bluuebunny/crossref_metadata_2025 huggingface dataset:
Reservoir Heterogeneity in Upper Carboniferous Tight Gas Sandstones: Lessons Learned From an Analog Study
Authors: Wuestefeld P.. , Hilgers C.. , Koehrer B.. , Hoehne M.. , Steindorf P.. , Schurk K.. , Becker S.. , Bertier P..
Published: June 2014

Upper Carboniferous sandstones in NW-Germany consist of thick successions of cyclic deposits and are major tight gas reservoirs. This study presents the heterogeneity exposed in a large quarry near Osnabrück, Germany, which contains faulted and jointed fourth-order coarse- to fine-grained tight sandstone cycles separated by anthracite coal seams. First, we characterize the rocks and the lateral variation of rock properties such as porosity, diagenesis and structural inventory. Than we test whether the quarry may act as a tight gas reservoir analogue to better constrain input data for reservoir modeling. The tight sandstones are intensely compacted and cemented with quartz and generally characterized by low matrix porosities < 8 % (He-pycnometry on plugs and cuttings) and very low permeabilities (< 0.01 mD). Porosity is generally secondary intraparticle, formed by detrital and authigenic carbonate dissolution and dissolution of feldspars. Matrix porosity significantly increases up to 25% in corridors around faults. Main rock types can be distinguished by spectral gamma ray in the quarry. Quartz veins and fault mineralizations indicate fluid flow within and around faults. Normal faults show bands of clay smear and gouge, forming compartments. Fractures were analyzed in a 50 x 50 m section of the quarry wall using LIDAR laser scanning. This digitized quarry face also allows the characterization of the lithology and quantitative measurement of bedding, fracture and fault orientation data in inaccessible areas. Our high-resolution field analogue enables a better understanding of tight sand reservoir properties and reservoir quality at a sub-seismic scale, considering both the change of porosity during diagenesis and the formation of structures. Results may be used to develop data-driven exploration strategies and improved development options for similar subsurface tight gas reservoirs, especially in Northern Germany.
De-Risking Shale Plays and Assessing By-Passed Pay Potential in the Netherlands
Authors: Lutgert Jan , Greiss Rita-Michel , Hughes Chris
Published: June 2014

This paper summarizes the work performed by EBN together with NuTech Energy Alliance for the Netherlands regional study, which aims to address the underexplored pay potential covering both onshore and offshore Netherlands. The paper provides the technical proceedures involved and the usage of available public domain well data for the Netherlands regional field study in order to fulfill the study's two main objectives. First main objective being to identify and analyze the shale play opportunities in unconventional reservoirs of the Lower Jurassic Posidonia Formation and the Namurian Geverik member as well as other shale & marl sections in the area. The second objective is to identify bypassed hydrocarbon opportunities in conventional reservoir sections through onshore and offshore Netherlands.

The Netherlands regional study provides insight into reservoir potential, geological and petrophysical properties of all formations based on innovative petrophysical well data analysis that were applied to 116 representative wells across the area.
Unlocking Future Heavy Oil Development in the North Sea: A Well Testing Success in the Kraken Field
Authors: Beck D.. , Shumakov Y.. , Hetherington G.. , Ovchinnikov V..
Published: June 2014

There is an increasing hydrocarbon demand from a diminishing resource base in the North Sea. Technological advancements and government support coupled with activities in the UK Continental Shelf are enabling the development of untapped heavy oil resources. Heavy oil appraisal-well testing has always been a primary source of information for reservoir characterization, well deliverability, and evaluation of potential technologies for further application in field development.

Until recently, heavy oil well tests have been limited and deemed challenging because of the complexities associated with the nature of the heavy crude and lack of a proven well-test concept with a strong track record. Technical challenges in heavy oil well testing include designing the most appropriate ESP-DST string, maintaining fluid mobility through the surface test spread, achieving efficient separation for safe and environmentally friendly disposal, and obtaining accurate flow rate measurements. With recent technological developments, enhancements in the well test design, and appropriate equipment selection, a heavy oil well test has been engineered for success by bringing together multi-disciplinary teams and emphasizing the importance of proper job design and operational collaboration.

