New Downhole-Fluid-Analysis Tool for Improved Reservoir Characterization

2008 ◽  
Vol 11 (06) ◽  
pp. 1107-1116 ◽  
Author(s):  
Chengli Dong ◽  
Michael D. O'Keefe ◽  
Hani Elshahawi ◽  
Mohamed Hashem ◽  
Stephen M. Williams ◽  
...  
Keyword(s):  
Real Time ◽  
Hydrocarbon Composition ◽  
Fluid Composition ◽  
Fluid Sample ◽  
Fluid Analysis ◽  
Reservoir Fluid ◽  
Reservoir Conditions ◽  
Fluid Properties ◽  
Fluid Characterization ◽  
Compositional Grading

Summary Downhole fluid analysis (DFA) has emerged as a key technique for characterizing the distribution of reservoir-fluid properties and determining zonal connectivity across the reservoir. Information from profiling the reservoir fluids enables sealing barriers to be proved and compositional grading to be quantified; this information cannot be obtained from conventional wireline logs. The DFA technique has been based largely on optical spectroscopy, which can provide estimates of filtrate contamination, gas/oil ratio (GOR), pH of formation water, and a hydrocarbon composition in four groups: methane (C1), ethane to pentane (C2-5), hexane and heavier hydrocarbons (C6+), and carbon dioxide (CO2). For single-phase assurance, it is possible to detect gas liberation (bubblepoint) or liquid dropout (dewpoint) while pumping reservoir fluid to the wellbore, before filling a sample bottle. In this paper, a new DFA tool is introduced that substantially increases the accuracy of these measurements. The tool uses a grating spectrometer in combination with a filter-array spectrometer. The range of compositional information is extended from four groups to five groups: C1, ethane (C2), propane to pentane (C3-5), C6+, and CO2. These spectrometers, together with improved compositional algorithms, now make possible a quantitative analysis of reservoir fluid with greater accuracy and repeatability. This accuracy enables comparison of fluid properties between wells for the first time, thus extending the application of fluid profiling from a single-well to a multiwall basis. Field-based fluid characterization is now possible. In addition, a new measurement is introduced--in-situ density of reservoir fluid. Measuring this property downhole at reservoir conditions of pressure and temperature provides important advantages over surface measurements. The density sensor is combined in a package that includes the optical spectrometers and measurements of fluid resistivity, pressure, temperature, and fluorescence that all play a vital role in determining the exact nature of the reservoir fluid. Extensive tests at a pressure/volume/temperature (PVT) laboratory are presented to illustrate sensor response in a large number of live-fluid samples. These tests of known fluid compositions were conducted under pressurized and heated conditions to simulate reservoir conditions. In addition, several field examples are presented to illustrate applicability in different environments. Introduction Reservoir-fluid samples collected at the early stage of exploration and development provide vital information for reservoir evaluation and management. Reservoir-fluid properties, such as hydrocarbon composition, GOR, CO2 content, pH, density, viscosity, and PVT behavior are key inputs for surface-facility design and optimization of production strategies. Formation-tester tools have proved to be an effective way to obtain reservoir-fluid samples for PVT analysis. Conventional reservoir-fluid analysis is conducted in a PVT laboratory, and it usually takes a long time (months) before the results become available. Also, miscible contamination of a fluid sample by drilling-mud filtrate reduces the utility of the sample for subsequent fluid analyses. However, the amount of filtrate contamination can be reduced substantially by use of focused-sampling cleanup introduced recently in the next-generation wireline formation testers (O'Keefe et al. 2008). DFA tools provide results in real time and at reservoir conditions. Current DFA techniques use absorption spectroscopy of reservoir fluids in the visible-to-near-infrared (NIR) range. The formation-fluid spectra are obtained in real time, and fluid composition is derived from the spectra on the basis of C1, C2-5, C6+, and CO2; then, GOR of the fluid is estimated from the derived composition (Betancourt et al. 2004; Fujisawa et al. 2002; Dong et al. 2006; Elshahawi et al. 2004; Fujisawa et al. 2008; Mullins et al. 2001; Smits et al. 1995). Additionally, from the differences in absorption spectrum between reservoir fluid and filtrate of oil-based mud (OBM) or water-based mud (WBM), fluid-sample contamination from the drilling fluid is estimated (Mullins et al. 2000; Fadnes et al. 2001). With the DFA technique, reservoir-fluid samples are analyzed before they are taken, and the quality of fluid samples is improved substantially. The sampling process is optimized in terms of where and when to sample and how many samples to take. Reservoir-fluid characterization from fluid-profiling methods often reveals fluid compositional grading in different zones, and it also helps to identify reservoir compartmentalization (Venkataramanan et al. 2008). A next-generation tool has been developed to improve the DFA technique. This DFA tool includes new hardware that provides more-accurate and -detailed spectra, compared to the current DFA tools, and includes new methods of deriving fluid composition and GOR from optical spectroscopy. Furthermore, the new DFA tool includes a vibrating sensor for direct measurement of fluid density and, in certain environments, viscosity. The new DFA tool provides reservoir-fluid characterization that is significantly more accurate and comprehensive compared to the current DFA technology.

