Unconventional tight reservoir sands have low porosity and very low permeability (mostly less than 0.1mD) due to their fine grain size and poor grain sorting that is often exacerbated by extensive diagenetic effects such as cementation and compaction. Petrophysical evaluation in these formations is very challenging. Conventional downhole logs such as density, neutron, sonic, gamma ray and resistivity measurements provide limited information on pore size variations and often missed Key geological features especially at the early stages of reservoir development. Fluid characterization at the earliest possible stage is paramount to guide the development of these reservoirs where tight well spacing, stimulation (fracturing) and or horizontal well completion is usually required. The main objective of this paper is to show a process of fluid characterization in unconventional tight sand that guides reservoir stimulation. Porosity partitioning using nuclear magnetic resonance (NMR) logging data helps address these challenges in three distinct steps. First, the 1-dimensional (1D) NMR T2 spectrum quantifies the amount of bound and free fluids pore space and reveals reservoir quality with unique sensitivity. In this step, the NMR fluid substitution method was utilized to ensure consistency between NMR logs in oil-based mud (OBM) and water-based mud (WBM) systems. Second, the free fluids are further subdivided into hydrocarbon and water phases using a 2-dimensional (2D) NMR T1/T2 processing technique. Third, the hydrocarbon phase is subdivided again into liquid and gas phases where a gas flag is turned on whenever the NMR gas signal significantly exceeds measurement uncertainty. This enables detection of live hydrocarbons with high gas-oil ratio (GOR). This paper presents the integration of NMR analysis into petrophysical evaluation of an unconventional tight sand reservoir. The evaluation helped optimize the best interval for stimulation. Fluid sample acquired with formation tester correlated very well with NMR log-based fluid prediction. Integrated NMR analysis, including bound fluid vs. free fluid analysis and 2D NMR-based fluid characterization, including gas indicator flag, was applied to establish the presence and type of hydrocarbon in tight sands and select the best representative interval for stimulation. The continuous reservoir quality and fluid distribution profiles provided by these logs were beneficial for the geological understanding and complex formation testing operations in this challenging reservoir.

Traditional approach relys on reservoir pressures to assess reservoir connectivity in low permeability formations. This paper will present a new approach of applying Reservoir Fluid Geodynamics (RFG) through Flory Huggins-Zuo (FHZ) equation of state (EOS) for asphaltene distributions to determine reservoir connectivity and fluid typing in undrilled locations. FHZ-EOS asphaltene gradient was constructed with data from downhole fluid samples in different wells covering two zones (A and B). The downhole fluid analysis (DFA) results were validated with laboratory analysis. The structural continuity of both zones across the study area in the field was validated using a wide range of geological data including conventional open-hole logs. The resulting FHZ-EOS model formed the basis for fluid typing, correlation and connectivity across layers. The DFA data was used in real time at different stages of formation fluid sampling cleanup to correlate the samples quality with the existing model. The DFA data used in real time in conjunction with the pre-built FHZ-EOS model, improved the sampling quality check process and confidence in the sample quality, especially in the presence of low gas oil ratio (GOR) fluids. This improvement in real time data quality helped to optimize the pumping time and reduce the number of samples in each reservoir since the confidence in the sample quality was high. The constructed asphaltene gradient from the FHZ-EOS model also confirm the hydrocarbon continuity both vertically and laterally in undrilled locations with the study area of the field. For each of the zones, the data analysis shows a clear and distinct asphaltene gradient with different asphaltene molecule sizes. This supports the presence of heavy oil / tar towards the deeper sections of the area of interest within the field. It also predicted the depths / location of the heavy oil / tar, which will assist in the field development plan and flow assurance.

Recent developments in surface logging and the need for sophisticated information on reservoir content and type in the oil industry have led to the availability of real-time advanced fluid solutions assisting in informed decisions while drilling. The objective of this study was to identify possible fluid contacts and acquire PVT quality sample data while drilling Paleozoic formations. This is accomplished by extracting and analysing formation gas from the drilling fluid employing the Advanced Formation Gas Extraction System for formation evaluation with a high-resolution chromatograph. The Advanced Formation Gas Extraction System provided consistent flow and heated mud and maintained constant temperature conditions. Thus, it provided an accurate chromatographic breakdown of the formation gas extracted from the drilling fluid at surface. The chromatograph was able to detect the hydrocarbons from the light to heavy factions, methane (C1) to pentane (C5), and also extended the detection range to include the dominant C6, C7, C8, aromatics and lighter alkenes. Gas ratio analysis of the detected hydrocarbon components enabled us to evaluate the reservoir fluid content and to identify and characterize the formation fluid and possible fluid contacts. The results, validated by correlation and comparison with other data such as wireline logs, well tests and PVT results assisted in the characterization of lithological changes, possible fluid contacts, vertical fluid differentiation in multi-layered intervals, and drill bit metamorphism (thermal cracking) effect. The comparison between surface gas data analysis and PVT data confirms the consistency between the gas show and the corresponding reservoir fluid composition.