Haider, Bader Y.A. (Kuwait Oil Company) | Rachapudi, Rama Rao Venkata Subba (Kuwait Oil Company) | Al-Yahya, Mohammad (Kuwait Oil Company) | Al-Mutairi, Talal (Kuwait Oil Company) | Al Deyain, Khaled Waleed (Kuwait Oil Company)
Production from Artificially lifted (ESP) well depends on the performance of ESP and reservoir inflow. Realtime monitoring of ESP performance and reservoir productivity is essential for production optimization and this in turn will help in improving the ESP run life. Realtime Workflow was developed to track the ESP performance and well productivity using Realtime ESP sensor data. This workflow was automated by using real time data server and results were made available through Desk top application.
Realtime ESP performance information was used in regular well reviews to identify the problems with ESP performance, to investigate the opportunity for increasing the production. Further ESP real time data combined with well model analysis was used in addressing well problems.
This paper describes about the workflow design, automation and real field case implementation of optimization decisions. Ultimately, this workflow helped in extending the ESP run life and created a well performance monitoring system that eliminated the manual maintenance of the data .In Future, this workflow will be part of full field Digital oil field implementation.
The global economy continues its journey of evolution and progression driven by industrialism as its primary force. With such a fast pace of development and recovery from several recessions over a number of years, dependency on energy sources became inevitable to satisfy the rising demand. This paper represents a proposed global energy price model that has the flexibility of modeling the energy price, using data from specific regions of the world, as well as the global energy pricing equation. The ANM (Alternate Novel Model) is presented here.
The model focuses mainly on oil price modeling, since oil accounts for more than 84% of the current world energy supply. The model duration is 50 years; starting from 1980 to 2030, model matching period from 1980 to 2011, and the prediction period is from 2012to 2030.
The modeling approach used in ANM adopts weighted averaging of individual factors and it relies on line regression technique. Therefore, future trends are being predicted based on the cyclic nature of the market and historical data "the future is reflection of the past??. ANM can then preduct the future oil prices, depending on the factors and variables that have been placed in the process for the output results.
The paper aims to propose a reliable model that accounts for most governing factors in the global energy pricing equation. All steps followed and assumptions made will be discussed in detailto clarify the working mechanism for this model and pave the road for any future modifications.
Alusta, Gamal Abdalla (Heriot-Watt University) | Mackay, Eric James (Heriot-Watt University) | Collins, Ian Ralph (BP Exploration) | Fennema, Julian (Heriot-Watt University) | Armih, Khari (Heriot-Watt University)
This study has focused on the development of a method to test the economic viability of Enhanced Oil Recovery (EOR) versus infill well drilling where the challenge is to compare polymer flooding scenarios with infill well drilling scenarios, not just based on incremental recovery, but on Net Present Value as well.
In a previous publication (Alusta et al., 2011, SPE143300) the method was developed to address polymer flooding, but it can be modified to suit any other EOR methods. The method has been applied to a synthetic scenario with constant economic parameters, which has demonstrated the impact that oil price can have on the decision making process.
The method was then applied and tested (Alusta et al., 2012, SPE150454) with varied operational and economic parameters to investigate the impact in delaying the start of polymer flooding to identify whether it is better to start polymer flooding earlier or later in the life of the project. Consideration was also given to the optimum polymer concentration, and the impact that factors such as oil price and polymer cost have on this decision. Due to the large number of combined reservoir engineering and economic scenarios, Monte Carlo Simulation and advanced analysis of large data sets and the resulting probability distributions had to be developed.
In this paper the methodology is applied to an offshore field where the choice has already been made to drill infill wells, but where we test the robustness of the method against a conventional decision making process for which there is historical data. We do this by performing calculations that compare the infill well scenario chosen with a range of polymer flooding scenarios that could have been selected instead, to identify whether or not the choice to drill infill wells was indeed the optimum choice from an economic perspective.
We conclude from all the reservoir simulations and subsequent economic calculations that the decision to drill infill wells was indeed the optimum choice from an economic perspective.
