|Theme||Visible||Selectable||Appearance||Zoom Range (now: 0)|
Methane (CH4), the primary constituent of natural gas and is the second-most abundant greenhouse gas after carbon dioxide (CO2), accounts for 16% of global emissions. The lifetime of methane in the atmosphere is much shorter than CO2, but CH4 is more efficient at trapping radiation than CO2. Pound for pound, the comparative effect of CH4 is more than 25 times greater than CO2 over a 100-year period. Natural-gas emissions from oil and gas facilities such as well sites, refineries, and compressor stations can have significant safety, economic, and regulatory effects. Continuous emission detection systems enable rapid identification and response to unintended emission events.
The objective of this paper is to define the relationship between diagenetic processes observed in core, reservoir thickness measured in wells and the thickness distribution at the field scale using seismic attributes. The delineation of a robust geological reservoir quality concept honouring all scales of observation is of extreme importance when defining an FDP based on a horizontal drilling programme.
Pressure dissolution features measured in core provide evidence that the intensity and abundance of chemical compaction varies across Reservoir 2 in Oilfield A. Reservoir thickness was measured in wells across the field. A negative correlation was found between reservoir thickness and the abundance of chemical compaction features field wide. This observation about reduction in reservoir thickness was subsequently validated using 3D seismic interpretation and attributes and ultimately implemented in structural reservoir modeling. Mapping of Reservoir 2 thickness from wells (point data) identified a trend of decreasing thickness across the field from the crest in the north-west (thickest) to the flank in the south-east (thinnest). The seismic interpretation of top and base reservoir reflections in both the time and depth domain allow the definition of the thickness trend to be calibrated with well data and extrapolated between them with increased confidence. Furthermore, a thickness trend is observed in seismic attributes (e.g. Amplitude and Sweetness) and in P-impedance from seismic inversion. By performing multivariate analysis on the seismic attributes it is possible to establish a strong relationship between geological process, thickness reduction and seismic response at the field scale.
The key finding from reconciling these different types and scales of data was the observation that reservoir thickness is positively correlated to reservoir quality. The presented methodology is a practical solution to estimate reservoir thickness variation and therefore the range of expected reservoir properties using multilinear regression of a combined set of seismic attributes. Quantification of the compaction effect on reservoir thickness reduction and reservoir quality shows a relationship that can be predicted with a sufficient level of confidence. Multiple realizations of expected thickness values are used to define various structural framework realizations within a distribution of equiprobable reservoir property scenarios.
The cross validation of direct measurements from core and logs, facilitated the development of a strong geological concept in Oilfield A. The integration of these observations with indirect measurements of density and velocity (impedance) from 3D seismic data enabled the concept to be reconciled field wide. The product has the ability to predict reservoir property distribution field wide using a simple tool (reservoir thickness from 3D seismic) grounded in a detailed understanding of the diagenetic overprint. The ability to generate a validated reservoir property distribution concept allows confident predictability and the anticipation of complex reservoir heterogeneities away from well control using 3D seismic. This tool will be used for efficient well placement, based on robust geomodeling, high confidence well planning and ultimately a more robust Field Development Plan.
The chemical reactions creating buildups of scale that can clog a well can be replicated in a chemical lab, but researchers are finding many more variables on the surfaces of pipes that need to be considered. At the 2017 SPE Oilfield Chemistry Conference, an assistant professor from Heriot-Watt University discusses the optimization of squeeze treatments delivered by diving support vessels. This paper describes a novel method of chemical dosage based on time-resolved fluorescence (TRF) that allows a simple, accurate, and efficient quantification of chemicals below parts-per-million ranges, even for double (scale/scale, scale/corrosion) quantification. Rigless coiled-tubing-unit (CTU) interventions can be effective in returning to production wells that have lost electrical-submersible-pump (ESP) efficiency because of organic, inorganic, or mixed scale deposits. The gas-producing carbonate zones of the Ghawar field in eastern Saudi Arabia have been affected by extensive iron sulfide (FeS) scale deposition, reducing overall gas production and increasing risks during well interventions.
This paper describes a material designed to interact specifically with highly corroded and weathered pipe to enable in-place application and refurbishment. As part of an effort to evaluate existing riser systems, an operator launched an inspection and testing program to investigate risers retrieved following well abandonment after a service life of nearly 10 years in the Gulf of Mexico. This paper describes a novel method of chemical dosage based on time-resolved fluorescence (TRF) that allows a simple, accurate, and efficient quantification of chemicals below parts-per-million ranges, even for double (scale/scale, scale/corrosion) quantification.
The industry increasingly relies on forecasts from reservoir models for reservoir management and decision making. However, because forecasts from reservoir models carry large uncertainties, calibrating them as soon as data come in is crucial. The complete paper explores the use of multilevel derivative-free optimization for history matching, with model properties described using principal component analysis (PCA) -based parameterization techniques. The results of the authors’ research showed promising benefits from the use of a systematic procedure of model diagnostics, model improvement, and model-error quantification during data assimilations. A challenging problem of automated history-matching work flows is ensuring that, after applying updates to previous models, the resulting history-matched models remain consistent geologically.
