In July 2006 the first stone was laid for constructing the largest Gas To Liquids (GTL) plant in the world, the Pearl GTL Complex in Ras Laffan, Qatar. After completing Shell's first GTL plant in Bintulu, Malaysia in 1993 with a debottlenecked capacity of 14 kbbl/d, the Pearl GTL plant is a major leap forward in size, innovation and integration. Pearl GTL is designed to produce 140 kbbl/d of finished GTL products and some 120 kbbl/d of natural gas liquids, including field condensate and ethane. Raw feed gas is routed from 2 identical offshore Platforms in the Qatar North Field via 2 parallel 30?? subsea pipelines to the onshore GTL manufacturing complex.
The reliable, efficient and well integrated Feed Gas Preparation plant is a key enabler to the overall success of the Pearl GTL complex. Feed Gas Preparation includes offshore platforms, inlet receiving facilities, integrated gas treating units and NGL extraction/fractionation unit.
The design of the Feed Gas Preparation complex is based on Shell's years of experience in designing, building, licensing and operating many Gas Processing & LNG plants. Due to the highly integrated design, implementation of significant technology innovations was executed only after thorough analysis and issuing of formal development releases.
The Pearl GTL plant came into operation on 23rd March 2011. Stable production of sweet Natural Gas, Sulphur, Propane, Butane and Condensate at 40% design capacity was achieved within 10 days. The plant is meeting its design capacity and product quality, and complies with stringent environmental specifications. The innovative design approach used has resulted in a stable, reliable operation and has contributed to the sustainable development of the project.
This paper describes in detail the configuration of the Feed Gas Preparation plant in Pearl GTL and highlights the key features in the design, construction, commissioning and start-up experiences.
Applying digital technology in the upstream introduces new equipment and applications that have the potential to transform asset management and optimization processes. Technology selection, delivery, sustainment and most importantly, business integration are key factors in making effective digital technology investments and realizing their full value. Leveraging the significant experience and synergies in ExxonMobil's* Information Technology organization and downstream has been recognized as an opportunity in the upstream to facilitate quicker technology deployment and effective, efficient sustainment. Aligning with business priorities, decisions on digital technology enablers are linked with relevant upstream best practices to facilitate integration with asset management work processes.
This paper will focus on ExxonMobil's approach with leveraging our corporate infrastructure and experience to deliver targeted upstream capabilities related to facilities, process and equipment surveillance and optimization, as well as how it enables further technology applications in advanced analytics and advanced process control.
In order to make effective decisions for oil field management, well and reservoir surveillance data needs to be utilized to better understand how the subsurface and surface systems in a field interact. This can be done at the reservoir, well and surface facility level, but is most effective when considering the entire production or injection system. IPM (Integrated Production Modeling) is now being used more often and, has demonstrated its usefulness in many oil and gas field applications.
The use of integrated production modeling methodologies for improving production, identifying and eliminating bottlenecks and improving production allocation for wells from multiple reservoirs from both onshore and offshore oil fields are presented. Methods for coupling the surface and subsurface are reviewed and its usefulness for identifying bottlenecks at both the well and surface facility level are demonstrated. Field examples are presented where issues were identified and overcome by operational means and, found to increase production. Prioritization of wells and production intervals can also be incorporated to improve production/system uptime and field life.
The use of artificial lift for oil wells and additional compression for gas wells can be effectively modeled by reasonably calibrated IPM models. Without proper calibration, these models can yield results that lead to inadequate decisions that have a significant impact on project economics. The use of IPM models as a tool to better allocate field production data has proved to be very reliable and has resulted in better field management. This approach requires both reservoir and surface facility information gathered on a regular basis in order to be reliable and accurate. Reservoir, well and surface models require occasional calibration or updates of inflow type curves. Application of these methods are discussed and presented for some field cases for oil reservoirs some under waterflood and others with active water drive.
Waterflooding in different reservoirs for pressure maintenance and recovering more oil is a well established practice in oil industry. Many research studies have shown that the success of any waterflooding process is mainly dependent on both physicochemical (fluid-rock) and geochemical (fluid-fluid) interactions. These interactions have been extensively investigated during seawater injection into carbonate formations. However, the rock/seawater chemical interactions are completely different in sandstone than in carbonate formations, due to different rock mineralogy. Therefore, the main objective of this paper is to investigate both the potential physicochemical and geochemical formation damage mechanisms that might occur during injection of seawater into a central Arabia sandstone formation.
