Moving Gas Geochemical Analysis from Lab to Field by Advanced Gas Sensor for Onsite Fluid Characterization and Time-Lapse Monitoring

Natural gas is sampled or produced throughout the lifespan of a field, including geochemical surface survey, mud gas logging, formation and well testing, and production. Detecting and measuring gas is a common practice in many upstream operations, providing gas composition and isotope data for multiple purposes, such as gas show, petroleum system analysis, fluid characterization, and production monitoring. Onsite gas analysis is usually conducted within a mud gas unit, which is operationally unavailable after drilling. Gas samples need be taken from the field and shipped back to laboratory for gas chromatography and isotope-ratio mass spectrometry analyses. Results take a considerable time and lack the resolution needed to fully characterize the heterogeneity and dynamics of fluids within the reservoir. We are developing and testing advanced sensing technology to move gas composition and isotope analyses to field for near real-time and onsite fluid characterization and monitoring. We have developed a novel QEPAS (quartz-enhanced photoacoustic spectroscopy) sensor system, employing a single interband cascade laser, to measure concentrations of methane (C1), ethane (C2), and propane (C3) in gas phase. The quartz fork detection module, laser driver, and interface are integrated as a small sensing box. The sensor, sample preparation enclosures and a computer are mounted in a rack as a gas analyzer prototype for the bench testing for oil industry application. Software is designed for monitoring sample preparation, collecting data, calibration and continuous reporting sample pressure and concentration data. The sensor achieved an ultimate detection limit of 90 ppb (parts per billion), 7 ppb and 3 ppm (parts per million) for C1, C2, and C3, respectively, for one second integration time. The detection limit for C2 made a record for QEPAS technique, and measuring C3 added a new capability to the technique. However, the linearity of the QEPAS sensing were previously reported in the range of 0 to 1000 ppm, which is mainly for trace gas detection. In the study, the prototype was separately tested on standard C1, C2, and C3 with different concentrations diluted in dry nitrogen (N2). Good linearity was obtained for all single components and the ranges of linearity were expanded to their typical concentrations (per cent, %) in natural gas samples from oil and gas fields. The testing on the C1-C2 mixtures confirms that accurate C1 and C2 concentrations in % level can be achieved by the prototype. The testing results on C1-C2-C3 mixtures demonstrate the capability of simultaneous detection of three hydrocarbon components and the probability to determine their precise concentrations by QEPAS sensing. This advancement of simultaneous measuring C1, C2 and C3 concentrations, with previously demonstrated capability for hydrogen sulfide (H2S) and carbon dioxide (CO2) and potential to analyze carbon isotopes (13C/12C), promotes QEPAS as a prominent optical technology for gas detection and chemical analysis. The capability of measuring multiple gas components and the advantages in small sensor size, high sensitivity, quick analysis, and continuous sensing (monitoring) open the way to use QEPAS technique for in-situ and real-time gas sensing in oil industry. The iterations of QEPAS sensor might be applied in geochemical survey, on-site fluid characterization, time-lapse monitoring of production, and gas linkage detection in the oil industry.

Accurate Live Interfacial Tension for Improved Reservoir Engineering Practices

Current reservoir simulators use interfacial tension (IFT) values derived from dead oil measurements at ambient conditions or predicted from literature correlations. IFT is highly dependent on temperature, pressure and fluid composition. Therefore, knowledge of the IFT value at reservoir conditions is essential for accurate reservoir fluid characterization. This study compares IFT values from dead and live oil measurements and the results of literature predicted values, thereby clearly showing the weakness of existing correlations when trying to predict crude oil IFT. A total of ten live oils was sampled for this study. Using the pendent drop technique, IFT was measured for each oil at different conditions: in the under-saturated region at reservoir pressure and temperature, in the saturated region at reservoir temperature, and for dead oil at ambient conditions. Basic PVT properties such as gas to oil ratio (GOR), gas and liquid composition, density, viscosity and molecular weight were also measured. The bubble point for each oil was identified to define the pressure step in the saturated region for extra IFT measurement. The equilibrium IFT values for the live oils were generally higher than for the corresponding dead oils. For oils where this general trend was not observed, contaminations were found in the crude samples. The use of current literature correlations does not allow to predict correct reservoir IFT. Therefore, this study provides accurate live IFT values for a variety of reservoir fluids and conditions in combination with live oil properties, highly beneficial to reservoir engineers, allowing better oil production planning.

