Dasgupta, Suvodip (Schlumberger) | Raina, Ishan (Schlumberger) | Povstyanova, Magdalena (ADNOC E&P) | Laer, Pierre Van (ADNOC E&P) | Baig, Muhammad Zeeshan (ADNOC E&P) | Casson, Neil (ADNOC E&P) | Marzooqi, Hassan Al (ADNOC E&P) | Suwaidi, Salama Jumaa Al (ADNOC E&P) | Ali, Humair (Schlumberger) | Subbiah, Surej Kumar (Schlumberger) | Mello, Ashish D' (Schlumberger)
Al-Shamali, Adnan (Kuwait Oil Company) | Mishra, P. K. (Kuwait Oil Company) | Verma, Naveen K. (Kuwait Oil Company) | Quttainah, Riyad (Kuwait Oil Company) | Al Jallad, Osama (Ingrain Inc.) | Grader, Avrami (Ingrain Inc.) | Walls, Joel (Ingrain Inc.) | Koronfol, Safouh (Ingrain Inc.) | Morcote, Anyela (Halliburton)
In Kuwait, the Najmah source rock is characterized by a complex diagenetic history and depositional variability. Accurate determination of the porosity and permeability logs is essential for improved petrophysical evaluation, which may not be properly performed using conventional methods. This complexity makes the conventional evaluation methods alone insufficient to determine porosity and permeability logs accurately. A major goal of this study was to produce high-resolution porosity-permeability logs for Najmah Formation using advanced digital analysis and geochemistry measurements.
Sixty (60) feet of continuous core were analyzed from an oil field in southwest Kuwait. The analysis started with dual-energy x-ray CT scanning of full-diameter whole core and core gamma logging. Plug-size samples were selected to represent the varying porosity and organic matter content along the entire core length. Two-dimensional Scanning Electron Microscopy (2D SEM) and three-dimensional Focused Ion Beam (3D FIB-SEM) images were acquired and analyzed to accurately determine the organic matter content and porosity. Matrix permeability was directly computed from the 3D FIB-SEM images using the Lattice Boltzmann method. The SEM porosity was calibrated by determining the amount of movable hydrocarbons at in-situ reservoir conditions based on geochemical analyses (XRF, XRD and LECO), pyrolysis indices, PVT data and adsorption isotherm experiments.
The digitally obtained porosity and permeability data showed a unique trend that was used to produce permeability at the core level. The integration between digital analysis and geochemistry data increased the estimated porosity and confirmed higher mobile hydrocarbon in the reservoir in comparison with the measured data at the surface. This produced a new porosity-permeability trend that was more representative of the reservoir conditions and caused a significant increase in the rock permeability.
The integration between the digital SEM analysis and the geochemical measurements was critical to estimate in-situ porosity and permeability characteristics of the tight formation under study. Moreover, this analysis provided an important tool for obtaining different high-resolution porosity and permeability logs based on various porosity considerations (effective, organic, inorganic, clay). This would lead to higher accuracy in determining reservoir properties for improved quantification of reserves and productivity.
Dekker, R. (Shell Global Solutions International BV) | Tegelaar, E. (Shell Global Solutions International BV) | Perrotta, S. (Shell Global Solutions International BV) | Miller, S. D. (Shell Kuwait Exploration & Production) | Le Varlet, X. (Shell Kuwait Exploration & Production) | Hasler, C-A. (Shell Kuwait Exploration & Production) | Narhari, S. R. (Kuwait Oil Company) | Rao, J. D. (Kuwait Oil Company) | Neog, N. (Kuwait Oil Company) | Dwindt, A. A. (Kuwait Oil Company) | Al-Haidar, S. (Kuwait Oil Company) | Dashti, Qusem (Kuwait Oil Company)
The primary objective of the present study is to determine the fluid connectivity in the Middle Marrat of the major Jurassic fields in North Kuwait. Understanding fluid connectivity on both geological and production time scales has a direct impact on static and dynamic reservoir modeling, history matching, fluid property variations during production and zonal allocation of comingled production.
