Capillary pressure is a crucial step in reservoir properties definition and distribution during static and dynamic modelling. It is a key input into saturation height modelling (SHM) process, understanding the fluid distribution and into reservoir rock typing process. Capillary pressure models provide an insight into field dynamic for the identification of swept zones and provide another calibration besides the log calculated saturation. Capillary pressure curve tends to be more complex in carbonates in comparison to sandstone reservoirs because of post deposition processes that impact the rock flow properties, hence complex pore throat size distribution (uni-modal, bi-modal or tri-modal). Therefore, accurate determination of this property is the cornerstone in the reservoir characterization process.
Capillary pressure can be obtained using several experimental techniques, such as mercury injection (MICP), centrifuge (CF) and porous plate (PP). Each method has its own inherited advantages and disadvantages. The MICP method tends to be faster, cheaper and provides a full spectrum of pore throat size of a plug. Whereas, the PP method can be carried out at reservoir conditions with minimum required corrections.
In this paper, a detailed workflow for quality control capillary pressure is discussed. The workflow is sub-divided into three main parts: Instrumental and experimental level, core measurement level and logs level. Experimental level starts with proper designing the actual procedure of the capillary pressure experiment. Parameters such as pore volume, bulk volume and grain density are investigated at core measurement level. In geological-petrography montage, all petrography data; X-Ray Diffraction (XRD), Scanning Electron Microscope (SEM), thin section and computed tomography scan (CT) are used along with the capillary pressure curve for assessment. Comparing various methodologies of experimental technique carried out on twin plugs, if exist, are also investigated. The capillary pressure that passes the previous QC steps is used as input into saturation-point comparison as a logs level QC. The saturation calculated from capillary pressure is compared to log-derived water saturation eliminating any issues with porosity and permeability of the trims and provides insight to the uncertainty level in the model. As an additional step, the MICP measurements are fitted with bi-modal Gaussian basis functions with two practical benefits. First, the quality of this fitting is a useful indicator for the evaluation of pore structure complexity and the identification erroneous measurements. Second, the fitting parameters are useful inputs for geological interpretation, rock typing and SHM. This rapid and automated workflow is a useful tool for screening, processing and integration of large-scale capillary pressure data sets, a key step in integrated reservoir description, characterization and modelling.
Horst, Juun van der (Shell International E&P) | Panhuis, Peter in 't (Shell International E&P) | Al-Bulushi, Nabil (Shell International E&P) | Deitrick, Greg (Shell International E&P) | Mustafina, Daria (Shell International E&P) | Hemink, Gijs (Shell International E&P) | Groen, Lex (Shell International E&P) | Potters, Hans (Petroleum Development Oman) | Mjeni, Rifaat (Petroleum Development Oman) | Awan, Kamran (Petroleum Development Oman) | Rajhi, Salma (Petroleum Development Oman) | Bakker, Goos
In the past decade, Fiber-Optic (FO) based sensing has opened up opportunities for in-well reservoir surveillance in the oil and gas industry. Distributed Temperature Sensing (DTS) has been used in applications such as steam front monitoring in thermal EOR and injection conformance monitoring in waterflood projects using (improved) warmback analysis and FO based pressure gauges are deployed commonly. In recent years
There are still improvements to be made in enabling Distributed Sensing infrastructure, such as handling and evaluation of very large data volumes, seamless FO data transfer, the robustness & cost of the FO system installation in subsea installations, and the overall integration of FO surveillance into traditional workflows. It will take some time before all these issues are addressed but we believe that FO based applications will play a key role in future well and reservoir surveillance.
In this paper we present a recent example of single-phase flow profiling using DAS. The example is from a long horizontal, smart polymer injector operated by Petroleum Development Oman (PDO).
There have been a number of major heavy oil discoveries in Oman in recentyears. In order to devise efficient and cost effective recovery mechanismcareful and detailed subsurface understanding of these fields is critical. Tothis end, petrophysical understanding plays a critical role, as it represents abasic building block of the static and dynamic models. The field under study isa fractured carbonate reservoir with high viscous oil. It is believed that thisreservoir has gone through various cycles of drainage and imbibition. Thus, inaddition to the complex geology, understanding of fluid distribution and fluidmobility are among major challenges that detailed petrophysical evaluationneeds to address. Understanding these parameters will help determine thefeasibility of the recovery methodology to be adopted.
This paper details a novel petrophysical workflow that integrates 3D NMR, multiarray/multi frequency dielectric measurements, borehole images, and coreanalysis. The core analysis focused on capillary pressures, Dean-Stark, androck typing. Fracture studies included detailed image analysis and extensivefall off test for understanding the nature and distribution of the fracturenetwork in the reservoir. The wealth of well data coupled with geological anddynamic data reduced the overall reservoir properties and fluid distributionuncertainties.
Dielectric data provided resistivity independent saturations validated byDean-Stark data. Combining dielectric and 3D NMR data allowed better formationcharacterization and fluid type evaluation and their present day distribution.Additionally, this combination indicated that water is not at an irreduciblestate in the reservoir. This was supported by the core saturation heightfunction which indicated that present day saturation should be much higher ifthe reservoir was in drainage mode. These results were crucial to evaluatedevelopment options, underlying uncertainty/risks of this reservoir, and designoptimum future data acquisition requirements.