Applications of Advance Downhole Fluid Analysis and Interval Pressure Transient Test for Improving Oil Reservoir Characterization: A Case Study from the East Cost of Trinidad

2014 ◽  
Author(s):  
S.. Paul ◽  
R.. Tapia ◽  
J.A.. A. Arias-Correa
Keyword(s):  
Real Time ◽  
Lessons Learned ◽  
Oil Field ◽  
Fluid Composition ◽  
Oil Reservoir ◽  
Pressure Transient ◽  
Fluid Analysis ◽  
Reservoir Fluid ◽  
Fluid Properties ◽  
Pressure Transient Test

Abstract Acquisition of reservoir information from exploration campaigns in offshore oil reservoirs is a continuous challenge in today's operations. Reservoir fluid properties and reservoir parameters characterization are fundamental for the accurate reservoir description for field planning and facilities design. With the aid of new technology, data of the highest quality can be obtained while the well is being drilled. This data is a key input to the development plans for the area. For an exploration well in an offshore Trinidad and Tobago oil field, in a reservoir of mainly unconsolidated sandstones with medium oil, the main objective was to acquire early and quick identification of the oil prospect for planning appraisal wells. A wireline formation tester (WFT) dual-packer module was deployed to perform an interval pressure transient test (IPTT), also known as a mini-drillstem test (mini-DST), at the interval of interest for assessing key reservoir parameters such as vertical and horizontal permeability, damage skin, and reservoir pressure, among others, in the near-wellbore domain, in addition to fluid sampling. Downhole fluid analysis (DFA) was performed to identify the reservoir fluid properties including oil and water fraction, fluid composition, gas/oil ratio, density, viscosity, fluorescence, reflectance, and resistivity at multiple depths in real time. Also, the real-time insitu fluid characterization allowed making decisions about where and when to take the samples in an optimal amount of time. Additionally, a single-probe wireline formation tester was used to take fluid samples and to obtain a single-point formation pressure, used for determining pressure gradient. DFA was combined with pressure profiles to improve the determination of zonal connectivity across the reservoir. The combination of IPTT and real time DFA characterization was applied at multiple depths and resulted in an improved understanding of oil reservoir, as well as lessons learned about methodology and applications and recommendations for future operations.