123 light oils and condensates were analysed using multi-dimensional gas chromatography (MDGC). The resulting so-called fluid fingerprints were interpreted in the context of a complex geological framework resulting from extensive sedimentological, petrographic, and structural geology studies. A detailed description of different fluid families allowed reconstruction of reservoir connectivity on a geological time scale. Fault transmissibility was reconstructed from the distribution of fluid fingerprints of samples taken during well tests or/and early production representing the fingerprint of the initial fluids in place. Also, the significance and extent of baffles to vertical fluid flow like anhydrites or low permeability streaks could be evaluated.
In time-lapse-geochemistry, fluid fingerprints are monitored during production. Changes in fluid fingerprints were interpreted in terms of fluid movement from other reservoirs along fault systems. These changes in fluid fingerprints matched the changes in fluid properties observed during the well testing. In other examples, changing relative contribution of different separate flow zones that are commingled in the subsurface were recognized.
The results are used to update/constrain the 3D static & dynamic models. Results help to understand connectivity, fluid flow and Pore Pressure Prediction (PPP) for new wells to be drilled.
Oil fingerprinting is a common name for techniques based on geochemical analysis of hydrocarbon fluids composition which could provide valuable and unique information for well and reservoir management. Hydrocarbons in oil and gas deposits are affected by different processes, such as: biodegradation, gas flushing, water washing and evaporation. The degree of change depends on many factors: temperature, reservoir compartmentalization, tectonics, aquifer activity etc. Consequently, hydrocarbons initially migrated from one source rock become different in different reservoirs and compartments. Evaluation of changes in composition allows identification of hydrocarbons from different reservoirs, in other words to identify unique "fingerprints" of hydrocarbons. This information can be very valuable for production allocation between reservoirs and for needs of well and reservoir management. This article summarizes the results of a pilot oil fingerprinting project on Astokh oil field based on High Resolution Gas Chromatography (HRGC). The primary objective of this work was to develop a methodology for production allocation in comingled oil producers based on HRGC as applied for the Astokh area. In the course of work some more opportunities were identified, for instance monitoring of reservoir dynamics which could turn out to be more powerful than the primary objective.
Dernaika, Moustafa R (Ingrain Inc) | Sahib, Mohammad Raffi (Kuwait Oil Company) | Gonzalez, David (Ingrain Inc) | Mansour, Bashar (Ingrain Inc) | Al Jallad, Osama (Ingrain Inc) | Koronfol, Safouh (Ingrain Inc) | Sinclair, Gary (Ingrain Inc) | Kayali, Anas (Ingrain Inc)
Detailed core characterization is often overlooked in the sampling process for core analysis measurements. Random core sampling is usually performed and the selected plugs are not associated with rock types or the reservoir heterogeneity. The objective of this study is to obtain representative samples for direct simulation of petrophysical and fluid flow properties in complex rock types.
A robust sampling strategy was followed in reservoir cores from two successive heterogeneous carbonate and siliciclastic formations in the Raudhatain field in Kuwait. The sample selection criteria were based on statistical distribution of litho-types in the cores to ensure optimum characterization of the main reservoir units. The litho-types were identified based on porosity and mineralogy variations along the core lengths utilizing advanced dual-energy X-ray CT scanning. High resolution micro-CT imaging and subsequent segmentation provided 3D representation of the pore space and geometric fabric of the core samples. Primary drainage and imbibition processes were simulated in numerical experiments using a pore-scale simulator by the Lattice Boltzmann Method. Capillary pressure (Pc) and relative permeability (Kr) curves together with water and oil distributions were investigated for complex geometries by the different rock types.
The dual energy CT density was compared with wireline log and provided accurate calibrations to the downhole logs. The different rock types gave distinct capillary and flow properties that can be linked to the rock structure and pore type of the samples. The Lattice Boltzmann based pore-level fluid calculations provided realistic fluid distributions in the 3D rock volume, which are consistent with pore-scale physical phenomena.
This characterization method by the dual energy CT eliminates sampling bias and allows for each cored litho-type to be equally represented in the plugs acquired for subsequent petrophysical and fluid flow analyses. It also provides accurate calibration tool for downhole logs. The digital analysis gave reliable SCAL data with improved understanding of the pore-level events and proved its effectiveness in providing advanced interpretations at multiple scales in relatively short timeframes.