This paper describes the evolution of the practically proven heavy oil well-testing methodology applied in the Kraken heavy oil field with 15° API crude located in the UK Continental Shelf. A horizontal well was successfully tested in 2011 by using an innovative ESP-DST string, a dual-energy gamma ray venturi-type multiphase flow meter, a new burner system and realtime data monitoring. This paper also presents the lessons learned for obtaining high quality data to extract critical reservoir information with confidence through pressure transient analysis. This success paves the way for confident development drilling to commence on the Kraken field and also proves the heavy oil well testing concept for future applications in the North Sea heavy oil fields and elsewhere.
Modeling Multiple Hydraulic Fractures Interacting with Natural Fractures Using the Material Point Method
Authors: Aimene Yamina E. , Nairn John A.
Published: June 2014

This paper describes use of the Material Point Method (MPM) for modeling the propagation and interaction of multiple hydraulic fractures (HF) with natural fractures (NF). First the method is used on a laboratory experiment involving one HF and one NF positioned at different angles from the maximum horizontal stress. Various geomechanical simulations are performed by varying the stress anisotropy and the angle of the NF to study the remote impact of the HF on the NF. The results show the various levels of influence a HF has on a NF with a general trend being a higher influence for lower anisotropy ratio and lower NF angles. For an anisotropy equal to 1 and a NF with angle of 90 degrees, the detailed NF opening mechanism before, during and after the HF crosses a NF is studied in detail. The MPM simulations show that under the influence of the HF, the NF opening starts before the HF reaches it and even before the HF propagation. This result could help better understand the microseismic events recorded farther from the HF tip. Finally, a new workflow that integrates geophysics, geology, geomechanical simulations using MPM and completion engineering is described and validated with a real and complex Marcellus gas shale well. The workflow uses a seismically derived fault attribute map as input into the Continuous Fracture Modeling (CFM) approach to generate an Equivalent Fracture Model (EFM). The MPM geomechanical simulation of multiple hydraulic fractures propagating in the input EFM model leads to estimation of a strain field and J integral at each frac stage with a computation time not exceeding a few hours. The application of this workflow to an anomalous Marcellus gas well, shows that the estimated strain model has many striking similarities with the interpreted microseismic. The shape and the extent of the geobodies seen in the simulated strain field are very similar to those seen in the microseismic. Furthermore, the predicted J integral at each frac stage is correlated well with the density of the microseismic events at the same frac stage. The entire workflow takes only few hours thus making it suitable for any completion engineer designing his well. The new workflow brings improved and realistic geomechanics into the G&G world by providing new insights into the complex behavior of multiple hydraulic fractures propagating in a naturally fractured reservoir. This new insight will provide an additional powerful tool for an integrated approach that combines G&G, geomechanics and engineering for the imaging of sweet spots and reliable estimates of well performance thus allowing improved and economical fracing and development of shale reservoirs.
Development of an Optimized Completion Strategy in the Vaca Muerta Shale with an Anisotropic Geomechanical Model
Authors: Ejofodomi E. A. , Varela R. A. , Cavazzoli G.. , Velez E. I. , Peano J..
Published: June 2014

In the Vaca Muerta shale of the Neuquén basin, Argentina, the most prolific intervals tend to be the most difficult to hydraulically fracture because of the abnormally high fracture gradients present in some parts of the basin. Thus, it becomes very important to have a good understanding of the anisotropic geomechanical properties of this heterogeneous formation prior to developing the completion strategy.

A calibrated, anisotropic 1D mechanical earth model (1D MEM) was developed and used to optimize the completion strategy for a vertical well in the Vaca Muerta shale. The output from the 1D MEM, including the principal stresses, anisotropic elastic properties, pore pressure, and rock strength, were used to define the reservoir intervals with the best characteristics for initiation, propagation, and maintenance of a conductive complex fracture network. Next, the reservoir intervals with the highest hydrocarbon generation tendency were determined from petrophysical and image logs acquired in the well. This formed the basis for selecting the optimum number of stages and perforation strategy for the well.

Sensitivity analysis revealed the impact of the hydraulic fracture properties on the production performance. The analysis showed that higher fracture conductivity greatly improves the well performance in the deeper Vaca Muerta intervals, whereas larger fracture surface area is more beneficial across the shallower intervals. Thus, a unique completion strategy was developed for each interval to optimize the well performance. Three hydraulic fracture stages were planned initially, but because of casing limitation, only the first stage was executed. A time-lapse acoustic measurement acquired from the well corroborated the propped fracture height predicted during the completion design phase.

