This course is designed for petro physics and reservoir engineers who are involved in formation sampling and testing. To learn about reservoir characterisation using formation testers, to be able to interpret pressure and fluid properties, and to design a successful sampling and testing operation. This class is designed for geophysicists, reservoir engineers and any engineers involved or interested in wireline formation sampling and testing including petro physical engineers, production engineers and testing engineers. There are no special requirements for this course. It is recommended for participants to bring their own examples to contribute to course discussions.
van den Berg, Frans G. (Shell) | Weiss, Cristopher (Wipro Technologies) | van Dijk, Jaap (Petroleum Development Oman) | Tulalian, Robert (Shell) | Amos, Martins (Shell) | Alharthy, Said (Shell) | Awobadejo, Mayowa (Shell)
Collaborative Work Environments (CWEs) were implemented in the majority of Shell's assets, now covering over 55% of the production. Collaborative working has evolved beyond production and surveillance processes, includes new mobility and visualization technologies and supports the cost reduction drive.
The Parque das Conchas field in Campos basin offshore Brasil is a phased ultra-deepwater heavy oil development tied to the Espírito Santos floating, production, storage and offload (FPSO) vessel, moored at a water depth of 1,780-meters. The subsea system utilizes a subsea boosting and separation technology, enhanced recovery through water and gas injection, subsea sampling, enhanced vertical deepwater trees (EVDT), steel lazy wave catenary risers, and high voltage multiplexed electro-hydraulic steel tube umbilicals. During its nine year development since sanctioning, the professionals, installation contractors, commercial and contractual conditions have changed and played their role on the successful deployment of the subsea systems architecture. The project's successful track history to date is largely attributed to the development and consistent application of standardized subsea hardware throughout its three distinct and independently developed phases.
This paper addresses the standardized features applied to the 10,000-psi (10K) rated subsea system components at BC-10: EVDT systems and tooling, including the upper completion tools which allowed deployment through either a subsea or surface blow-out preventer; completion and intervention riser systems on the lower riser package; retrievable flow modules and flow meters; production and injection jumper kits; manifolds; subsea boosting and separation; subsea control modules; umbilicals and subsea distribution hardware. This paper also addresses how these features fit within the operator's global subsea hardware standardization program, and provides examples on how continuous improvement, lessons learned and innovations are implemented in that program.
This paper provides an overview of the unique challenges faced by the oil and gas export pipelines during the development and execution phases of the Lucius project. The oil pipeline will focus on the repurposing of 47 miles of the Phoenix gas pipeline for oil service which reduces infrastructure and environmental footprint in the Gulf of Mexico. The gas pipeline will focus on the re-engineering of the pipeline end terminations (PLETs) and installation procedures after the engineering and fabrication phases of the project were complete due to a change in installation vessel so that Lucius first production was not impeded. The oil export pipeline, with a nominal capacity of 115 KBPD, is an 18-inch, 147 mile pipeline consisting of 3 segments: (1) 74 miles of 18-inch new build pipeline from the Lucius spar to the existing Phoenix pipeline, (2) test and reuse of an existing 47 mile section of Phoenix gas pipeline converted to oil service, and (3) 26 miles of 18-inch new build pipeline to the existing platform South Marsh Island 205 (SMI-205). First oil was delivered in 1Q2015. The gas export pipeline, with a max capacity of 400 MMCFD, is a new build 20-inch, 209 mile pipeline anchored by the Lucius and Hadrian South developments. The pipeline starts in Keathley Canyon 831 and terminates into a new build transportation platform located in South Timbalier 283 (ST-283). First gas was delivered in 1Q2015.
In general, water-treatment systems in the North Sea differ from those in the deepwater Gulf of Mexico (GOM). The two most apparent differences are the extensive use of hydrocyclones in the North Sea, and the use of large, multistage horizontal flotation units in the deepwater GOM. Deepwater-GOM platforms use hydrocyclones, but not nearly to the extent that they are used in typical North Sea platforms. Typically in the North Sea, if flotation is used at all, it is a vertical compact unit. The objective of this paper is to provide an understanding of the reasons for these differences. In this paper, field data and modeling results are presented to explain these differences. The models accurately correlate the measured drop size and oil-in-water concentration observed in the two regions. In addition, the modeling tools are used to answer hypothetical “what if” questions. This allows isolation of individual variables such as fluid temperature, shear, separator residence time, and fluid density. Thus, the modeling provides a detailed understanding of the relative importance of these variables. It also provides a direct comparison of the performance of North Sea vs. GOM process configurations. While the qualitative conclusions are well-known (i.e., deepwater separation systems are designed to minimize weight and space), the detailed understanding provided here provides insight into the design of water-treatment systems in general. It also emphasizes, in a quantitative way, the importance of carrying out effective water treatment early in the process and the necessary use of large end-of-pipe equipment when this is not possible.
This paper presents the results of a joint industry project (JIP) that developed an improved wellbore stability (WBS) tool for wells in three basin areas in the Gulf of Mexico (GoM) and North Sea. The analysis was performed in 106 wells to identify suitable rock failure criteria and rock strength correlation combinations for determining WB Sunder complex geological conditions. A “well quality index” (WQI) parameter was defined for calibrating the shear failure gradient (SFG), taking into account the over-gauge observed and the difference between the SFG and mud weight. In addition, a comparison is made for SFG calculations between an Abaqus finite element method (FEM) and Drillworks® (DWs) Predict Geostress modeling. The analysis showed that the SFGs obtained by these methods are practically identical. However, a three-dimensional (3D) numerical model is more appropriate for WBS analysis in a sub-salt environment because the stress field is strongly perturbed by the presence of salt.