The North Kuwait Jurassic Gas (NKJG) reservoirs are currently under development by KOC with assistance from Shell under an Enhanced Technical Services Agreement (ETSA). The fractured carbonate reservoirs contain gas condensate and volatile oil at pressures up to 11,500 psi with 2.5% H2S and 1.5% CO2. This paper describes the planning and implementation of a Well Integrity Management System (WIMS) that allows the safe management of the wells that are being drilled in this hazardous environment.
The wells are designed and constructed in accordance with KOC standards and on transfer of ownership from Deep Drilling Group to Production Services Group have their integrity managed under WIMS. The system is a structured process, relating the frequency and extent of routine monitoring and testing to the particular risks associated with the wells. Compliance with WIMS requirements are routinely reported so that all are aware of the current state of well integrity. WIMS is initially managed through simple spreadsheets and during 2012 is being integrated into KOC's Digital Field infrastructure.
Initially, WIMS has been applied to the range of wells ‘owned' by Production Services Group and tests currently carried out by Well Surveillance Group under PSG's direction. In order to realise the full assurance of safe operation the scope of WIMS application is being extended to the full well population, including suspended wells, and the full range of tests required.
Implementation of WIMS will allow KOC (NKJG) to be able to state that ‘our wells are safe and we know it'.
Wu, JinYong (Schlumberger) | Banerjee, Raj (Schlumberger) | Bolanos, Nelson (Schlumberger) | Alvi, Amanullah (Schlumberger) | Tilke, Peter Gerhard (Schlumberger - Doll Research) | Jilani, Syed Zeeshan (Schlumberger Oilfield UK Plc) | Bogush, Alexander (Schlumberger)
Assessing the waterflood, monitoring the fluids front, and enhancing sweep with the uncertainty of multiple geological realisations, data quality, and measurement presents an ongoing challenge. Defining sweet spots and optimal candidate well locations in a well-developed large field presents an additional challenge for reservoir management. A case study is presented that highlights the approach to this cycle of time-lapse monitoring, acquisition, analysis and planning in delivery of an optimal field development strategy using multi-constrained optimisation combined with fast semi-analytical and numerical simulators.
The multi-constrained optimiser is used in conjunction with different semi-analytical and simulation tools (streamlines, traditional simulators, and new high-powered simulation tools able to manage huge, multi-million-cell-field models) and rapidly predicts optimal well placement locations with inclusion of anti-collision in the presence of the reservoir uncertainties. The case study evaluates proposed field development strategies using the automated multivariable optimisation of well locations, trajectories, completion locations, and flow rates in the presence of existing wells and production history, geological parameters and reservoir engineering constraints, subsurface uncertainty, capex and opex costs, risk tolerance, and drilling sequence.
This optimisation is fast and allows for quick evaluation of multiple strategies to decipher an optimal development plan. Optimisers are a key technology facilitating simulation workflows, since there is no ‘one-approach-fits-all' when optimising oilfield development. Driven by different objective functions (net present value (NPV), return on investment (ROI), or production totals) the case study highlights the challenges, the best practices, and the advantages of an integrated approach in developing an optimal development plan for a brownfield.
Determining the optimum location of wells during waterflooding contributes significantly to efficient reservoir management. Often, Voidage Replacement Ratio (VRR) and Net Present Value (NPV) are used as indicators of performance of waterflood projects. In addition, VRR is used by regulatory and environmental agencies as a means of monitoring the impact of field development activities on the environment while NPV is used by investors as a measure of profitability of oil and gas projects. Over the years, well placement optimization has been done mainly to increase the NPV. However, regulatory measures call for operators to maintain a VRR of one (or close to one) during waterflooding.
A multiobjective approach incorporating NPV and VRR is proposed for solving the well placement optimization problem. We present the use of both NPV and VRR as objective functions in the determination of optimal location of wells. The combination of these two in a multiobjective optimization framework proves to be useful in identifying the trade-offs between the quest for high profitability of investment in oil and gas projects and the desire to satisfy regulatory and environmental requirements. We conducted the search for optimum well locations in three phases. In the first phase, only the NPV was used as the objective function. The second phase has the VRR as the sole objective function. In the third phase, the objective function was a weighted sum of the NPV and the VRR. A set of four weights were used in the third phase to describe the relative importance of the NPV and the VRR and a comparison of how these weights affect the optimized NPV and VRR values is provided.