The study showed that proper characterization of the anisotropic geomechanical behavior of the Vaca Muerta formation improves the development of a completion strategy, which ultimately optimizes economic performance of the well.
Automated Modeling by Recognition
Authors: Anvar Amir , Fisher Christopher
Published: June 2014

Facility 3D Computer Aided Design (CAD) models are not updated regularly, or at all, once a facility goes into operations. In many brownfield assets, there is no 3D facility model to begin with. As-built models are required as a foundational technology that, through the virtual and visual experience of dynamic 3D models, will enable several business functions such as training and simulation, operations monitoring and surveillance, design modifications and project execution planning support, and hazard analysis and system reviews. In addition, the regulatory environment is changing and could result in the use of immersive 3D environments for operator competency assurance and various other compliance requirements, similar to the airline industry.

While there are existing model update processes, such as automated pipe recognition, the creation of the as-built model is a very time-consuming and labor-intensive activity that prohibits broader adoption and use, especially on large offshore Major Capital Projects.

The current objective of our R&D effort is to build an innovative modeling system, which combines data-driven and primitive-based modeling techniques, to automate the creation of 3D geometry models and texture maps from LiDAR (Light Detection and Ranging) point cloud data. In essence, this system acts as a highly automated bridge between "dumb" laser scan data and "intelligent" 3D models, enabling pervasive use of as-built models throughout an asset’s lifecycle.
Identification of Reservoir Analogues in the Presence of Uncertainty
Authors: Perez-Valiente M. L. , Martin Rodriguez H. , Santos C. N. , Vieira M. R. , Embid S. M.
Published: June 2014

We propose and evaluate a new methodology and tool for the identification of reservoir analogues of a target reservoir, given a database of known reservoirs. In particular, we focus on the common situation where some of the key properties of the target reservoir are unknown. This situation introduces uncertainty into the identification procedure. Therefore, an important step in our methodology is to characterize this uncertainty, so that it can later be considered when estimating production potential and capturing the associated risk.

The proposed methodology is composed of a sequence of five steps: Data Preprocessing, Key Parameters Selection, Statistical Learning, Similarity Ranking and Uncertainty Characterization. The first step consists of the analysis and pre-processing of the available database. During Key Parameters Selection, properties with largest impact in the case to be evaluated are identified. In the third step, unknown key properties of the target reservoir are estimated using different statistical learning techniques. In the Ranking step, a similarity function is applied to the database, generating a similarity ranking. Finally, in the Uncertainty Characterization step nonparametric methods are used to estimate probability density/mass functions to characterize the uncertainty in the properties estimated through analogous reservoirs.

We perform experiments to assess both the quality of property prediction and the quality of the selected analogues. We report results produced by five different machine learning algorithms using leave-one-out cross-validation. According to our results, Decision Trees was the most effective algorithm for categorical properties, while Regressive Support Vector Machines produced the best results for numerical properties. We also show detailed results for the Casablanca oil field as a target reservoir, which is a mature carbonate reservoir very well known by Repsol.

Our methodology allows the identification of analogues for newly discovered reservoirs with limited information. An important additional outcome is the estimation of unknown properties such as recovery factor and production mechanism, and their associated uncertainties, which support the field development plant.
An Innovative Approach To Select Shallow Casing Points Remotely, Utilizing Real-Time WITSML Data
Authors: Khudiri Musab M , Oteibi Munahi D , Gadri Waleed I , AlSanie Faisal S , Kashif Muhammad , Hickin Gary
Published: June 2014

This paper describes the continued & increasing impact of WITSML on the Drilling & Workover real time operations. The Wellsite Information Transfer Standard Markup Language (WITSML) is an Industry Standard that is used for transmitting GeoTechnical Data from the Wellsite to specialised databases. Saudi Aramco has been and remains to be the largest user of WITSML and is the Leader in the development of innovative techniques that improve Well Safety and Efficiency.