The JIP DEA-161 was performed with the purpose of developing an improvedWBS prognosis tool and evaluating applicable rock failure criteria and rock strength correlations for wells in different basins, as well as determining the minimum limits on an acceptable dataset. Data from 199 wells were collected, and a WBS analysis was performed for 106 wells. The data were acquired in image format from the public domain and digitized as part of the project. The analysis was conducted using limited data. However, it was possible to performa wide variety of approaches and tests. Not all of these were successful, and the lessons learned from the unsuccessful attempts were invaluable in developing an overall successful set of guidelines, methods, and procedures that are incorporated into the results of the study.
2. Project Overview
Five major phases were performed during the project:
i) research to determine current industry practices;
ii) data gathering, quality control, and validation;
iii) determination of in-situ stress and rock strength;
iv) WBS analysis; and
v) documentation and communication of findings.
Figure 1 shows the location of seven fields in the northern GoM shelf and seven in the deepwater GoM basin. A total of 157 wells were analyzed in the two basins, and 76 had sufficient data to perform a full WBS analysis.
Projects in the global deepwater environment are increasingly complex, costly and often face significant schedule pressures to reach both a "commitment to develop" decision and "first oil/gas milestone". Typical industry deepwater project costs ranges from USD$1 billion for a small scale subsea tieback to upward of USD$10 billion for a custom design standalone hub class development. Therefore ensuring that the appraisal campaign addresses the data acquisition required to reduce both key subsurface, and key development uncertainties as well as enable a robust development decision is critical. The appraisal phase of the project (post discovery) is the most important early phase in the development cycle which sets the stage for the remainder of the concept selection, detailed design, execution and production phases of the development. This paper explores and discusses, with the use of relevant examples, the key aspects of appraisal planning and execution specifically related to reducing uncertainties and determining the ultimate development scope for deepwater oil and gas development projects. The paper does not attempt to expand on building understanding or managing the nontechnical aspects of early phase deepwater project management which can have an equally significant role in shaping the ultimate deepwater development project.
Many production and injection wells completed with intelligent (smart) systems are operating around the world. These wells are more economical and efficient than conventional wells. This paper presents functional networks as a novel modeling method to forecast bottomhole flowing pressures and temperatures in vertical multiphase production wells using 700 data points from multiple fields. This new approach helps to overcome the most common limitations of existing predictive techniques such as empirical correlations, multiple regressions and artificial neural networks.The functional network models were trained and tested using 70% and 30% of the available datasets, respectively. Trainings and testing were conducted with associativity functional networks models with families of linearly independent learning functions such as polynomial, logarithm, Fourier and exponential basis. By using backward-forward search based on minimum description length criterion or a least-squares optimization technique, the best functional networks models were selected and tested. The models results are accurate, reliable and can be used for forecasting. For the times series analyses, the models perform excellently with R2 > 0.99 for the hourly and six-hour data while R2 > 0.96 for the data obtained every three minutes. In addition, trend analysis shows that the predictive models are physically correct and justified by the field data. Finally, the current models outperform the artificial neural network models in both time series and trend analyses.
This is the first reported study where a functional network is used to simultaneously forecast bottomhole flowing pressures and temperatures with such a high accuracy. This work also holds a significant contribution to authenticating the operational state and diagnosing future malfunction of downhole pressure and temperature sensors in intelligent well system operations in petroleum and geothermal industry.
Predicting flow rates of wells located in these frontier environments accurately is of great importance to enable asset performance monitoring, field surveillance, production accounting, production optimization, reservoir management decision, volumetric input to reservoir simulators and reservoir estimate tracking, though out the field life cycle. Although several studies have focused on real-time well rate estimation using physical multiphase flow meters, theoretical approach (mass, momentum and energy coupled with real-time field data) and artificial neural network models, little attention has been given to continuous flow rate surveillance based on hybrid intelligent systems. Hybrid intelligent systems combine intelligent techniques synergistic architecture in order to provide solution for complex problems. These systems utilize at least two of the three techniques: fuzzy logic, genetic algorithm and artificial neural networks. The goal of their combination is to amplify their strengths and compliment their weaknesses. This paper presents a novel approach of using hybrid intelligent modeling technique, available time series field data and well configuration information to develop a virtual flow meter for production wells. The simulation results from the hybrid intelligent based virtual flow rate meter are compared to those obtained from real life field data. The validated model is used to predict future performance of existing wells. The effects of various parameters are performed to determine their impacts on the predictive accuracy of the new approach.
This paper explores and discusses the interplay between field development and lifecycle reservoir management and the selection and operation of dry or wet tree host systems for the development and production of deepwater oil and gas fields. Drawing on insights from recent Shell deepwater projects, the selection criteria related to development and reservoir management are highlighted and discussed to portrait the advantages and limitation of the two different host concepts. The paper does not attempt to expand on the engineering and construction elements of either option. Introduction Globally production from deepwater fields contributes over 5mln barrels of oil per day of total production which is expected to significantly grow in the coming years. By the end of decade production from recent discoveries, in-appraisal projects and those projects currently in the construction phase are expected to grow global deepwater production to 8 - 10mln barrels of oil per day.