Analyzing Reservoir Fluid Composition In-Situ in Real Time: Case Study in a Carbonate Reservoir

2003 ◽  
Author(s):  
Fujisawa Go ◽  
Oliver C. Mullins ◽  
Chengli Dong ◽  
Andrew Carnegie ◽  
Soraya S. Betancourt ◽  
...  
Keyword(s):  
Real Time ◽  
Carbonate Reservoir ◽  
Fluid Composition ◽  
Reservoir Fluid

scholarly journals Challenges of Mechanochemistry: Is In Situ Real-Time Quantitative Phase Analysis Always Reliable? A Case Study of Organic Salt Formation

2017 ◽  
Vol 4 (9) ◽  
pp. 1700132 ◽  
Author(s):  
Adam A. L. Michalchuk ◽  
Ivan A. Tumanov ◽  
Sumit Konar ◽  
Simon A. J. Kimber ◽  
Colin R. Pulham ◽  
...  
Keyword(s):  
Real Time ◽  
Phase Analysis ◽  
Organic Salt ◽  
Quantitative Phase Analysis ◽  
Salt Formation ◽  
Quantitative Phase

Dynamic Formation Evaluation to Reduce Uncertainty and Confirm Completed Intervals in Brown Fields

2021 ◽  
Author(s):  
Muhamad Aizat Kamaruddin ◽  
Ayham Ashqar ◽  
Muhammad Haniff Suhaimi ◽  
Fairus Azwardy Salleh
Keyword(s):  
Real Time ◽  
Optical Sensors ◽  
Sensor Technology ◽  
Innovative Technology ◽  
Fluid Type ◽  
Formation Evaluation ◽  
Reservoir Fluid ◽  
Logging While Drilling ◽  
Dynamic Formation

Abstract Uncertainties in fluid typing and contacts within Sarawak Offshore brown field required a real time decision. To enhance reservoir fluid characterisation and confirm reservoir connectivity prior to well final total depth (TD). Fluid typing while drilling was selected to assure the completion strategy and ascertain the fluvial reservoir petrophysical interpretation. Benefiting from low invasion, Logging While Drilling (LWD) sampling fitted with state of ART advanced spectroscopy sensors were deployed. Pressures and samples were collected. The well was drilled using synthetic base mud. Conventional logging while drilling tool string in addition to sampling tool that is equipped with advanced sensor technology were deployed. While drilling real time formation evaluation allowed selecting the zones of interest, while fluid typing was confirmed using continually monitored fluids pump out via multiple advanced sensors, contamination, and reservoir fluid properties were assessed while pumping. Pressure and sampling were performed in drilling mode to minimise reservoir damage, and optimise rig time, additionally sampling while drilling was performed under circulation conditions. Pressures were collected first followed by sampling. High success in collecting pressure points with a reliable fluid gradient that indicated a virgin reservoir allowed the selection of best completion strategy without jeopardising reserves, and reduced rig time. Total of seven samples from 3 different reservoirs, four oil, and three formation water. High quality samples were collected. The dynamic formation evaluation supported by while drilling sampling confirmed the reservoir fluid type and successfully discovered 39ft of oil net pay. Reservoir was completed as an oil producer. The Optical spectroscopy measurements allowed in situ fluid typing for the quick decision making. The use of advanced optical sensors allowed the sample collection and gave initial assessment on reservoir fluids properties, as a result cost saving due to eliminating the need for additional Drill Stem Test (DST) run to confirm the fluid type. Sample and formation pressures has confirmed reservoir lateral continuity in the vicinity of the field. The reservoir developed as thick and blocky sandstone. Collected sample confirmed the low contamination levels. Continuous circulation mitigated sticking and potential well-control risks. This is the first time in surrounding area, advanced optical sensors are used to aid LWD sampling and to finalize the fluid identification. The innovative technology allowed the collection of low contamination. The real-time in-situ fluid analysis measurement allowed critical decisions to be made real time, consequently reducing rig downtime. Reliable analysis of fluid type identification removed the need for additional run/service like DST etc.

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.

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.

Advanced Gas While Drilling GWD Comparison with Pressure Volume Temperature PVT Analysis to Obtain Information About the Reservoir Fluid Composition, a Case Study from East Kuwait Jurassic Reservoir

2021 ◽  
Author(s):  
Mohammad J. Ahsan ◽  
Shaikha Al-Turkey ◽  
Nitin M. Rane ◽  
Fatemah A. Snasiri ◽  
Ahmed Moustafa ◽  
...  
Keyword(s):  
Real Time ◽  
Oil And Gas ◽  
Compositional Analysis ◽  
Fluid Composition ◽  
Well Test ◽  
Drilling Mud ◽  
Strong Base ◽  
Field Development ◽  
Gas Drilling ◽  
Reservoir Fluid

Abstract Objectives/Scope The acquisition of mud gas data for well control and gathering of geological information is a common practice in oil and gas drilling. However, these data are scarcely used for reservoir evaluation as they are presumably considered as unreliable and non-representative of the formation content. Recent development in gas extraction from drilling mud and analyzing equipment has greatly improved the data quality. Combined with proper analysis and interpretation, these new datasets give valuable information in real-time lithological changes, hydrocarbons content, water contacts and vertical changes in fluid over a pay interval. Methods, Procedures, Process Post completion, Mud logging data have been compared with PVT results and they have shown excellent correlation on the C1-C5 composition, confirming the consistency between gas readings and reservoir fluid composition. Having such information in real time has given the oil company the opportunity to optimize its operations regarding formation evaluation, e.g downhole sampling, wireline logging or testing programs. Formation fluid is usually obtained during well tests, either by running downhole tools into the well or by collecting the fluid at surface. Therefore, its composition remains unknown until the arrival of the PVT well test results. This case intends to use mud gas information collected while drilling to predict information about the reservoir fluid composition in near real time. To achieve this goal we compared mud gas data collected while drilling with reservoir fluid compositional results. Pressure volume temperature (PVT) analysis is the process of determining the fluid behaviors and properties of oil and gas samples from existing wells. Results, Observations, Conclusions The reason any oil and gas company decides to drill a well is to turn the project into an oil-producing asset. But the value of the oil extracted from a single well is not the same as the value of the oil produced from another. The makeup of the oil, which can be determined from the compositional analysis, is an important piece of the equation that determines how profitable the play will be. The compositional analysis will determine just how much of each type of petroleum product can be produced from a single barrel of oil from that wells. Novel/Additive information Formation samples were obtained from offset wells in the Marrat Formation. These datasets gave valuable indications on fluid properties and phase behavior in the reservoir and provided strong base for reservoir engineering analysis, simulation and surface facilities design. The comparison of the gas data to PVT results gives a good match for reservoir fluid finger print, early acquisition of this data will help for decision enhancement for field development.

In-Situ Tectonic Stress Measurement from Wireline Straddle Packer MicroFrac Testing: A Case Study in a Carbonate Reservoir (U.A.E.)

2015 ◽  
Author(s):  
Noora Saeed Al Shehhi ◽  
Mohamed El-Hamawi ◽  
Dee Moronkeji ◽  
Javier Franquet ◽  
Steve Smith
Keyword(s):  
Stress Measurement ◽  
Tectonic Stress ◽  
Carbonate Reservoir

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.

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