Siddiqui, M. A. (KOC) | Al-Mutairi, Moute'a (KOC) | Mankala, R. (KOC) | Qayyum, S. (Resman) | Prusakov, A. (Resman) | Leung, E. (Resman) | Alabdulwahab, M. (KOC) | Al-Rashidi, M. M (KOC) | Al-Ali, A. (MEOFS)
Kuwait Oil Company is pursuing fast track technology deployment in its fields to meet the strategic target of production. The horizontal wells provide good mean to exploit the reservoir through increased reservoir contact but it brings some inherent problems in optimizing production and low cost well intervention. To address these inherent challenges, the deployment of inflow control device (ICD) has become a normal trend of completion in horizontal wells.
The completion of horizontal wells with ICDs helps in optimizing production but information of inflow contribution from each section qualitatively and quantitatively is still a challenge. In this perspective, KOC has deployed intelligent chemical inflow tracer technology combined with On/Off ICDs below an ESP in a horizontal well located in its northern field to assess the inflow performance of the production. The horizontal well was drilled through a heterogeneous reservoir, which was compartmentalized with swell packers and completed with On/Off ICDs. In these types of wells, traditional production logs are considered risky and expensive due to the limitations of using a small-diameter coil tubing, which must fit through the Y-tool on the ESP. This small diameter coil tubing will go into helical buckling before reaching the toe of the well resulting in an incomplete log for the well. In some cases, the wells are lacking Y-Tool facility, which practically does not allow production logging in the well.
In such cases, the intelligent chemical inflow tracers are used to provide a qualitative assessment of the clean-up phase of production, quantitative inflow information from each zone, and to identify the section producing water along the horizontal well. The use of intelligent tracers overcame the intervention challenges by installing intelligent downhole chemical sensors in pup-joint carriers next to the ICD joints in each compartment from heel to toe to meet monitoring objectives of Kuwait Oil Company. Fluid samples collected from the surface flow lines were analyzed for unique chemical tracer signatures and interpreted the corresponding tracer signals. This has resulted into identification of quality of fluid flowing from each section concomitant with its quantification. In addition, the pilot results have increased the reservoir understanding that leads to optimum ICD designs for future wells in the same reservoir.
This paper discusses the first well installation of its kind in Kuwait, the methodology for selecting the technology, the deployment in the well, and the interpretation of results of water and oil tracers obtained during different monitoring campaigns through fluid sampling.
For formation tester sampling, it is crucial to obtain clean representative samples of low drilling fluid filtrate contamination. The accurate, real-time prediction of the level of oil-based mud (OBM) filtrate contamination during sampling is essential to ensure that a low contamination fluid sample is obtained. Existing methods rely on the curve fitting technique of single channel/sensor measurements, such as optical, composition, density, and compressibility. These curve fitting methods necessitate a significant signal contrast between the pure OBM filtrate and the formation fluid. Curve fitting uses two assumptions that are often proven untrue: 1) the fluid asymptotically approaches a clean fluid value and 2) the curve fit equation is simple and unchanging throughout the pumpout and can therefore be extrapolated to long times. Accurate knowledge of pure component properties for both fluids is also necessary for curve fitting methods. Unfortunately, the properties of the two endmembers cannot be measured directly, either in the downhole environment or the laboratory. Therefore, existing methods can be highly sensitive to sensor data selection, the estimates of the endmember properties, and the method of curve fitting.
A new reliable multivariate method was developed to accurately determine the downhole sample contamination level using the data stream from multiple sensors. The new multivariable method overcomes all limitations of curve fitting methods. This method treats the downhole sample cleanup process as a mixing problem of the two endmembers and solves the problem by applying reasonable and ubiquitous constraints to the multivariate sensor signals of the mixtures. This method enables data from multiple optical channels or multiple sensors to be fused and then used in a process to accurately and reliably predict contamination. Using this method, accurate knowledge of the endmember properties is no longer necessary to estimate the contamination level. The algorithm automatically weights the contributions of signals based on the contrast of each signal and optimally processes data to generate the properties and concentration profiles of the endmembers, which provides the OBM contamination measurement in real time. This study shows that sample contamination can be measured even when a pumpout has asymptotically reached a higher level of steady-state contamination. The effectiveness and reliability of this method are demonstrated through three field cases in which the predicted contaminations levels closely matched laboratory results.