Scaling potential due to seawater-produced brine chemical interactions was investigated at reservoir average temperature of 186°F, based on Pitzer theory of electrolytes. In addition to the prediction data, laboratory compatibility tests were conducted to investigate the scaling potential in different seawater/produced brine mixtures at reservoir temperature. Since this sandstone formation contained different clays such as illite and smectite, the clay swelling and fines migration tendency was explored using coreflood setup and zeta potential technique.
The saturation index (SI) of different scales such as calcium carbonate and calcium sulfate was found to be mainly dependent on seawater/produced brine mixing ratio. Additionally, it was found that scaling did not occur in supersaturated mixtures of seawater, aquifer water and produced brine, which indicated that there is a critical SI for the scaling onset. Zeta potential for different formation rocks was determined for sweater, aquifer and produced brine. It was nearly zero when using only seawater. One of the major findings of this study is that the presence of sulfate ions caused clay particles to migrate even in high TDS seawater of nearly 55,000 ppm.
DOST - Directorate Operations Strategy Team was formed in year 2007 to develop Operations Directorate long term vision. Inspired by Qatar National Vision - QNV2030 and fuelled by Qatar Petroleum "Commitment to Excellence??, DOST has made significant strides in developing a shared Operations Directorate Vision - ODVision2020 under an innovative and unique LEADERSHIP concept.
This paper highlights the DOST journey in establishing the Operations Directorates Mission, Vision and Values as well as developing broad Objectives, Strategies and Roadmap based on SWOT analysis, cultural surveys and interviews carried out across the ranks. The paper will also present the challenges anticipated in realization of ODVision2020 and how organizational people, processes and systems would be transformed and Operations Directorate emerges as a leader in the industry in all aspects of its business.
Production optimization for offshore oil and gas production is in general a challenging task, even at fields operated "Smart" with continues 24/7 optimization, due to the intrinsic complexity of the domain. In this paper, we present an intelligent multi-objective-control-software approach for the next generation of Smart Fields.
At the DONG Energy E&P operated Siri area, which we use as a test case, several optimization studies have shown that an increase in production throughput is possible, if the comfort zone, i.e. the band between the actual and the maximally possible production level, is reduced dynamically. Maximal production will be obtained when the comfort zone meets the minimally required margin that ensures a safe and stable production in all constraining systems of the installation. This can be hard for the control operators to achieve with the present complex dynamic production configurations.
In our approach, we focus on intelligent online control to minimize the comfort zone by pushing the production towards the process constraints which always have to be satisfied. The new intelligent online multi-objective control system is implemented as a stratified multi-agent system allowing control concerns to be dynamically introduced, changed or removed without the need to modify or inspect the existing control system. The stratified approach supports multi-objective optimization in all layers, i.e. in contexts of strategy, tactics and operation. Optimization conflicts are dynamically identified and propagated to a higher layer. The "irony of automation" predicts that more advanced automation systems require more tacit knowledge; an essential property of any advanced control system is, therefore, the capability to identify and explain optimization conflicts well in advance.
In this paper, we demonstrate that it is possible to continuously minimize the comfort zone and thereby gain higher production throughput by using intelligent online multi-objective control, even at fields with complex configurations.
The exploitation of an oil field in deep water presents many challenges related to high water production, high cost of frequent well interventions and many uncertainties. One of the technologies available, which can overcome these problems, is the use of intelligent wells (IW), which are capable of reducing water production rates, to avoid intervention in the well and to add operational flexibility to mitigate risk. However, the real benefits of this technology are not always clear due to the lack of a consolidated methodology in the literature. Moreover, there are also two main ways of controlling valves, i.e., reactive and proactive controls, making it necessary to better understand them to extract advantages and disadvantages from each one. Therefore, the objective of this work is the comparison between conventional wells (CW) and IW, using reactive and proactive controls. The first control is simpler to be used and quicker to be optimized but the second type can be more profitable, although more difficult to optimize. The optimization method used to solve the problem is an evolutionary algorithm, which is coupled to a commercial simulator to search for the maximum net present value (NPV), based on the ‘shut in' water cut to determine the optimum time in which to close each valve and the well, in all types of controls. This work employs a model using an inverted five-spot configuration of wells to represent a part of a reservoir under a waterflooding recovery method. Some case studies are used considering different reservoir heterogeneities, type of oil and under economic uncertainty. The conclusion shows that IWs are able to increase production time, oil recovery and the NPV; as a consequence total water production is also increased. The results also show higher benefits in cases with more heterogeneity and light oil. Moreover, IWs using proactive control is better than IWs with reactive control and using either of them is better than CWs.