Saudi Aramco Drilling & Exploration teams have commenced a project of Picking Shallow Casing Points Remotely from their corporate offices. From past experiences we found that sending wellsite geologists to rig sites to select these Casing Points has always required people which could be utilized for other frontline exploration jobs. Due to the remote locations Saudi Aramco are also eliminating the risks associated with these field trips. Saudi Aramco teams determined to utilize the real-­-time data transfer and pick those shallow Casing Points from the office. Across these shallow sections, loss circulation is more likely to happen which means rate of penetration (ROP) data is the only entity that we depend on in order to pick these shallow Casing Points. Based on this understanding, and based on the fact that we can easily get the ROP data of the pilot well and also having ROP data of the offset wells, we see the great benefit of starting such project. In this trial project, Drilling, GOC (Geosteering Operations Center) and exploration teams were able to pick the formation tops to set the shallow casing point remotely from a few fields. This critical requirement was achieved by using AramcoLink’s Real-­-Time software that collects and transmits surface parameters data.

This Paper will address the important operational aspects that were implemented and demonstrate how this innovative technique has led to improved employee safety and operational cost savings.
Breaking the Implementation Barrier
Authors: Kilgore Laura , Hernandez Margarita , Scott Peter , MacKenzie Kenneth , Whittaker Paula , Vasquez Daniel
Published: June 2014

The barriers for implementing an Intelligent Energy (IE) Solution can vary from asset to asset. To complicate matters further, the challenges are extremely diverse ranging from organizational to technical. Quantifying the challenges requires discovering the gaps between the asset’s current state and the state required for the solution. Leadership commitment, effective workflow modeling, data quality and user’s behavioral change are examples of the kinds of gaps that could result in a delayed or potentially failed implementation.

A key component is to identify the gaps early enough to ensure the asset has the time to allocate resources and close the gaps prior to deploying the solution. The potential exists that once the asset truly understands the time, effort and resources required the business case may no longer justify the implementation for that asset. While this may appear to be a negative it actually results in the ability to improve business decisions.

To ensure a successful IE Solution Deployment and understand the true business value, processes to uncover and address the gaps between the asset’s current state and the state required for the solution is critical. In an effort to tackle the IE Solution implementation challenges, Chevron’s Upstream Workflow Transformation Team has developed processes to identify and address the barriers. These processes have been piloted and adopted as standards for implementing IE Solutions.
Implementation of Complex Event Processing for Intelligent-Field
Authors: Al-Gosayir Muhammad , Al-Nammi Moayad , Awadh Waleed , Al-Bar Abdullah , Nasser Nasser
Published: June 2014

One of the main challenges for Intelligent Field engineers is handling large amount of data stream in real-time. Finding meaningful patterns among this huge amount of data is just like trying to find a needle in a haystack. Every day reservoir and production engineers are being bombarded with streams of massive amount of real-time data coming from all kinds of Intelligent Field equipment’s including but not limited to Permanent Downhole Monitoring Systems (PDHMS), Multiphase Flowmeters (MPFM), MicroMotion Meters, Wellhead Gauges, Smart Well Completion (SWC), and Electrical Submersible Pumps (ESP). They spend significant amount of time and effort looking at the trends and analyzing the data to find anomalies. Moreover, the existing systems for data cleansing and summarization are based on batch processing, hence, engineers cannot make the right decision on time and they do not have the mechanism to instantly detect interesting patterns as data coming in streams.

The objective of this paper is to share Saudi ARAMCO experience with Complex Event Processing (CEP) as an emerging technology that is designed for low-latency and high-throughput event processing for data stream. This paper addresses the architecture, the implementation, and the benefits of CEP as a solution for Intelligent Field. The implementation will cover three common applications of CEP namely real-time data cleansing, pattern detection, and Event-Driven computation. Data cleansing covers handling out-of-bound, negative, and frozen values. Patten detection enables the detection of anomalous behavior in the data stream, such as unusual buildup or drawdown in well pressure in real-time. Event-Driven computation is trigged by events in the field, such as change in downhole pressure to perform advanced calculation logic, such as average reservoir pressure. Implementing CEP will help reservoir and production engineers obtain clean data in real time and receive notification in case of any significant event detected.
Fuzzy Logic Application to Monitor and Predict Unexpected Behavior in Electric Submersible Pumps (Part of the KwIDF Project)
Authors: Bermudez F. , Carvajal G. A. , Moricca G. , Dhar J. , Md Adam F. , Al-Jasmi A. , Goel H. K. , Nasr H.
Published: June 2014