Advanced machine-learning methods combined with aspects of game theory are helping operators understand the drivers of water production and improve forecasting and economics in unconventional basins. The complete paper discusses the importance of adequate preparation and the approaches used to overcome challenges of EOR operations, including handling back-produced polymer. Several well-stimulation products and techniques have been seen to benefit well productivity from recent field trials and implementations in carbonate reservoirs, including simpler acid fluid systems, integrated work flows, and coiled-tubing bottomhole assemblies. Researchers use novel methodology to measure the thermo-electric properties of native crude. Business Development VP Kirstie Boyle joins The SPE Podcast to talk startups.
FLITE Material Sciences says that its unique lasering process can be used on just about any type of material to make it either repel or attract water and oil. For an industry that deals with a lot of both, the technology has many potential use cases. The complete paper presents the results of evaluation of laboratory and demonstration trials of HDPE liner to mitigate premature failures and prolong the run life of production tubing. Corrosion inhibitors are often the first line of defense against internal corrosion, and effective mitigation relies on proactive monitoring and management of these inhibitors to allow for regular feedback and dose adjustment. This paper describes a novel method of chemical dosage based on time-resolved fluorescence (TRF) that allows a simple, accurate, and efficient quantification of chemicals below parts-per-million ranges, even for double (scale/scale, scale/corrosion) quantification.
Hydrocarbon typing and prediction of fluid properties by nuclear magnetic resonance (NMR) logs is predicated on reliable laboratory correlations between NMR measurements (i.e., relaxation times and diffusion) and fluid properties, for example: Early studies were limited to investigations at ambient conditions;  however, using the standard correlations derived from these studies may result in seriously underestimating viscosity. More-recent studies have expanded these correlations to oils and mud filtrates at reservoir conditions. The NMR T2-porosity relationship in which T2 is a function of pore size (i.e., S/V ratio, see Eq.1) holds for water-saturated rocks. Despite the variability in the NMR properties of fluids, the locations of signals from different types of fluids in the T2 distribution can often be predicted or, if measured data are available, identified (Figure 1). The position and spread of the oil component in the T2 distribution depends on oil viscosity and formation wettability.
This article aim to present the technology for detection and quantification of fugitive gas emissions in deep offshore activities of TOTAL E&P Angola (hereafter mentioned as "Company").
Company has been operating in Angola for more than 60 years, totally committed to the environmental sustainability through full compliance to the local regulation, Company standards, and best oilfield environmental practices.
Fugitive emissions represent a general set of emission from industrial sources that cannot be connected through controlled means to a definitive emission point. These normally and relatively small and hard-to- detect emissions from valve packing, pump seal, compressor seals and piping connections occur as part of normal industrial operations. They are characterized by a diffused release of VOC (Volatile Organic Compounds: methane, ethane, methanol, etc) or other pollutants into the atmosphere.
Methane’s global warming potential is higher than carbon dioxide. Methane emissions in Company’s operated scope stood at 2.3 Mt CO2-eq in 2015 and nearly half or 1.1 Mt CO2-eq were specifically related to gas production. In all, they account for less than 0.5% of Company’s marketed operated production; therefore improving methane measurement and mitigating these emissions are part of climate change strategy of the Company.
Reducing oil and gas methane emissions is an essential, low-cost strategy for slowing the accelerated pace of today’s Global Warming. It is a major opportunity for climate progress that cannot be missed. This is why all efforts were centered to join the Climate and Clean air Coalition (CCAC) Oil & Gas Methane Partnership, important step to understand the scope of the company methane emissions. The CCAC Partnership provides companies with a credible mechanism to systematically address their methane emissions and demonstrate this systematic approach to stakeholders.
Materials are made of distinct constituents. Connectivity of material constituents govern several physical properties, such as transport, mechanical, and electromagnetic properties. High-resolution microscopy imaging of a material is the best way to capture the microstructural aspects describing the distribution, topology and morphology of various material constituents. In this study, we develop two novel connectivity-quantification metrics for robust quantification of connectivity of material constituents captured in high-resolution images. Two-point connectivity function and fast-marching-based travel-time histograms are developed to quantify connectivity of each type of material constituent captured in the images. Two-point connectivity function for a specific constituent type is computed as a function of separation distance between two randomly selected pixels belonging to a specific constituent type. On the other hand, a fast-marching-based travel-time histogram for a specific constituent type is generated by using the fast marching method to compute the time taken by monotonically advancing interfaces starting from several randomly selected pixels to travel to each pixel belonging to the specific constituent type. The travel-time histogram indicates the tortuosity of connected paths, whereas the connectivity function indicates the length-scale of dominant globular connectivity. As a scalar measure of connectivity, the distributions corresponding to the two metrics are transformed to an average connected distance derived from the connectivity function and average travel time derived from fast-marching calculations. The performances of these two connectivity-quantification metrics are tested on 1500 images belonging to three categories of connectivity, namely poor, intermediate, and good connectivity, with 500 images for each category. Then, the metrics are evaluated on the organic constituent captured in the scanning electron microscopy (SEM) images of rock samples from various shale formations. Material constituents exhibiting high connectivity results in large values of average travel time and average connected distance. The average connected distances for the three categories of connectivity are 140.1, 14.6, and 5.6 pixels, respectively. The average travel times for the three categories of connectivity are 34.1, 5.2, and 1.9 seconds. The quantifications of connectivity using the two metrics show good agreement with each other and with visual inspection. For the two real SEM images exhibiting good connectivity and poor connectivity of the organic constituent, the average connected distances are 125.9 and 25.5 pixels, respectively, and the average travel times are 24.6 and 6.2 seconds, respectively, which confirms the robust performance of the metrics.