Thinly laminated and silty deep-water reservoirs of offshore Malaysia have historically posed difficulties in formation evaluation due to complex log responses causing uncertainties in key petrophysical properties like porosity, water saturation, net pay and productivity. Moreover, compartmentalization of the reservoirs due to extensive faulting in this area increases the evaluation challenges. Generally, thinly laminated reservoirs are evaluated either by high-resolution methods, including borehole imaging and whole core analysis; or bulk volumetric approaches, which utilize nuclear magnetic resonance (NMR) and suitable shaly sand saturation equations. Adding silt as an additional component requires a cautious combination of these two approaches. Furthermore, linking the petrophysical evaluation with depositional processes and structural settings using borehole image, acoustic log and formation pressure is key to the future development of the field. Lastly, securing clean formation fluid samples is crucial to design the production strategy. Aforesaid complete dataset was acquired in a deep-water well of offshore Malaysia to assess hydrocarbon potential. While relatively higher resistivity distinguished potential hydrocarbon bearing zones, NMR-based irreducible water saturation was a crucial indicator of possible water-free hydrocarbon production from the silty zones with high water content. Net sand was accurately calculated from the high-resolution borehole image and compared with the standard petrophysical approach. Then, a detail analysis of formation dip, facies and paleo-current direction was performed on borehole image to recognize different depositional processes and structural settings. Formation pressure data was collected extensively to understand reservoir compartmentalization. While the testing zones were selected based on higher free fluid and higher resistivity anisotropy; the precise testing depths on sand laminae were guided by high-resolution borehole image. Later, low contamination downhole fluid samples were collected using focused sampling technique. 2D NMR method and real-time downhole analysis of optical absorbance, refractive indices, fluorescence, density, viscosity and sound speed were used to differentiate formation fluid from the OBM filtrate. The reservoirs were then evaluated integrating the petrophysical properties with the depositional process and structural settings to understand their long-term production potential. This paper represented a case study of an integrated workflow of optimum data acquisition and evaluation of the thinly laminated sand-silt-clay sequence of deep-water reservoirs of offshore Malaysia. Effective and optimum integration of NMR, high-resolution borehole images, formation testing and sampling data provides the robust framework of this formation evaluation workflow to solve the complex petrophysical and geological uncertainties of these reservoirs.

Reservoir model is widely used in oil and gas industry for hydrocarbon resources assessment, development, and management with different depletion strategies. The reservoir model is built through integration of multi-disciplinary information, data and interpretation at various scales. Integration of data from various resolutions and scales is usually a big challenge in constructing reservoir model due to its impact to the model's ability to make a reliable production forecast. The objective of this study is to analyze the impact of scale changes in clastic reservoir modelling and to evaluate its implication to hydrocarbon volume in-place and fluid flow behavior. Several examples from clastic reservoirs of different geological environments were evaluated and data from various scale were incorporated in reservoir description in constructing a representative reservoir models. Reconciliation of various reservoirs properties using database such as core data, logs, DST and production/pressure were performed. Permeability upscaling was observed posing significant challenges compared to the other properties at each stage. Therefore, the paper puts more emphasize on permeability while briefly discuss the other properties. Other challenges including complex reservoir types such as thinly laminated reservoirs are also evaluated. The study demonstrates that different permeability modeling methods may give significant impact on the hydrocarbon in-place and fluid flow characteristic. In the absent of production data to verify the in-place, the uncertainty of in-place is inevitable. In addition to that, those different permeability models may also give different flow characteristic. It is concluded that by recognizing the scale difference and impact of averaging/upscaling with the guidance from production/pressure performance, robust reservoir model with representative reservoir properties could be achieved. This paper shares the best practices in integrating data from various scale/discipline and highlights the impact of the data integration at right scale in constructing robust reservoir model.