Implementing asset-wide intelligent digital oilfield (iDOF) solutions is more complex than simply "integrating technology." For iDOF to be truly successful and achieve expectations, concepts from different fields, such as artificial intelligence (AI) or soft computing techniques, must be used to help orchestrate the technology and required functionality to deliver the "intelligence" required to meet the challenges associated with optimizing oil production. Fuzzy logic (FzL) is a type of probabilistic logic that is approximate as opposed to being precise or exact. FzL can have a range of truth values or determine a likelihood of being true.

The process of diagnosis for artificial lift systems has always relied solely on the engineer’s criteria when analyzing data. It is not uncommon for two engineers with similar backgrounds to have, on the basis of the same data, differing opinions of a well problem. It is, however, uncommon that both engineers are either completely incorrect or correct in their judgment, which begs the question as to why this occurs. When traditional binary logic (true or false) is used for well analysis, the outcomes must be either this or that, simply because of the nature of binary logic. Unfortunately, most of the time, the results of well diagnoses, especially when attempting to use a predictive approach, cannot be properly represented with a yes-no approach, which means both engineers would be correct to a certain degree; in FzL, this is called the "degree of truth." FzL incorporates the rationale of having different degrees of truth into the world of well diagnosis and adds tremendous value by raising the issue of different conditions having certain degrees of truth of being in development.

The FzL in this solution was built on a set of worldwide expert rules and converts these rules to their mathematical equivalents. Production operation’s expert rules are used to formulate the conditional statements that comprise FzL (e.g., if the motor temperature exceeds a certain limit, the pump can burn out).

This paper discusses how the AI tool determines trends by calculating a slope for a predetermined period of time for the different sensor signals and compares these sets of trends with pre-established sets of rules. The closeness of the measured trends to the models is expressed as "conditioners" that represent the likelihood of each trend occurring over a period of time.

This technique has proven to be very useful in real-time monitoring for production engineers, helping them to perform fast predictions and pump diagnostics to predict unexpected problems, such as pump wear, gas interference, tubing leaks, viscous forces, and solids-plugged intakes. Several case histories are discussed in this paper. The ultimate goal of this smart flow is to deliver field-level actions that extend pump life and reduce pump downtime.
Applying Analytics to Production Workflows: Transforming Integrated Operations into Intelligent Operations
Authors: Bravo César , Rodriguez Jose , Saputelli Luigi , Rivas Francklin
Published: June 2014

Several industry technologies support integrated operations, such as intelligent completions, real-time systems, surface-sub- surface models, workflow automation systems, etc. Each of these technologies provides relevant data pertaining to one specific part of the asset. The integration, correlation, and analysis of this data (current and historic) help the operator to understand the current state of the asset, as well as make inferences about future behavior. Such capabilities are provided by a set of tools and techniques known within the industry as analytics. Operating and service companies are using new and improved analytics to support oil and gas operations and management processes. Additionally, several analytics commonly used in the foreign market are being applied to industry operations and management workflows. This has led to more robust and effective solutions for oil and gas production operations. However, the analytics value added is limited if implemented in an isolated fashion; the real value is obtained when analytics are immersed within comprehensive production workflows, which aid in analysis, processing, and modeling of the production process. Workflows enhanced using analytics can transform integrated operations into intelligent operations. This paper presents an analysis of the primary analytics techniques and how they have been applied to support intelligent operations. To support this analysis, several application examples of analytics in oil and gas intelligent operations are described, and several case studies of real applications of analytics are referenced.
Social Networking Technologies: Can They Help Increase Production and Improve Operations?
Authors: Morneau Richard , Brink James
Published: June 2014

Approximately $1 trillion in yearly value across the commercial value chain could be created by social technologies according to a July 2012 McKinsey Global Institute analysisi. Believe that? No, we did not think so. The report finds that two-thirds of the potential value can be found in improving collaboration. Within the Oil and Gas industry, we have been chasing and improving on cross-functional collaboration for the past two decades. And, whatever the actual value generation number is associated with social networking technologies, we believe that greater levels of and more timely collaboration can only have a positive impact on production, increased efficiency and more reliable operations.