We applied the method to determine the optimum placement of wells using two sample reservoirs: one with a distributed permeability field and the other, a channel reservoir with four facies. Two evolutionary-type algorithms: the covariance matrix adaptation evolutionary strategy (CMA-ES) and differential evolution (DE), were used to solve the optimization problem. Significantly, the method illustrates the trade-off between maximizing the NPV and optimizing the VRR. It calls the attention of both investors and regulatory agencies to the need to consider the financial aspect (NPV) and the environmental aspect (VRR) of waterflooding during secondary oil recovery projects. The multiobjective optimization approach meets the economic needs of investors and the regulatory requirements of government and environmental agencies. This approach gives a realistic NPV estimation for companies operating in jurisdiction with requirement for meeting a VRR of one.
In order to develop the design requirement with current regulatory and contemporary HSE practices, for a typical sour oil/gas production facility, a hypothetical case of about 3 mol % v/v H2S in gas and 300 ppm w/w H2S in oil, of multiphase feed stream, has been studied through the dispersion modeling for the conceptual stage. The findings indicated credible downwind lethal / semi lethal threat distance up to 300 meters. The conclusions of the H2S toxic risk assessment combined with the inherent safe design guidelines have yielded an entirely new set of requirement for the risk reduction. To start with it was realized that safe distance control room should be constructed and facilities should be designed for the remote operation, utilizing the new trends of foundation field bus, electronic marshaling and SIL-3 fiber optic sensors. The facility should be access controlled with mandatory PPE requirement of personal H2S monitors and personal quick donning (5 sec) escape SCABA (15 minutes capacity). The centrifugal compressors should be new generation design of enclosed and hermetically sealed type, levitated with magnetic bearing, without dry gas seals and oil lubrication. The vessels should be ASME Section VIII "lethal service?? design and plant piping should be as per fluid category "M?? of ASME B31.3 chapter VIII. Furthermore, stress relieving for thicknesses as low as 10 mm, rather than ASME B31.3 code specified >19 mm would be required. Small valves <4?? sizes should be of forged steel instead of cast steel. The export oil/gas pipelines and flow lines should be designed for =< 50~60 % of SMYS. Plate instead of Shell and Tube Exchangers. Adequate margins between vessels design and operating pressures to avoid PSV chattering. The PSV's to have acoustic monitoring. The facilities should be designed free of valve pits and internal corrosion monitoring pits.
Ali, Zaki (Schlumberger) | G. Bonilla, Juan Carlos (Schlumberger) | Zolotavin, Andrey (Kuwait Oil Company) | Al-Shammari, Reem Faraj (Kuwait Oil Company) | Robert, Herric (Schlumberger) | Saleem, Hussain A. (Kuwait Oil Company) | Farid, Ahmad (Schlumberger)
As oilfields mature and new fields come into operation, real time asset management of reserves is providing ongoing challenges to Kuwait Oil Company (KOC). Fewer engineers are managing more wells under increasingly tougher environmental conditions and compliance regulations. The combination of these factors has driven the need for KOC to make a step change in its approach to operations by incorporating digital field concepts to transform the way engineers are working. The result is the Kuwait Intelligent Digital Field initiative.
To enable KwIDF, new technologies were deployed in both mature and immature assets, creating issues in terms of interoperability and integration thereby increasing the strain on the legacy IT infrastructure. In addition, there was the requirement to isolate the SCADA industrial networks from the corporate business networks while automating traffic control with the various enterprise data systems. This ‘managed' separation complicated the delivery of productivity tools to employees and posed the greatest challenge to creating a transparent, seamless KwIDF infrastructure.