REAL-TIME AND ON-SITE RESERVOIR FLUID CHARACTERISATION USING SPECTRAL ANALYSIS AND PVT EXPRESS

2004 ◽  
Vol 44 (1) ◽  
pp. 605
Author(s):  
A.K.M. Jamaluddin ◽  
C. Dong ◽  
P. Hermans ◽  
I.A. Khan ◽  
A. Carnegie ◽  
...  
Keyword(s):  
Real Time ◽  
Carbon Number ◽  
Saturation Pressure ◽  
Fluid Composition ◽  
Reservoir Fluid ◽  
Basic Fluid ◽  
Development Cycle ◽  
Surface Analysis Techniques ◽  
Fluid Properties ◽  
Open Hole

Obtaining an adequate fluid characterisation early in the life of a reservoir is becoming a key requirement for successful hydrocarbon development. This work presents and discusses a number of new fluid sampling and fluid characterisation technologies that can be deployed either down hole or at surface in the early stages of the exploration and development cycle to achieve this objective. Techniques discussed include methods to monitor and quantify oil-based mud contamination, gas-liquid-ratio (GLR) and basic fluid composition in real time during open-hole formation testing operations. In addition, we demonstrate the applicability of new surface analysis techniques that allow for rapid, accurate, and reliable measurements of key fluid properties, such as saturation pressure, gas-oil ratio, extended carbon number composition, viscosity, and density, on-site within a few hours of retrieving reservoir fluid samples at surface. Finally, prediction tools used to extend these limited measurements to a traditional PVT fluid characterisation are presented along with example measurements from all the techniques described. In conclusion, it is shown that the implementation of these techniques in a complementary program can reduce the risk associated with making key development decisions that are based on an understanding of reservoir fluid properties.

scholarly journals Effect of Compositional Grading On reservoir Performance

1996 ◽  
Vol 1 (1) ◽  
pp. 37
Author(s):  
M. Al-Rumhy ◽  
A. Al-Bemani ◽  
F. Boukadi
Keyword(s):  
Oil Recovery ◽  
Simulation Analysis ◽  
Fluid Composition ◽  
Fluid Viscosity ◽  
Reservoir Performance ◽  
Reservoir Fluid ◽  
Stock Tank ◽  
Fluid Properties ◽  
Secondary Oil Recovery ◽  
Compositional Grading

In reservoirs with thickness exceeding fifty meters, compositional guiding has been found to cause significant variation in performance. Main fluid properties, governing the magnitude of reservoir performance, such as density; formation volume factor and fluid viscosity experience variation due to varying fluid composition along the hydrocarbon column. These variations cause erroneous estimation of stock-tank oil in place and may infer reservoir engineers to consider inappropriate secondary oil recovery methods, for example. In the presence of gravity segregation within the oil column, heavy ends will form a heavy oil blanket in the lower part of the reservoir. Such a scenario may result in poor displacement and an earlier breakthrough when water drive is the dominant fluid flow mechanism. In this paper reservoir performance due to varying reservoir fluid composition has been examined using  reservoir simulation analysis and recommendations for better characterization of reservoir fluid sampling are outlined.

Towards a Continuous Near-Real Time Reservoir Fluid Characterization by the Implementation of Advanced Mud Logging Technology

2019 ◽  
Author(s):  
V. Franzi ◽  
C. Robert ◽  
A. Shoeibi ◽  
R. Galimberti ◽  
E. Ndonwie Mahbou ◽  
...  
Keyword(s):  
Real Time ◽  
Reservoir Fluid ◽  
Fluid Characterization ◽  
Mud Logging

A Sensitivity Study of Reservoir Performance Using a Compositional Reservoir Simulator

1972 ◽  
Vol 12 (01) ◽  
pp. 3-12
Author(s):  
Edward T.S. Huang
Keyword(s):  
Limited Range ◽  
Measured Data ◽  
Compositional Variation ◽  
Fluid Sample ◽  
Laboratory Measurements ◽  
Reservoir Performance ◽  
Reservoir Fluid ◽  
Liquid Phases ◽  
Fluid Properties ◽  
Compositional Simulator