This paper will take a work process view of production operations and consider where, when and how social networking technologies can be a benefit. But a quick and limited Twitter-type of response has its drawback, which also needs to be considered and explored. We will consider what is and is not a beneficial social network and what constitutes a value- adding social network response.

The purpose of this paper is to cut through the hype and focus on where, when and how social networking technologies can and will increase production and improve safe and reliable operations. While we do not have a yearly dollar estimate associated with value creation, the same McKinsey Global Institute analysis stated: "Most importantly, we find that social technologies, when used within and across enterprises, have the potential to raise the productivity of the high-skill knowledge workers that are critical to performance and growth in the 21st century by 20 to 25 percent." which we think is a worthy goal regardless of the actual dollar amount.
Intelligent Field Infrastructure: Distributed Intelligence and Retention Based System
Authors: Almadi Soloman
Published: June 2014

The continuous technology development in different industries and Information Technologies invites opportunities for porting these capabilities to the upstream domain. Also, the goal of increasing overall reservoir performance and operational environment mount higher pressure on the operating companies. Hence, different attempts are made to explore new solutions, optimize processes, and/or introducing new enhancements. One approach is to establish parallelism between the mature industries such as Downstream and Information Technology in pursuit of Intelligent Field Infrastructure (IFI) enhancements. This shall speed up and increase the flexibility in digitizing the oil and gas fields.

The IFI success in delivering intended objectives requires embedded intelligence at all layers; from sub-surface, surface, and to the engineer’s desk top. A model that maps the intelligence for these layers to ensure a coherent end-to-end system is required. The model depends on hardware, software, and integrated data exchanges that may result in new process and/or altering the conventional operation. In this paper, the authors share systematic approach in the concept of technology parallelism and mapping intelligence at each of the IFI layers. The outcomes resulted in actual enhancements by modifying and introducing new capabilities in the IFI infrastructure’s algorithm, hardware and software. This required close collaboration with the different Service Companies. The final outcome resulted in standard feature capabilities part of the standard Saudi Aramco’s IFI solution for Intelligent Field. Case study with empirical data is used in this paper to demonstrate the enhancement outcomes on the overall operation improvements.
Digital Oilfield Implementation: Learning From the Ghostbusters
Authors: Feineman David R
Published: June 2014

Implementing digital oilfield concepts and realizing value from their mainstream use and operations has been discussed openly for the last six years or more, and there is now some evidence to suggest the value portrayed in early success stories could not be sustained. Case studies from Intelligent Energy Conferences underscore that digital oilfield maturity remains highly variable between and within organizations. This paper attempts to investigate what it takes to improve digital oilfield maturity, and is a companion paper to SPE-167832 which deals directly with what the key attributes of digital oilfield maturity are and its use across a portfolio of projects. To find guidance in how to deliver high digital oil field maturity projects, this paper suggests that some relevant lessons were built into the 1984 supernatural comedy film "Ghostbusters". The movie provides parallels to the issues of digital oilfield maturity related to people, process, technology, strategy, and governance. Insights span issues ranging from moving to higher levels of maturity from a new vision driven business model, adoption of new step out technologies, customer engagement and change management challenges, demands for results in a world of complex operational decisions, all interacting in a political environment.
Assessing the Maturity of Digital Oilfield Developments
Authors: Feineman David R
Published: June 2014

Ten years of Digital Oilfield (DOFF) implementation have left recognizable differences in adoption of the new ways of working and their enabling technologies across companies. These differences, in the state of maturity of digital oilfield activity, exist even though the concept is no longer new. Case studies of successful implementations of one or more DOFF solutions, in both greenfield and brownfield assets, are well documented. Understanding the actual state of digital oil field implementation across a portfolio of projects and assets in a single operator, or across operators today, is almost impossible due to the lack of consistent definitions of what constitutes a digital oilfield. There are differences in the R&D activity between companies in response to specific business challenges, and differences between base level and advanced capabilities needed to support different resource types. This paper examines the concepts, challenges, and benefits for establishing a maturity assessment tool for benchmarking multiple digital oilfield projects. Key insights include: The maturity model concept has been used to understand solution quality in multiple domainsThere is no agreed and consistent DOFF maturity framework or model todayA workable maturity model would have strategic and tactical implications: maturity assessment supports analyzing the gap between where we are against where we want to beMaturity assessment is an evergreen activity: assets that score high in a dimension of maturity today will see that lead erode over time unless they identify and close gaps as part of a continuous renewal process
How IO Leaders Can Use Technology to Enhance Risk Perception and Communication
Authors: Taylor C. , Sarshar S. , Larsen S.
Published: June 2014