The KwIDF Jurassic project was particularly challenging since it had the most limited existing infrastructure, requiring the design and deployment of an entirely new architecture scattered over significant distances and business areas. This in turn created significant hurdles in terms of integration and compatibility with the remainder of KOC's proprietary systems and technologies. Specific efforts were required to allow KOC's network infrastructure to be capable of embracing such solutions and technologies with proper security measures in place.
Developing a network infrastructure to enable real time solutions for KwIDF Jurassic involved analyzing the specific business drivers of the asset to ensure that the capital investment not only delivered results, but did so within a secure environment. This paper presents the methodology employed by KOC's Corporate IT Group (CITG) to deliver the right network infrastructure, along with lessons learned, for enabling the Kuwait Intelligent Digital Field Jurassic project.
Vibrations are caused by bit and drill string interaction with formations under certain drilling conditions. They are affected by different parameters such as weight on bit, rotary speed, mud properties, BHA and bit design as well as by the mechanical properties of the formations. During the actual drilling process the bit interacts with different formation layers whereby each of those layers usually have different mechanical properties. Vibrations are also indirectly affected by the formations since weight on bit and rotary speed are usually optimized against changing formations (drilling optimization process). Therefore it can be concluded that for optimized drilling reduction of vibrations is one of the challenges.
A fully automated laboratory scale drilling rig, the CDC miniRig, has been used to conduct experimental tests. A three component vibration sensor sub attached to drill string records drill string vibrations and an additional sensor system records the drilling parameters. Uniform concrete cubes with different mechanical properties were built. Those cubes as well as a homogeneous sandstone cube were drilled with different ranges of weight on bit and bit rotary speed. The mechanical properties of all cubes were measured prior to the experiments. During all experiments, drilling parameters and the vibration data were recorded. Based on analyses of the data in the time and the frequency domain, linear and non-linear models were built. For this purpose the interrelations of sandstone and concrete mechanical properties, drilling parameters and vibration data were modeled by neural networks. Application of sophisticated attribute selection methods showed that vibration data in both, time- and frequency domain, have a major impact in modeling the rate of penetration.
Significant advances have been made in formation testing since the introduction of wireline pumpout testers (WLPT), particularly with respect to downhole fluid compositional measurements. Optical sensors and the use of spectroscopic methods have been developed to improve sample quality and minimize sampling time in downhole environments. As a laboratory technique, spectroscopy is a ubiquitous and powerful technology that has been used worldwide for decades to measure the physical and chemical properties of many materials, including petroleum, geological, and hydrological samples. However, laboratory-grade, high-resolution spectrometers are incompatible with the hostile environments encountered downhole, at wellheads, and on pipelines. Only limited resolution techniques are available for the rugged conditions of the oil field. This paper introduces a new optical technology that can provide high-resolution, laboratory-quality analyses in harsh oilfield environments.
A new technology for optical sensing, multivariate optical computing (MOC), has been developed and is a non-spectroscopic technique. This new sensing method uses an integrated computation element (ICE) to combine the power and accuracy of high-resolution, laboratory-quality spectrometers with the ruggedness and simplicity of photometers. Many modern sensors typically merge the sensor with the electronics on an integrated computing chip to perform complex computations, resulting in an elegant yet simplistic design. Now, optical sensing using ICE features an analogue optical computation device to provide a direct, simple, and powerful mathematical computation on the optical information, completely within the optical domain. Because the entire optical range of interest is used without dispersing the light spectrum, the measurements are obtained instantly and rival laboratory-quality results.
A proof of concept MOC with ICE has been demonstrated, logging more than 7,000 hours, in nearly continuous use for 14 months. Oils with gravities ranging from 14 to 65°API have been measured in downhole environments that range from 3,000 to 20,000 psi, and from 150 to 350°F. Hydrocarbon composition measurements, including saturates, aromatics, resins, asphaltenes, methane, and ethane, have been demonstrated using the MOC configuration. As compositional calculations therein, GOR and density are validated to within 14 scf/bbl and 1%, respectively. The paper discusses the details of the new ICE-based sensor and describes its adaptations to downhole applications.