Abstract Simulation of isothermal fluid flow in a reservoir using a compositional simulator requires fluid properties that are functions of pressure and properties that are functions of pressure and composition. These properties, i.e., K-values, densities and viscosities of both vapor and liquid phases, are usually obtained from general correlations phases, are usually obtained from general correlations or laboratory measurements of a reservoir fluid sample during a differential-depletion experiment in a PVT cell. prediction of fluid properties of complex mixtures using existing correlations is generally subject to great uncertainties. The laboratory measured data that are generally correlated as functions of pressure have validity only over a limited range of compositional variation. The purposes of this paper were (1) to assess, using a linear compositional simulator, the error introduced into calculated reservoir performance by employing fluids with a given range of uncertainties in their physical properties; and (2) to examine the validity of using the physical data correlated in the compositional simulator as functions of pressure rather than functions of both pressure and composition. The gas cycling process was chosen for illustration because composition changes during this process are large and results are affected more than in a depletion-type process. The hypothetical reservoir fluid system considered in this study was a methane-n-butane-n-decane mixture chosen to simulate a volatile oil system. The results of this investigation show for the particular system studied that:(1)the K-values for particular system studied that:(1)the K-values for the lighter components have the most significant effect on the calculated reservoir performance; and(2)simulations using fluid properties that are equivalent to the data measured during a differential depletion experiment reliably predict reservoir performance even under conditions where significant performance even under conditions where significant variations in reservoir fluid composition occur. Introduction A number of papers have recently been published concerning the development of compositional reservoir simulators-the mathematical models that simulate isothermal flow of multiphase, multicomponent fluids in porous media considering mass transfer effects. These models, which properly describe the distribution of each individual component in both vapor and liquid phases and account for pressure and compositional dependence of K-values, phase densities and viscosities, are more rigorous than the conventional simulators. The latter assumes that the heavy component does not exist in the vapor phase. To use the compositional simulator, it is highly desirable that fluid properties, i.e., K-values, densities and viscosities, as functions of pressure and composition, be available. However, for complex reservoir fluid mixtures, this information is rarely available. These fluid properties are usually calculated from published generalized correlations or obtained from laboratory measurements of a reservoir fluid sample by performing differential depletion experiments in a PVT cell. Prediction of fluid properties of complex mixtures using existing correlations is generally subject to great uncertainty. These errors will certainly have effects on the predicted reservoir performance. These effects may predicted reservoir performance. These effects may even be amplified if all the fluid properties are calculated from correlations. Improvement of the correlation predicted data by adjusting these data to match the limited available experimental values for the system of interest can be make. Yet there is no guarantee that the adjusted data will describe reliable fluid behavior in the region away from the matched points. On the other hand, the laboratory measured data, which are expressed as functions of pressure only, have validity over a limited range of pressure only, have validity over a limited range of compositional variation. When compositions of reservoir fluids vary significantly, the reliability of applying the laboratory measured data in the numerical simulation becomes questionable. SPEJ p. 3

Numerical Investigation of Gravitational Compositional Grading in Hydrocarbon Reservoirs Using Centrifuge Data

2009 ◽  
Vol 12 (05) ◽  
pp. 793-802 ◽  
Author(s):  
P. David Ting ◽  
Birol Dindoruk ◽  
John Ratulowski
Keyword(s):  
Experimental Data ◽  
Phase Behavior ◽  
Rock Properties ◽  
Model Parameters ◽  
Fluid Composition ◽  
Bulk Fluid ◽  
Reservoir Fluid ◽  
Fluid Systems ◽  
Fluid Properties ◽  
The Impact