Gas Deviation Factor Calculation Made Easy and Accurate Using an IR 4.0 Tool

Gas deviation factor (z-factor) and other gas reservoir fluid properties, such as formation volume factor, density, and viscosity, are normally obtained from Pressure-Volume-Temperature (PVT) experimental analysis. This process of reservoir fluid characterization usually requires collecting pressurized fluid samples from the wellbore to conduct the experimental work. The scope of this paper will provide an alternative methodology for obtaining the z-factor. An IR 4.0 tool that heavily utilizes software coding was developed. The advanced tool uses the novel apparent molecular weight profiling concept to achieve the paper objective timely and accurately. The developed tool calculates gas properties based on downhole gradient pressure and temperature data as inputs. The methodology is applicable to dry, wet or condensate gas wells. The gas equation of state is modified to solve numerically for the z-factor using the gradient survey pressure and temperature data. The numerical solution is obtained by applying an iterative computation scheme as described below:A gas apparent molecular weight value is initialized and then gas mixture specific gravity and pseudo-critical properties are calculated.Gas mixture pseudo-reduced properties are calculated from the measured pressure and temperature values at the reservoir depth.A first z-factor value is determined as a function of the pseudo-reduced gas properties.Gas pressure gradient is obtained at the reservoir depth from the survey and used to back-calculate a second z-factor value by applying the modified gas equation of state.Relative error between the two z factor values is then calculated and compared against a low predefined tolerance.The above steps are reiterated at different assumed gas apparent molecular weight values until the predefined tolerance is achieved. This numerical approach is computerized to perform the highest possible number of iterations and then select the z-factor value corresponding to the minimum error among all iterations. The proposed workflow has been applied on literature data with known reservoir gas properties, from PVT analysis, and showed an excellent prediction performance compared to laboratory analysis with less than 5% error.

Accuracy and Precision of Reservoir Fluid Characterization Tests Through Blind Round-Robin Testing

Objectives/Scope: Oil and gas operators use a variety of reservoir engineering workflows in addition to the reservoir, production, and surface facility simulation tools to quantify reserves and complete field development planning activities. Reservoir fluid property data and models are fundamental input to all these workflows. Thus, it is important to understand the propagation of uncertainty in these various workflows arising from laboratory fluid property measured data and corresponding model uncertainty. The first step in understanding the impact of laboratory data uncertainty was to measure it, and as result, ADNOC Onshore undertook a detailed study to assess the performance of four selected reservoir fluid laboratories. The selected laboratories were evaluated using a blind round-robin study on stock tank liquid density and molar mass measurements, reservoir fluid flashed gas and flashed liquid C30+ reservoir composition gas chromatography measurements, and Constant Mass Expansion (CME) Pressure-Volume-Temperature (PVT) measurements using a variety of selected reservoir and pure components test fluids. Upon completion of the analytical study and establishing a range of measurement uncertainty, a sensitivity analysis study was completed using an equation of state (EoS) model to study the impact of reservoir fluid composition and molecular weight measurement uncertainty on EoS model predictions. Methods, Procedures, Process: A blind round test was designed and administered to assess the performance of the four laboratories. Strict confidentiality was maintained to conceal the identity of samples through blind test protocols. The round-robin tests were also witnessed by the researchers. The EoS sensitivity study was completed using the Peng Robinson EoS and a commercially available software package. Results, Observations, Conclusions: The results of the fully blind reservoir fluid laboratory tests along with the statistical analysis of uncertainties will be presented in this paper. One of the laboratories had a systemic deviation in the measured plus fraction composition on black oil reference standard samples. The plus fraction concentration is typically the largest weight percent component in black oil systems and, along with the plus fraction molar mass, plays a crucial role in establishing the mole percent overall reservoir fluid compositions. Another laboratory had systemic issues related to chromatogram component integration errors that resulted in inconsistent carbon number concentration trends for various components. All laboratories failed to produce consistent molecular weight measurements for the reference samples. Finally, one laboratory had a relative deviation for P-V measurements that were significantly outside the acceptable range. The EoS sensitivity study demonstrates that the fluid composition and stock tank oil molar mass measurements have a significant impact on EoS model predictions and hence the reservoir/production models input when all other parameters are fixed. Novel/Additive Information: To the best of our knowledge, this is the first time such an extensive and fully blind round-robin test of commercial reservoir fluid characterization laboratories has been completed and published in the open literature. The industry should greatly benefit from this first-of-its-kind blind round-robin dataset being made available to all. The study provides the basis, protocols, expectations, and recommendations for such independent round-robin testing for fluid characterization laboratories on a broader scale.