McCaffrey, Mark A. (Weatherford Laboratories) | Al-Khamiss, Awatif (Kuwait Oil Company) | Jensen, Marc D. (ConocoPhillips Alaska) | Baskin, David K. (Weatherford Laboratories) | Laughrey, Christopher D. (Weatherford Laboratories) | Rodgers, Wade M. (Occidental Petroleum)
AbstractUsing examples from the Permian Basin of Texas, the North Slope of Alaska, and the Bergan Field of Kuwait, this paper describes how oil geochemical fingerprinting can be applied to diagnose quickly and easily three production problems that may affect highly deviated wells.High-Resolution Gas Chromatography can be used to quantify ~1,000 different compounds in an oil, and the relative abundances of those compounds form a geochemical fingerprint. Geochemical differences between fluids in adjacent reservoirs can serve as natural tracers for fluid origin, allowing changes in production in highly deviated wells to be understood.Application 1: In wells that are fracture stimulated, oil fingerprinting can be used to assess whether induced fractures have propagated out of the target interval and into overlying or underlying formations. Oil fingerprinting can be used to quantify what percentage of the produced oil and gas is coming from each interval and how the effective stimulated rock volume changes through time. This concept is illustrated here with a Permian Basin example.Application 2: In wells with multiple laterals in the same well (such as those in certain North Slope, Alaska fields), sand can settle out of the production stream and form sand bridges that obstruct production from one or more of the laterals. In addition, sand co-produced with oil from shallower laterals can settle at the bottom of the vertical section during regular production and obstruct the entry to a deeper lateral. Geochemical fingerprinting can be used to determine quantitatively the contribution of each of several zones to a commingled oil stream. This technique allows the operator to identify sanded-out intervals for fill cleanout (FCO).Application 3: If two reservoirs are both oil bearing, but are of very different permeability, horizontal wells with an intended landing target in the tighter reservoir may be adversely affected if the well path contacts the more permeable reservoir. The Mauddud reservoir in Kuwait provides examples of this phenomenon. The Mauddud carbonate occurs between two massive clastic reservoirs, the Wara and the Burgan. Average Mauddud porosity is 18% with low permeability (1-10 mD), characteristics which make this reservoir a candidate for horizontal drilling. However, some lateral wells in this carbonate may encounter the adjacent, more permeable reservoirs over a short portion of the well path. In such cases, production from the adjacent reservoir may account for virtually all of the well's production, even though the well was intended to be completed solely in the tighter reservoir. Oil fingerprinting can be used to identify wells affected by this problem.A common theme unifies these three applications: Geochemical differences between in-situ fluids in adjacent reservoirs can serve as natural tracers for fluid movement. However, these techniques have been under-applied as tools for optimization of production from highly deviated wells. This paper illustrates the application of this technology to that well type in a variety of play types.
Veedu, F. Koyassan (DeGolyer and MacNaughton) | Dharanidharan, B. (DeGolyer and MacNaughton) | Tye, R. (DeGolyer and MacNaughton) | Prasse, E. (DeGolyer and MacNaughton) | Flagg, S. (DeGolyer and MacNaughton) | Hornbrook, J. (DeGolyer and MacNaughton) | Ahmad, F. (Kuwait Oil Company) | Al-Dohaiem, K. (Kuwait Oil Company) | Jha, M. (Kuwait Oil Company) | Bagheri, M. (Kuwait Oil Company) | Sanyal, T. (Kuwait Oil Company)
This paper summarizes a reservoir modeling study involving the evaluation of development strategies relevant to a newly discovered, unconsolidated sandstone heavy oil field in Kuwait. The methodologies used provided essential information to define and evaluate feasible options to develop the reservoir.