Summary Fluid properties descriptions are required for the design and implementation of petroleum production processes. Increasing numbers of deep water and subsea production systems and high-temperature/high-pressure (HTHP) reservoir fluids have elevated the importance of fluid properties in which well-count and initial rate estimates are quite crucial for development decisions. Similar to rock properties, fluid properties can vary significantly both aerially and vertically even within well-connected reservoirs. In this paper, we have studied the effects of gravitational fluid segregation using experimental data available for five live-oil and condensate systems (at pressures between 6,000 and 9,000 psi and temperatures from 68 to 200°F) considering the impact of fluid composition and phase behavior. Under isothermal conditions and in the absence of recharge, gravitational segregation will dominate. However, gravitational effects are not always significant for practical purposes. Since the predictive modeling of gravitational grading is sensitive to characterization methodology (i.e., how component properties are assigned and adjusted to match the available data and component grouping) for some reservoir-fluid systems, experimental data from a specially designed centrifuge system and analysis of such data are essential for calibration and quantification of these forces. Generally, we expect a higher degree of gravitational grading for volatile and/or near-saturated reservoir-fluid systems. Numerical studies were performed using a calibrated equation-of-state (EOS) description on the basis of fluid samples taken at selected points from each reservoir. Comparisons of measured data and calibrated model show that the EOS model qualitatively and, in many cases, quantitatively described the observed equilibrium fluid grading behavior of the fluids tested. First, equipment was calibrated using synthetic fluid systems as shown in Ratulowski et al. (2003). Then real reservoir fluids were used ranging from black oils to condensates [properties ranging from 27°API and 1,000 scf/stb gas/oil ratio (GOR) to 57°API and 27,000 scf/stb GOR]. Diagnostic plots on the basis of bulk fluid properties for reservoir fluid equilibrium grading tendencies have been constructed on the basis of interpreted results, and sensitivities to model parameters estimated. The use of centrifuge data was investigated as an additional fluid characterization tool (in addition to composition and bulk phase behavior properties) to construct more realistic reservoir fluid models for graded reservoirs (or reservoirs with high grading potential) have also been investigated.

Wet Gas Compressor Testing – Performance Uncertainty

2020 ◽  
Author(s):  
Dagfinn Mæland ◽  
Lars E. Bakken
Keyword(s):  
Performance Test ◽  
Thermodynamic Simulation ◽  
Operating Conditions ◽  
Fluid Composition ◽  
Wet Gas ◽  
Thermodynamic Simulations ◽  
Fluid Properties ◽  
Compressor Performance ◽  
Fluid Characterization ◽  
Compressor Power

Abstract Based on experience from wet gas compressor testing at NTNU (low-pressure air-water fluid) and K-Lab full-scale testing (normal operating conditions, high pressure and hydrocarbon fluids), this paper documents important aspects relating to the uncertainty evaluation of wet gas compressor performance test results. The Monte Carlo method for evaluation of uncertainty on a wet gas compressor system is outlined, and the resulting uncertainties of key compressor performance parameters are presented. Furthermore, a sensitivity analysis has been performed to evaluate how uncertainties in the output of the model can be appointed to different sources of uncertainty in the inputs, thus identifying main contributors to the uncertainties. The importance of accurately determining the fluid composition, the properties of the fluid components and how these affect the fluid characterization are discussed. Together with the choice of equation of state, the characterization directly affects the simulated fluid properties, and great care is required to obtain reliable compressor performance results. Uncertainties of physical properties originating from the thermodynamic simulation show that compressor power and gas density ideally should be determined from direct measurements and not from thermodynamic simulations.

Gas Deviation Factor Calculation Made Easy and Accurate Using an IR 4.0 Tool

2021 ◽  
Author(s):  
Nasser M. Al-Hajri ◽  
Akram R. Barghouti ◽  
Sulaiman T. Ureiga
Keyword(s):  
Molecular Weight ◽  
Apparent Molecular Weight ◽  
Numerical Approach ◽  
Temperature Data ◽  
Reservoir Fluid ◽  
Fluid Properties ◽  
Deviation Factor ◽  
Alternative Methodology ◽  
Fluid Characterization ◽  
Gas Properties