Safe, reliable and efficient operation is a common goal for all organizations in the petroleum industry. To achieve this, the organizations must manage the risks inherent in this high hazard industry. Risk management is one example of a capability where leadership can, and does, have an impact on safe, reliable and efficient operation. In fact, poor leadership has been cited as a contributing factor in a number of major accidents, such as the Texas City refinery explosion and the Deepwater Horizon oil spill.

However, in the North Sea petroleum industry, risk management is shared across a number of disciplines and geographical locations, and so it may be difficult for individuals to maintain an adequate picture of risk during everyday activities. Risk identification, analysis and modeling are typically performed onshore by engineers with little or no offshore experience. Meanwhile, the planning of preventative and corrective maintenance tasks, including local Safe Job Analysis prior to execution of the task, is performed by personnel who may have little or no knowledge of the higher-level qualitative and quantitative risk models.

This paper seeks to identify the potential impact of this distributed approach to risk management and the implications in terms of leadership roles and responsibilities. The paper will also examine the challenges for leaders in cultivating and maintaining a good level of risk perception and communication between geographically dispersed teams.

Work is ongoing within the Center for Integrated Operations (IO) in the Petroleum Industry in Norway to investigate the solutions that IO can offer to overcome these leadership challenges. This paper will describe a case study looking at how leaders can use innovative IO software tools to enhance risk perception and communication of risk between the different disciplines and across geographical boundaries.
Overcoming Constraints with a Visualisation Environment; How such a Facility has Begun to Change the Way We Work
Authors: Scholtz E. , Wood L.
Published: June 2014

A quote from Eliyahu Goldratt’s "Necessary but not Sufficient" concisely defines how we should correctly approach the deployment of technology; "Technology is a necessary condition, but it's not sufficient."

The method provides for two types of conditions for the application of concepts, namely necessary (what are the required attributes) and sufficient(the minimum required attributes to qualify). In this discourse, participants jointly exert themselves through a process of ongoing reductive questioning to identify the necessary and sufficient conditions for the submission of a specific concept.

Other than extensive investment in technology, managers must ensure a variety of other aspects are under control in order to ensure that they maximise the business benefit available from their exploration applications (Nor, 2001). This is crucial when deploying a visualisation environment in an exploration department – a facility designed to enhance collaboration and decision making. Goldratt’s mantra applies closely here where the considerable investment in technology is indeed essential, but if treated in isolation will not deliver the expected business benefits to the exploration department, nor the operating enterprise.

"To reap the benefits at the time new technology is installed, we must also change the rules that recognize the existence of the limitation"; Goldratt was stating that the introduction of improved technology must be complimented with a consideration of existing work practices and values, to ensure maximum value is extracted from the improved capability. To this end, throughout the planning and design of PetroSA’s new Collaboration and Visualization Environment (CVE) - the first of its kind in South Africa - this high technology facility was positioned as a change enabler.

This paper describes how the new CVE has begun to embed change in the way geoscientists and drilling teams interact, thereby significantly improving the performance associated with a number of processes in the exploration and operations divisions of this National Oil Company.

Four examples of identified constraints are described in detail, supporting Goldratt’s hypothesis of championing new processes and working practices in order to create demonstrable operational improvement; in this case in a geoscience visualisation facility. Outlines are given as to how such change in working practices was undertaken, the importance of ongoing measurement of effectiveness and how such a change management journey was undertaken with the establishment of a Management Plan, in order to ensure that improvement is continuous.