Ultra-Deep LWD Electromagnetic Directional Resistivity for Waterflood Mapping – A Game Changer

Abu Dhabi's thick Lower Cretaceous carbonate reservoirs experience injection water overriding oil. The water is held above the oil by negative capillary pressure until a horizontal borehole placed at the reservoir base creates a small pressure drawdown. This causes the water above to slump unpredictably towards the horizontal producer, increasing water cut and eventually killing the well under natural lift after a moderate amount of oil production. Water slumping is difficult to forecast using the reservoir model. This paper showcases the successful deployment of an ultra-deep electromagnetic directional resistivity (UDDE) instrument to map injection water movement. The UDDE instrument selected for the 6-in. horizontal hole was a 4¾-in. OD multifrequency tool with configurable transmitter-to-receiver spacings. Pre-well modeling using hybrid deterministic 1D resistivity inversions was conducted for the candidate well to investigate the resistivity tool's ability to identify water slumping at distances 60-100 ft TVD above the planned well trajectory. The inversions aided the selection of optimum operating frequencies, transmitter-to-receiver spacings and BHA configuration. During operations, multiple 1D and 3D inversions were run in the cloud real time during drilling to provide simultaneous deep and shallow resistivity inversions for early identification of the water fronts and structural changes, and near wellbore changes to geosteer and maximize reservoir contact in the complex layered reservoir. Real-time 1D and 3D deep inversion results indicated the resistivity tool had a depth of reliable waterflood detection of more than 80 ft. While drilling, an interpreted subseismic fault was encountered which appeared to influence how water moved in the reservoir. Water slumped closest through the sub-seismic fault towards the well path. Past the fault, the waterfront receded upwards away from the well bore. The data proved useful for updating the static model, providing a snapshot of water flood areas, reservoir tops and faults with throw, helping to optimize the completion design to defer water production and enhance oil production. Furthermore, it captured resistivities of target, underlying and overlying reservoirs to integrate with other geology and geophysics data for better reservoir and fluid characterization near the drilled area. The positive results of this case study encouraged field-wide implementation of this technology for waterflood mapping. The information provided allowed petroleum engineers to adjust the completion design to delay water breakthrough. This proactive approach to waterflood field management improves cumulative oil production and recovery factors according to mechanistic models which have been built and tested.

Automated determination of interfacial tension and contact angle using computer vision for oil field applications

Contact angle and surface tension are the two most widely used surface analysis approaches for reservoir fluid characterization in petroleum industries. The pendant drop method has among the most widely used techniques for the estimation of surface tension. The present work utilizes a python-based computer program to automatically determine interfacial tension (IFT) and contact angle from the pendant drop image acquired from a typical pendant drop apparatus. The proposed program uses python-based image processing libraries for the analysis of the pendant drop image. Also, the program is tested on images acquired from the standard solutions for the IFT and contact angle calculation showing promising results with a standard deviation of less than 1.7 mN/m.