This study has been undertaken in three oil fields (A-Libya, B-Libya, and C-Libya) in sirte basin located in Libya. Nubian sandstone Formation is the main reservoir in the studied oil fields. Laboratory measurements methods were applied on the core
samples that were selected from three different fields of Nubian Sandstone. Some of these measurements were conducted in Libyan Petroleum Institute (LPI Tripoli-Libya) laboratories in order to determine the resistivity parameters of the central graben reservoir cores and to investigate the effect of rock hetrogeneity and wettability on the resistivity parameters of Nubian sandstone reservoir rocks. The pore size distribution was estimated from generated capillary pressure curves. The samples
belonged to Nubian sandstone, Sirt basin were selected to perform formation resistivity factor measurements.
The Pore size distribution and type of pores were calculated from mercury injection capillary pressure data. The results indicated that changes had been observed in formation resistivity factor and cementation exponent when overburden pressure
was applied (slightly increases in cementation exponent with increasing O.B.P).Wettability played an important role in determining the fluid movement, distribution and electrical conduction during desaturation processes. Resistivity index effect has been observed after wettability measurement showing oil-wet tendency.
From the results obtained, a good relation between resistivity and type of pores (macro and micro pore system) was observed.
When oil begins to penetrate micro-pore systems during the measurements, a significant change in slope of the resistivity index relationship occurs.
Most of the existing correlations for estimating gas viscosity were developed in mid 60's and 70's of the last century. Limited number of data was used to develop them and their accuracies are questionable. Predicting accurate gas viscosity is extremely important in the oil and gas industry as it has a major impact on reservoir recovery, fluid flow, deliverability, and well storage.
In this study, a new correlation has been introduced. This correlation is simpler, features higher accuracy, and uses fewer coefficients compared with the existing correlations. Its application covers a wider range of gas specific gravity without jeopardizing the accuracy of the correlation. Another model was built using Artificial Neural Networks, ANN in order to compare its results with those obtained from the new correlation.
The existing correlations were studied and analyzed using the same, large set of measured data used for this study. Most of these correlations suffered from high errors and thus were optimized using the linear and non-linear regressions. New set of coefficients for these correlations are recalculated for which the accuracy has significantly improved. In spite of such an improvement, the new correlation and new ANN model outperform the existing correlations.
Many correlations have been proposed for gas viscosity estimation. These methods include Carr, et al., Jossi, et al, which was adapted by Lohernz, Bray and Clark, Dien and Stiel, Lee, et al. and Sutton. Carr, et al. 1 correlation has been very popular for estimating gas viscosity. Lee, et al. correlation has been used widely since mid 80s as it has proven to be more accurate. Each of these correlations will be discussed briefly below. The corresponding viscosity correlations are shown in Appendix A.
1. Carr, et al.1- Dempsey2-Standing3 method
Until recently, this correlation was considered to be the main correlation for estimating gas viscosity in petroleum industry. Carr, et al.1 used their experimental data (and Comings, Mayland, and Egly data) to create a graphical correlation, as function of reduced pressures and temperatures. Results were used to construct cross plots, which were a function of pseudo-reduced pressure, pseudo-reduced temperature and viscosity ratio. The main advantage of this correlation is its simplicity as well as the corrections it has for the existence of non-hydrocarbon gases such as CO2, N2 and H2S.
Carr, et al.1 correlation is reported to have an average of 0.38 absolute error. This correlation is recommended to be used for gases with specific gravity between 0.55 and 1.22 and a temperature range between 100 and 300 ºF.
Dempsey2 (1965) expressed the viscosity ratio for Carr, et al.1 chart µg/ µ1 mathmatical formula as shown in Appendix A.
Gasco operates two NGL plants located in Alexandria; Amerya LPG plant and Western Desert Gas Complex (WDGC). Recently, Gasco has started up a new project that integrates the two plants to maximize Ethane and Propane productivity.
The project design is based on adding new process facilities in Amerya plant to start producing C2+ that directed to WDGC, while a new train is added in WDGC to increase the feed gas capacity and maximize C2+ recovery by applying the Gas
Subcooled Process (GSP) as Ethan mode of operation scheme.
This paper presents a study to increase the productivity of the two plants by using simulation software to help the decision making for what the optimum conditions should be applied in different modes of operation to increase the production.