Abstract Gas deviation factor (z-factor) and other gas reservoir fluid properties, such as formation volume factor, density, and viscosity, are normally obtained from Pressure-Volume-Temperature (PVT) experimental analysis. This process of reservoir fluid characterization usually requires collecting pressurized fluid samples from the wellbore to conduct the experimental work. The scope of this paper will provide an alternative methodology for obtaining the z-factor. An IR 4.0 tool that heavily utilizes software coding was developed. The advanced tool uses the novel apparent molecular weight profiling concept to achieve the paper objective timely and accurately. The developed tool calculates gas properties based on downhole gradient pressure and temperature data as inputs. The methodology is applicable to dry, wet or condensate gas wells. The gas equation of state is modified to solve numerically for the z-factor using the gradient survey pressure and temperature data. The numerical solution is obtained by applying an iterative computation scheme as described below:A gas apparent molecular weight value is initialized and then gas mixture specific gravity and pseudo-critical properties are calculated.Gas mixture pseudo-reduced properties are calculated from the measured pressure and temperature values at the reservoir depth.A first z-factor value is determined as a function of the pseudo-reduced gas properties.Gas pressure gradient is obtained at the reservoir depth from the survey and used to back-calculate a second z-factor value by applying the modified gas equation of state.Relative error between the two z factor values is then calculated and compared against a low predefined tolerance.The above steps are reiterated at different assumed gas apparent molecular weight values until the predefined tolerance is achieved. This numerical approach is computerized to perform the highest possible number of iterations and then select the z-factor value corresponding to the minimum error among all iterations. The proposed workflow has been applied on literature data with known reservoir gas properties, from PVT analysis, and showed an excellent prediction performance compared to laboratory analysis with less than 5% error.

DEEP TRANSIENT TESTING DIGITAL PRODUCTS CREATE NOVEL REAL-TIME RESERVOIR INSIGHTS

2021 ◽  
Author(s):  
Jansen Oliveira ◽  
◽  
Karl Perez H. ◽  
Alejandro Martin V. ◽  
Ricard Fernandez T. ◽  
...  
Keyword(s):  
Numerical Analysis ◽  
Real Time ◽  
History Matching ◽  
Fluid Model ◽  
Saturation Pressure ◽  
Fluid Composition ◽  
Dynamic Data ◽  
Pressure Transient ◽  
Reservoir Fluid ◽  
Geologic Model

Offshore exploration requires the evaluation of hydrocarbon presence, estimation of volumes in place, and flow potential. To this capacity, formation testers are widely used to determine static data such as reservoir fluid gradients and reservoir pressure, obtain fluid samples, and to assess reservoir connectivity. Dynamic data, acquired with interval pressure transient testing and well testing techniques, are used to assess reserves and productivity. However, these evaluation techniques provide dynamic data at different resolution and length scales, and with different environmental footprint, cost, and operational constraints. A new wireline formation testing technique known as deep transient testing (DTT) has been introduced, which combines high-resolution measurements, higher flow rates, and longer test durations to perform transient tests in higher permeability, thicker formation, and at greater depth of investigation than with previous formation testers—without flaring and at a low carbon footprint. The platform combines advanced metrology with extensive automation to generate unique, real-time reservoir insights. Traditionally, pressure transient analysis and well deliverability predictions were produced through an analytical framework. Today, deep transient testing measurements are interpreted, and placed in reservoir context, in real-time by integration with geological and reservoir models. These steps can be performed from any wellsite utilizing cloud-based resources. Products such as reservoir fluid compressibility, saturation pressure, equation of state (EOS) models, well productivity, or minimum connected volumes are integrated in real-time interpretation utilizing numerical analysis. The digital infrastructure enables key reservoir insights to be shared between all stakeholders in a transparent and collaborative environment for both operational control and rapid decision making. This paper presents a case study where the new DTT technique was combined with numerical analysis and real-time integrated workflows to characterize a multilayer reservoir in a recent discovery in deepwater Mexico. During the drawdown phase of the DTT operation, real-time downhole fluid analysis was used to determine the fluid composition, density, viscosity, compressibility, and saturation pressure. These fluid properties were then used to generate and tune an EOS model. Accurate drawdown flow rate measurements and the subsequent pressure transients were combined with the fluid model and geologic model to enable integrated pressure transient history matching. The resulting calibrated numerical model honors the fluid measurements and geologic model and was used to predict the permeability profile, zonal producibility, and the volume of influence of the test.

Sign in / Sign up

Export Citation Format

Share Document