A reservoir model was developed utilizing seismic, well-log, and core data. Petrophysical estimates of mineralogy, porosity, water saturation (Sw), and permeability were made and calibrated to core data. The field geology and the depositional analog guided the interpretations of the reservoir geomorphology and sediment-distribution patterns. Facies modeling was achieved through multiple-point statistics methodology. Porosity, permeability, and Sw were distributed using Sequential Gaussian Simulation. Various sensitivity runs were made for key parameters to understand the uncertainty of the model forecast. A full-field reservoir model (FFRM) was developed by incorporating available engineering analysis data. Development potential of the field through pressure depletion was studied through full-field reservoir simulations. Considering the high level of uncertainty of a new field, Low, Mid and High forecast cases were established for development through pressure depletion. Simulations of secondary and tertiary recovery techniques were then evaluated through sector model simulations and upscaled to field level. Finally, roadmaps were laid out for several development scenarios considered for the field.
This paper demonstrates how various geological, petrophysical, and engineering data were used to build a representative full-field geocellular model (FFGM) and make field-performance forecasts under uncertainties pertaining to a green, heavy-oil field. During the model development stage, dielectric and elemental spectroscopy log data were utilized to enhance the petrophysical analyses. The distribution of Sw followed a distinct workflow where the distribution within each reservoir zone was based on several oil/water contacts (OWC). Available pressure-volume-temperature (PVT) analysis data were used to estimate and confirm the presence of water zones within the reservoir intervals.
Ahmed, Khalid (Kuwait Oil Company) | Hassan, Faisal (Kuwait Oil Company) | Taqi, Fatma (Kuwait Oil Company) | Ahmad, Fatma (Kuwait Oil Company) | Pearl, Megan (Halliburton) | Jones, Christopher (Halliburton) | Vasquez, Rafael (Halliburton) | Zuilekom, Anthony van (Halliburton) | Pelletier, Mickey (Halliburton)
Viscosity is driven by asphaltene content and is a key parameter in the development of heavy oil fields. Understanding fluid composition and temperature and pressure-induced changes in fluid viscosity is vital for an optimized production strategy and surface facility design. A recent field and laboratory study exemplifies the steps necessary to obtain the fit-for-purpose data from heavy oil samples. This paper presents the case study of a new downhole optical composition analysis sensor used during real-time downhole fluid analysis and sampling for the first time in a Kuwait heavy oil formation.
The primary objectives of a sampling program are to confirm fluid indications on the openhole logs and collect crucial pressure/volume/temperature (PVT) samples. The downhole optical composition analysis sensor provides the information necessary to estimate a sample contamination level. It also indicates when the sample is sufficiently clean for PVT analysis. The samples should be acquired from the reservoir and maintained as single phase throughout transport to the laboratory. The pressure should be maintained higher than the asphaltene precipitation onset pressure and much higher than the bubblepoint. If the sample is not maintained higher than the asphaltene onset pressure, asphaltenes precipitate in the sample chamber and cannot be reconstituted as single phase in the laboratory. The new optical composition analyzer can also identify fluid stream components and their relative concentration in real time with laboratory-quality accuracy downhole.
Near-infrared (NIR) sensors are most commonly used to identify fluid in the wireline formation tester (WFT). The sensors work well in light hydrocarbons. However, in heavy oil, the sensor performance degrades and fails to identify the contamination level accurately. The new multivariate optical computing (MOC) technique for downhole optical composition analysis overcomes this by performing a photometric detection with the entire relevant spectral range compared to spectroscopic analysis, which is only performed over a narrow band or sparse set of channels while traditional sensors are configured. The MOC sensor also recognizes in real time the chemical nature (optical fingerprint) of analytes (e.g., methane, ethane, propane, carbon dioxide, hydrogen sulfide, water, asphaltene, aromatics, and saturates) using all of the useful information in the optical spectrum. The real-time analyte chemical composition provided by the sensor is comparable to laboratory tests conducted on the collected PVT sample.
Laboratory measurements on representative fluid samples from the correct locations early in the field development stage help develop an optimal field-development strategy. At the same time, sample integrity is maintained from the reservoir to the laboratory, which is vital. This paper discusses how the new optical compositional analysis sensor in combination with a high-resolution fluid identification sensor provides comprehensive and accurate downhole fluid composition in real time. This compares well with the laboratory-measured PVT analysis of heavy oil samples. The compositional analysis sensor optimizes pumpout time, thus helping obtain practically ideal contamination levels to begin the single-phase sampling process, which saves valuable rig time.