Successful Reservoir Fluid Characterization and Testing While Overcoming the Challenges of Falling Oil Price and a Pandemic: A First for an Integrated Brown Field Alliance Project in Sarawak, Malaysia

A brown field, offshore Sarawak, Malaysia, with multiple sub-layered laminated sands of varied pressure regimes and mobility ranges, was challenged by depletion, low mobility and uncertainty in the current fluid types and contacts. Optimal dynamic fluid characterization and testing techniques comprising both Wireline and Logging While Drilling (LWD) were applied in nine development wells to acquire reliable formation pressure data and collect representative fluid samples including fluid scanning. Some of the latest technologies were deployed during the dual crises of falling oil price and the Covid-19 pandemic. The S-profile wells were drilled using oil-base mud (OBM) with an average deviation of 60 degrees. Formation Pressure While Drilling (FPWD), Fluid Sampling While Drilling (FSWD) and wireline formation testing, and sampling were all utilized allowing appropriate assessment of zones of interest. Various probe types such as Conventional Circular, Reinforced Circular, Elongated, Extra-Elongated and Extended Range Focused were used successfully, ensuring that the right technology was deployed for the right job. Formation pressure and fluid samples were secured in a timely manner to minimize reservoir damage and optimize rig time without jeopardizing the data quality. As a classified crisis due to the pandemic, rather than delaying the operations, a Remote Operations Monitoring and Control Center was set-up in town to aid the limited crew at rig site. A high success rate was achieved in acquiring the latest formation pressure regimes, fluid gradients, scanning and sampling, allowing the best completion strategy to be implemented. With the selection of the appropriate probe type at individual sands, 336 pressure tests were conducted, 44 fluid gradients were established, 27 fluid identification (fluid-id / scanning) pump-outs were performed, and 20 representative formation fluid samples (oil, gas, water) were collected. Amongst the Layer-III, Layer-II and Layer-I sands, Layer-I was tight, with mobility < 1.0 mD/cP. Wireline focused probe sampling provided clean oil samples with 1.4 to-3.7 wt. % OBM filtrate contamination. The water samples collected from Layer-II during FSWD proved to be formation water and not injection water. The wells were thus completed as oil producers. Reliable fluid typing and PVT quality sampling at discrete depths saved rig time and eliminated the requirement of additional runs or services including Drill Stem Testing (DST). This case study has many firsts. It is the first time where latest fluid characterization and testing technologies in both Wireline and LWD were deployed for an alliance project in Malaysia and that too during dual crises of falling oil price and the pandemic aftermath. Overcoming various challenges including limited rig site manpower, there was no delay in completing the highly deviated wells with tight formations in a single drilling campaign and provided rig time savings. For the purpose of this case study, two wells have been discussed. First well used the wireline focused sampling technology and the second used the FSWD technology.

Minimum Miscibility Pressure of Gas Injection in Unconventional Reservoirs

Unconvnetional reservoirs are predominantly consisted of nanoscale pores. The strong confinement effect within nanopores imposes significant deviations to the confined fluid phase behavior. Minimum miscibility pressure (MMP) in unconventional reservoirs, as a parameter highly related to the phase behavior of confined fluids, is inevitably affected by the nanoscale confinement. The objective of this work is to investigate the impact of nanoscale confinement on MMP of unconventional reservoir fluids and to recognize a reliable theoretical approach to determine the MMP values in unconventional reservoirs. A modified Peng-Robinson equation of state (PR EOS) applicable for confined fluid characterization is applied to perform the EOS simulation of the vanishing interfacial tension (VIT) experiments. The MMP of a binary mixture at bulk and 50 nm are obtained via the VIT simulation. Meanwhile, the multiple mixing cell (MMC) algorithm coupled with the modified PR EOS is applied to compute the MMP for the same binary system. Comparison of the calculated results to the experimental values recognize that the MMC approach has higher accuracy in determining the MMP of confined fluid systems. Moreover, this approach is then applied to predict the MMP values of both Bakken and Eagle Ford oil at different pore sizes with various injected gases. Results demonstrate that the nanoscale confinement causes drastic suppression to the MMP of unconventional reservoir fluids and the suppression rate increases with decreasing pore size. The drastic suppression of MMP is highly favorable for the miscible gas injection EOR in unconventional reservoirs.