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. ◽  
...  

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.

2004 ◽  
Vol 44 (1) ◽  
pp. 605
Author(s):  
A.K.M. Jamaluddin ◽  
C. Dong ◽  
P. Hermans ◽  
I.A. Khan ◽  
A. Carnegie ◽  
...  

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.


2014 ◽  
Author(s):  
S.. Paul ◽  
R.. Tapia ◽  
J.A.. A. Arias-Correa

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.


2021 ◽  
Author(s):  
Mohammad J. Ahsan ◽  
Shaikha Al-Turkey ◽  
Nitin M. Rane ◽  
Fatemah A. Snasiri ◽  
Ahmed Moustafa ◽  
...  

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.


2008 ◽  
Vol 11 (06) ◽  
pp. 1107-1116 ◽  
Author(s):  
Chengli Dong ◽  
Michael D. O'Keefe ◽  
Hani Elshahawi ◽  
Mohamed Hashem ◽  
Stephen M. Williams ◽  
...  

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.


2003 ◽  
Author(s):  
Fujisawa Go ◽  
Oliver C. Mullins ◽  
Chengli Dong ◽  
Andrew Carnegie ◽  
Soraya S. Betancourt ◽  
...  

2021 ◽  
Author(s):  
Elizabeth Ruiz ◽  
Brandon Thibodeaux ◽  
Christopher Dorion ◽  
Herman Mukisa ◽  
Majid Faskhoodi ◽  
...  

Abstract Optimized geomodeling and history matching of production data is presented by utilizing an integrated rock and fluid workflow. Facies identification is performed by use of image logs and other geological information. In addition, image logs are used to help define structural geodynamic processes that occurred in the reservoir. Methods of reservoir fluid geodynamics are used to assess the extent of fluid compositional equilibrium, especially the asphaltenes, and thereby the extent of connectivity in these facies. Geochemical determinations are shown to be consistent with measurements of compositional thermodynamic equilibrium. The ability to develop the geo-scenario of the reservoir, the coherent evolution of rock and contained fluids in the reservoir over geologic time, improves the robustness of the geomodel. In particular, the sequence of oil charge, compositional equilibrium, fault block throw, and primary biogenic gas charge are established in this middle Pliocene reservoir with implications for production, field extension,and local basin exploration. History matching of production data prove the accuracy of the geomodel; nevertheless, refinements to the geomodel and improved history matching were obtained by expanded deterministic property estimation from wireline log and other data. Theearly connection of fluid data, both thermodynamic and geochemical, with relevant facies andtheir properties determination enables a more facile method to incorporate this data into the geomodel. Logging data from future wells in the field can be imported into the geomodel allowingdeterministic optimization of this model long after production has commenced. While each reservoir is unique with its own idiosyncrasies, the workflow presented here is generally applicable to all reservoirs and always improves reservoir understanding.


Geofluids ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-21 ◽  
Author(s):  
Sungil Kim ◽  
Baehyun Min ◽  
Kyungbook Lee ◽  
Hoonyoung Jeong

This study couples an iterative sparse coding in a transformed space with an ensemble smoother with multiple data assimilation (ES-MDA) for providing a set of geologically plausible models that preserve the non-Gaussian distribution of lithofacies in a channelized reservoir. Discrete cosine transform (DCT) of sand-shale facies is followed by the repetition of K-singular value decomposition (K-SVD) in order to construct sparse geologic dictionaries that archive geologic features of the channelized reservoir such as pattern and continuity. Integration of ES-MDA, DCT, and K-SVD is conducted in a complementary way as the initially static dictionaries are updated with dynamic data in each assimilation of ES-MDA. This update of dictionaries allows the coupled algorithm to yield an ensemble well conditioned to static and dynamic data at affordable computational costs. Applications of the proposed algorithm to history matching of two channelized gas reservoirs show that the hybridization of DCT and iterative K-SVD enhances the matching performance of gas rate, water rate, bottomhole pressure, and channel properties with geological plausibility.


2015 ◽  
Vol 18 (02) ◽  
pp. 187-204 ◽  
Author(s):  
Fikri Kuchuk ◽  
Denis Biryukov

Summary Fractures are common features in many well-known reservoirs. Naturally fractured reservoirs include fractured igneous, metamorphic, and sedimentary rocks (matrix). Faults in many naturally fractured carbonate reservoirs often have high-permeability zones, and are connected to numerous fractures that have varying conductivities. Furthermore, in many naturally fractured reservoirs, faults and fractures can be discrete (rather than connected-network dual-porosity systems). In this paper, we investigate the pressure-transient behavior of continuously and discretely naturally fractured reservoirs with semianalytical solutions. These fractured reservoirs can contain periodically or arbitrarily distributed finite- and/or infinite-conductivity fractures with different lengths and orientations. Unlike the single-derivative shape of the Warren and Root (1963) model, fractured reservoirs exhibit diverse pressure behaviors as well as more than 10 flow regimes. There are seven important factors that dominate the pressure-transient test as well as flow-regime behaviors of fractured reservoirs: (1) fractures intersect the wellbore parallel to its axis, with a dipping angle of 90° (vertical fractures), including hydraulic fractures; (2) fractures intersect the wellbore with dipping angles from 0° to less than 90°; (3) fractures are in the vicinity of the wellbore; (4) fractures have extremely high or low fracture and fault conductivities; (5) fractures have various sizes and distributions; (6) fractures have high and low matrix block permeabilities; and (7) fractures are damaged (skin zone) as a result of drilling and completion operations and fluids. All flow regimes associated with these factors are shown for a number of continuously and discretely fractured reservoirs with different well and fracture configurations. For a few cases, these flow regimes were compared with those from the field data. We performed history matching of the pressure-transient data generated from our discretely and continuously fractured reservoir models with the Warren and Root (1963) dual-porosity-type models, and it is shown that they yield incorrect reservoir parameters.


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