Pulsed neutron spectroscopy (PNS) is a well-established technology for characterizing reservoir saturation through cased hole, using either sigma (Σ) or carbon/oxygen (C/O) ratio measurements. However, the current technologies struggle to deliver reliable answers in complex completions. Tubing and casing, with varying tubing and annulus fluids, or dual tubing completions with changing annulus and tubing fluids represent cases in which it becomes difficult to identify fluid contacts in the formation and calculate remaining saturations. A new-generation slim pulsed neutron logging tool has been developed to deliver reliable answers in conditions that challenged existing technologies. It introduces the new petrophysical measurement, fast neutron crosssection. This measurement is highly sensitive to variations in gas volume and insensitive to variations in water volume, independent of neutron porosity and formation Σ properties. It provides high-resolution spectroscopy with a much-improved accuracy and precision of all elements measured, including the key element for oil saturation, carbon. The carbon measurement is used conventionally for C/O, and it is used directly to derive total organic carbon (TOC), which is then converted to oil saturation. This tool delivers the self-compensated Σ and neutron porosity measurements in a wide range of conditions, including complex completions and varying amount of gas in the wellbore or annulus. The field test results in this paper demonstrate the performance of this new tool in a few wells from Malaysia. All present some complex completions, from single tubing inside 7-in. casing and 8.5-in. hole to dual 3.5-in. tubing in 95/8-in. casing and 12 ¼-in. hole. Additional challenges include gas-filled annulus, multizone completion with sliding side doors (SSD) and wire-wrapped screens (WWS), and environments in which there are no water sands for C/O measurement calibration. The logging objectives include determining theoil/water contact (OWC) and the gas/water contact (GWC),quantifying the current saturation, confirming the source of water for water shutoff determination and anticipated gain, and verifying sand-filled annulus. A back-to-back comparison with the previous technology was also run in the first well, allowing a directcomparison of the measurements from the new and the existing tools in the same conditions.

Residual oil saturation (Sor) is defined as fraction of pore volume occupied by oil at the end of the oil displacement by a specific fluid. It signifies the ultimate recovery under a given displacement process and represents the endpoint of the relative permeability curves in reservoir simulation. The estimation of Sor is critical in understanding the behavior of the reservoirs during various recovery mechanisms and it is a very important measure used to decide the EOR process selection and feasibility for further exploitation of the reservoir. The residual oil saturation varies depending on lithology, pore size distribution, permeability, wettability and fluid characteristics. There are several ways to estimate the Sor including core analysis methods, well log methods, and other saturation and volumetric assessment methodologies. However, none of the methods is regarded as a single best method for determining the Sor. In addition, there could be circumstances that the remaining oil saturation (ROS) is misinterpreted as Sor. The integration of various data sources is therefore critical in estimating the true residual and remaining saturations. This paper highlight number of offshore field case studies where significant difference observed in Sorw estimation using various approaches from core and logs analysis. In these examples, SCAL data and logs in hydrocarbon column as well as swept intervals together with the wells/reservoir performances have been considered in estimating the Sor. It was observed that the production forecasting, reserve estimates, EOR mechanism are hugely affected by the Sorw estimation.

Although papers comparing some standard functions with saturation models have been published, no consistent review exists comparing the performance of most of the universal saturation-height function quantitatively. The universal SHF is fast and straightforward, but robust enough to account for limited data and while another full data acquisition and advanced analysis are in progress (partially obtained). The method can help the subsurface team in understanding the water saturation nature in quick turnaround time before the completion of ongoing volumetrics estimation. Two best practices of this workflow are rapid and robust. The paper reviews three of the universal saturation-height methods, namely those proposed by Choo, Kyi-Ramli, and K-Function. The comparisons between modelled and measured capillary pressure measurements over the most common functions and through different reservoirs are discussed. The advantages and drawbacks of each method are highlighted. Each technique is compared by investigating how accurately they model the saturation-height profiles of several wells from Offshore Malaysia. The work was carried out to independently assess which equations should be tested first during saturation-height studies. The differences for each capillary pressure between the water saturations estimated using the equations and those measured on the samples are examined in both graphic and quantitative terms. The results of this study show that Choo (2010) model is one of the better performing saturation-height functions. However, the best results are achieved using this function, but this method is also the most challenging to execute in petrophysical and static modelling software. Of the conventional equation-based approaches, the K-Function model appears to have the most utility and are recommended as first choice saturation-height models to test. It only has two inputs for the modelling comprising of RQI and HAFWL. This study continues the extended concepts of Adams (2016) and Harrison (2001) to describe quantitative comparisons between modelled and measured capillary pressure measurements over the functions and through different reservoirs. The review presented could not include all possible equations, but shows which of the most frequently cited functions, is likely to be of utility. Areas for future improvement are also highlighted.