Since early 1990's, Downhole Fluid Analysis (DFA) has been developed to monitor mud filtrate contamination for Wireline Formation Tester downhole sampling. DFA can also provide accurate reservoir fluid information in real time such as hydrocarbon composition including CO2. However, DFA technology cannot measure Nitrogen because N2 has no absorption in the Near Infrared Region (NIR). Therefore, it cannot be directly detected with any spectrometer measurement downhole. This paper will present innovative methods that can be used to predict the amount of N2 in each reservoir. These new techniques can help many clients in the EAG and as well as other basins to accurately quantify N2 without the need to wait for PVT laboratory analysis which generally takes several months to complete. Detection of non-hydrocarbon gases in oil and gas fluids, such as nitrogen gas, is very important for reservoir assessment and management. N2 content affects reserve estimation, especially in the area where reservoir fluids have high N2 contents. In our experience, there are several basins in Asia where N2 and CO2 coexist in the same reservoirs. N2 was charged into reservoirs from the source rock in the same geological time as Hydrocarbon (HC). The CO2 then later charged into the same reservoirs. Xu et al (2008) and Mullins (2019) suggested that the ratio of HC. and N2 are in proportional for each basin. However, the CO2 which was later charged are variable in each reservoir depending on CO2 source and charging area. The relationship between HC. and N2 can be used to predict amount of N2 using three proposed methods (1) Basin Base Method (2) Iteration Methods using DFA spectrometer and InSitu Density measurements., and (3) Equation of State (EOS) Method. This nitrogen prediction techniques were developed to better characterize reservoir fluids and overcome the limitation of the existing technology that's unable to detect and measure nitrogen at downhole conditions. This method can offer extra information, especially for our new Ora Intelligent Wireline Formation Tester technology where answer products will be expanded to tailor client objectives. The N2 and HC. relationship from each basin are examined in detail from our DFA and PVT data base. The ratio of N2 and HC. were then recorded as initial value for Basin Base Method. Then the second N2 prediction technique that uses individual hydrocarbon compositions and downhole density measurements were conducted to calculate missing N2 mass from spectrometer measurements. A ternary diagram was prepared to visualize and determine correlation of the gas composition components. It was found that straight line can be obtained on the Ternary diagram between N2, HC., and CO2 for each reservoir. A detailed calculation based on fluid components and partial densities together with iteration process allows to estimate the mass percentage of nitrogen. The results were then compared with actual value from PVT lab. These nitrogen prediction techniques already have been tested and validated using various datasets from South East Asia and other. This technique can be extended to be part of Reservoir Fluid Geodynamic (RFG) to evaluate lateral reservoir connectivity and to better understand CO2 and N2 charge to reservoirs.

Mini-DST, as alternative to conventional DST, has been in the industry more than 30 years, and its economic value has showed the advantage over DST, however limited permeability-thickness and investigated radius is a bottle neck which in many cases has much uncertainty to support reservoir characterization. The recently developed Deep Transient Testing technology improved its performance over former mini-DST technology in terms of longer pumping time, larger produced volume, and greater investigation radius. This paper presents a study in a variety of environments and applications, demonstrating how formation testing is being planned, acquired, and used in new ways, including Deep Transient Testing (DTT). The comprehensive radial model approach based on DTT using integration of well logs, numerical simulation grid and pressure transient behavior is built for the first time. To design an effective approach to generate a radially gridded single well predictive model, this workflow requires knowledge of well performance, petrophysics and reservoir simulation. This simulation workflow started with a petrophysical interpretation together with well surveys which serve as essential input data to build a single well predictive model. Rock typing using Heterogenous Rock Analysis (HRA) method resulted in a more detailed properties population along the vertical direction in tartan grid. Defining completions of the well and followed by conversion of tartan grid to radial grid was performed to accurately capture the pressure transient response near wellbore. The radial grid model was setup as a DTT model to forecast the pressure transient behavior of the reservoir incorporating the technology of a new intelligent wireline formation testing platform in the simulation inputs. The outcome of this study produced multiple scenarios incorporating different reservoir tightness from low to high with known thickness. The reason is that as the formation gets tighter; it is more challenging to achieve radial flow and predict producibility. By having uncertainty study in place, we can understand the outcome of each scenario then provide quantitative data to make decision on DTT feasibility, inlet and flow manager selections based on simulation result. This methodology not only optimizes the operation planning and execution, but also estimates pressure drop and the time needed to be on stationary for operational risk mitigation, which are in place to help operators improve certainty in decision making. The case study showed that the advanced 3D radial grid predictive model method addressed the advantage of Interval Pressure Transient Testing (IPTT) and DTT in accessing and evaluating reservoir connectivity, heterogeneity, and drainage radius. In this paper, we are the pioneer in this robust Intelligent FT integrated workflow globally, which was successfully implemented together with all wireline operations within planned time frame involved and delivered with exceptional results.

The past few years have been challenging for the oil and gas industry. Many processes and operations have needed to adapt to lower oil and gas prices, caused in part by the COVID-19 pandemic. Understanding reservoir producibility and proving reserves are keys to generating a reservoir field development plan (FDP). However, the different processes to obtain such answers are strongly dependent on cost. The value of information is an extremely important criterion for operators to decide whether to proceed with their discoveries. In an interval pressure transient test (IPTT), a formation tester is used to pump a fluid from a single point or small interval of the formation into the wellbore. Zones of interest can be isolated and tested separately zone by zone. Mud filtrate and reservoir fluids are pumped continuously using the downhole pump, and a downhole fluid analyzer (DFA) is used to monitor the fluid cleanup process. The post-pumping p pressure buildup can be analyzed in a similar manner to traditional well test analysis. Such IPTT have been available since 1980s; however, comparisons of IPTT to actual well tests and other permeability measurements were rarely published until the early 2000s. IPTT have been widely used in the past 20 years, especially in combination with dual packers, and more recently with single packers. Operation efficiency and safety have improved significantly. However, interpretation of the pressure transient obtained from an IPTT is not always well understood. Frequently asked questions (FAQs) include the following: What is an IPTT or a vertical interference test (VIT)?How does an IPTT compare with other permeability measurements?What are the different scales of pressure transient data?How do we upscale zone permeability to an entire reservoir interval?What is next? This paper will address these questions using both reservoir simulation and field data. The field examples are from different environments, ranging from shallow marine to turbidite to deepwater environments, with different fluid systems, such as black oil, heavy oil, waxy oil, gas, and gas condensate. Geographically, the field data include examples from South East Asia and the Middle East. Permeability obtained from pretests, IPTT, nuclear magnetic resonance (NMR), core analyses, and well testing will be compared. Recently deep transient testing (DTT) has been introduced in the industry. With DTT, we can flow faster and longer than previously possible with formation testers, enabling pressure transient analysis in higher permeability and thicker formation. Further data quality improvements come from new, high-resolution gauges deployed with an intelligent wireline formation testing platform. This paper includes a review of the DTT method with several field examples. Finally, the advantages and disadvantages of the different testing methods are discussed relative to the test objectives, with the intent to provide a cost-effective data selection method to ensure sufficient FDP input and to justify the value of investment to the relevant stakeholder.