. 541-553 ◽  
Author(s):  
Prabodh Pathak ◽  
Dale E. Fitz ◽  
Kenneth P. Babcock ◽  
Richard J. Wachtman
Keyword(s):  
Data Acquisition ◽  
Oil Recovery ◽  
Tracer Tests ◽  
Carbonate Reservoir ◽  
Core Analysis ◽  
Residual Oil ◽  
Oil Saturation ◽  
West Texas ◽  
Remaining Oil ◽  
Data Acquisition Program

Summary The technical success of an enhanced oil recovery (EOR) project depends on two main factors: first, the reservoir remaining oil saturation (ROS) after primary and secondary operations, and second, the recovery efficiency of the EOR process in mobilizing the ROS. These two interrelated parameters must be estimated before embarking on a time-consuming and costly process for designing and implementing an EOR process. The oil saturation can vary areally and vertically within the reservoir, and the distribution of the ROS will determine the success of the EOR injectants in mobilizing the remaining oil. There are many methods for determining the oil saturation (Chang et al. 1988; Pathak et al. 1989), and these include core analysis, well-log analysis, log/inject/log (LIL) procedures (Richardson et al. 1973; Reedy 1984), and single-well chemical tracer tests (SWCTT) (Deans and Carlisle 1986). These methods have different depths of investigation and different accuracies, and they all provide valuable information about the distribution of ROS. No single method achieves the best estimate of ROS, and a combination of all these methods is essential in developing a holistic picture of oil saturation and in assessing whether the oil in place (OIP) is large enough to justify the application of an EOR process. As Teletzke et al. (2010) have shown, EOR implementation is a complex process, and a staged, disciplined approach to identifying the key uncertainties and acquiring data for alleviating the uncertainties is essential. The largest uncertainty in some cases is the ROS in the reservoir. This paper presents the results from a fieldwide data acquisition program conducted in a west Texas carbonate reservoir to estimate ROS as part of an EOR project assessment. The Means field in west Texas has been producing for more than the past 75 years, and the producing mechanisms have included primary recovery, secondary waterflooding, and the application of a CO2 EOR process. The Means field is an excellent example of how the productive life and oil recovery can be increased by the application of new technology. The Means story is one of judicious application of appropriate EOR technology to the sustained development of a mature asset. The Means field is currently being evaluated for further expansion of the EOR process, and it was imperative to evaluate the oil saturation in the lower, previously undeveloped zones. This paper briefly outlines the production history, reservoir description, and reservoir management of the Means field, but this paper concentrates on the residual oil zone (ROZ) that underlies the main producing zone (MPZ) and describes a recent data acquisition program to evaluate the oil saturation in the ROZ. We discuss three major methods for evaluating the ROS: core analysis, LIL tests, and SWCTT tests.

Assessing Fluid Migration and Quantifying Remaining Oil Saturation in a Mature Carbonate Reservoir: Dukhan Arab D

2009 ◽  
Author(s):  
Levin Jose Barrios Vera ◽  
Tajjul Muhamad Rais ◽  
Ali Trabelsi ◽  
Ibrahim Al-Qarshubi ◽  
Hussain Abdulla Al-Ansi
Keyword(s):  
Carbonate Reservoir ◽  
Fluid Migration ◽  
Oil Saturation ◽  
Remaining Oil

Oil Saturation Log Prediction Using Neural Network in New Steamflood Area

2020 ◽  
Author(s):  
A. Syahputra
Keyword(s):  
Neural Network ◽  
Water Saturation ◽  
Prediction Method ◽  
Neural Model ◽  
Training Model ◽  
Acquisition Time ◽  
Oil Saturation ◽  
Full Field ◽  
Remaining Oil ◽  
Observation Wells

Surveillance is very important in managing a steamflood project. On the current surveillance plan, Temperature and steam ID logs are acquired on observation wells at least every year while CO log (oil saturation log or SO log) every 3 years. Based on those surveillance logs, a dynamic full field reservoir model is updated quarterly. Typically, a high depletion rate happens in a new steamflood area as a function of drainage activities and steamflood injection. Due to different acquisition time, there is a possibility of misalignment or information gaps between remaining oil maps (ie: net pay, average oil saturation or hydrocarbon pore thickness map) with steam chest map, for example a case of high remaining oil on high steam saturation interval. The methodology that is used to predict oil saturation log is neural network. In this neural network method, open hole observation wells logs (static reservoir log) such as vshale, porosity, water saturation effective, and pay non pay interval), dynamic reservoir logs as temperature, steam saturation, oil saturation, and acquisition time are used as input. A study case of a new steamflood area with 16 patterns of single reservoir target used 6 active observation wells and 15 complete logs sets (temperature, steam ID, and CO log), 19 incomplete logs sets (only temperature and steam ID) since 2014 to 2019. Those data were divided as follows ~80% of completed log set data for neural network training model and ~20% of completed log set data for testing the model. As the result of neural model testing, R2 is score 0.86 with RMS 5% oil saturation. In this testing step, oil saturation log prediction is compared to actual data. Only minor data that shows different oil saturation value and overall shape of oil saturation logs are match. This neural network model is then used for oil saturation log prediction in 19 incomplete log set. The oil saturation log prediction method can fill the gap of data to better describe the depletion process in a new steamflood area. This method also helps to align steam map and remaining oil to support reservoir management in a steamflood project.

scholarly journals Enhanced Oil Recovery: Chemical Flooding

2021 ◽  
Author(s):  
Ahmed Ragab ◽  
Eman M. Mansour
Keyword(s):  
Interfacial Tension ◽  
Enhanced Oil Recovery ◽  
Oil Recovery ◽  
Recovery Phase ◽  
Mobility Ratio ◽  
Chemical Flooding ◽  
Sweep Efficiency ◽  
Oil Displacement ◽  
Remaining Oil ◽  
Oil Displacement Efficiency

The enhanced oil recovery phase of oil reservoirs production usually comes after the water/gas injection (secondary recovery) phase. The main objective of EOR application is to mobilize the remaining oil through enhancing the oil displacement and volumetric sweep efficiency. The oil displacement efficiency enhances by reducing the oil viscosity and/or by reducing the interfacial tension, while the volumetric sweep efficiency improves by developing a favorable mobility ratio between the displacing fluid and the remaining oil. It is important to identify remaining oil and the production mechanisms that are necessary to improve oil recovery prior to implementing an EOR phase. Chemical enhanced oil recovery is one of the major EOR methods that reduces the residual oil saturation by lowering water-oil interfacial tension (surfactant/alkaline) and increases the volumetric sweep efficiency by reducing the water-oil mobility ratio (polymer). In this chapter, the basic mechanisms of different chemical methods have been discussed including the interactions of different chemicals with the reservoir rocks and fluids. In addition, an up-to-date status of chemical flooding at the laboratory scale, pilot projects and field applications have been reported.

Toward Quantitative Remaining Oil Saturation (ROS): Determination Challenges and Techniques

2011 ◽  
Author(s):  
Ahmed A. Al-harbi ◽  
Denis Philippe Schmitt ◽  
Shouxiang Mark Ma
Keyword(s):  
Oil Saturation ◽  
Remaining Oil
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