This paper describes this journey from the Theory of Constraints point of view, whilst conveying the understanding that it is acceptable to know an end goal, but accept that the journey to success will alter depending on several aspects during design and implementation, whilst the goals remain non-negotiable.
Implementation of an Integrated Digital Field Project: Intricacies of Project Management and Change Management Processes for Successful Project Execution
Authors: Al-Jasmi Ahmad Kh. , Choudhuri Amit , Goel Harish
Published: June 2014

Several years back, Kuwait Oil Company (KOC), the National Oil Company (NOC) of the State of Kuwait initiated multiple projects on Kuwait Integrated Digital field (KwIDF). There was a significant amount of planning before launching the KwIDF program, however, the projects involved lots of intricacies and the implementation process involved novel experiences of obstacles and setbacks caused due to introduction of innovative work and business process which were overcome over the project cycle. The paper will delve upon the positive facilitators enabling implementation of a complex project of this nature, lessons learnt from the project and necessities of an excellent change management and project management program to successfully execute the program.

The key drivers for the projects, team structure for program management and lessons learnt will be discussed during course of this paper. There will be a short description of the KwIDF program, technical workflows implemented and production optimization runs along with conceptualization of the new concept of an integrated surface-sub surface workflows.
Building Effective Teams to Enable Project Success
Authors: Lyden John , Zeringue Amy
Published: June 2014

A comprehensive research study conducted by the Construction Industry Institute reported that the two most important contributors to project success are front end loading (FEL) and team development.

FEL has to do with the "hard" or technical aspects of the project. FEL defines the concept for the project, the project economic rationale or feasibility, and the depth and breadth of the project scope.

Team building and team development concern the "soft" aspects of a project — the activities and initiatives undertaken to help a group of individuals work effectively together and produce superior project results. When people are combined into teams, the results can be highly unpredictable. Even teams with great people and great skills can be unsuccessful. The ultimate success or failure of a project is often strongly linked to the way in which project leaders and the project team handle the soft issues. In fact, it has often been said that "the soft stuff is really the hard stuff."

In intelligent energy projects involving experts, team members and practitioners across distance and function, teamwork challenges can be magnified. Finding ways to build alignment, and productive collaboration in a complex project environment can require dedicated effort and, if not done properly, can have detrimental effects on team and project success.

This paper presents: A definition and assessment of successful teamsPrinciples for a well-designed teamTeam development—start with trust, end with trust; everything else goes in the middleTrust always affects two outcomes: speed and cost.Building a collaborative teamAddressing team challengesCase Study: Digital oilfield solution project teamTransportable lessons
Enterprise SCADA Case Study: Pipeline, Plants, Production
Authors: Seale Steven R. , Cousins Barrett , Hanna Ron
Published: June 2014

As companies working in the oil and gas industry move into the Digital Energy age, they often have to deal with legacy SCADA platforms that fail to meet the challenges of supporting their growing enterprise. Intelligent asset management across a company’s entire network of pipelines, plants, and producing fields requires the acquisition, management, and manipulation of large volumes of data. Without the proper enterprise strategy in place, a company often finds itself with fragmented data and applications all across the enterprise and unusable or unmanageable IT systems. These fragmented solutions often become a liability when trying to manage an asset’s technology, equipment, and people.

A short list of the Technical and People Challenges include: Addressing SCADA systems that historically were managed by I&E field personnelMultiple SCADA vendors, solutions, and versions deployedChallenges associated with the IT responsibilities being outsourced to multiple integratorsA multiple integrator and system approach, creating installations that are unique and independent from each otherAddressing a network infrastructure that allows for enterprise visibilityHistorical data warehousing that was never in scope with future needs

This paper discusses an enterprise approach to SCADA that supports distributed assets across multiple vertical sectors (plants, pipelines, producing facilities). The approach has been implemented in several CO2 enhanced oil recovery (EOR) projects by Denbury Resources, as it solves the requirements for support of the process and business network, data replication, system failover, redundant control centers, and data historization and management across the enterprise. Denbury is deploying the enterprise SCADA system in a growing number of its CO2 EOR assets, which includes both projects that are being converted and new assets being added through the acquisition of properties.
ISA99 Compliant Architecture for Realtime Drilling Data Capture and Remote Monitoring
Authors: Callander M. , Hashim M. , Pickering J.
Published: June 2014

This paper gives an overview of the innovative technology and ISA 99 compliant architecture that was used to implement a high availability realtime drilling data hub on a recent project in the Caspian along with proposed refinements for future deployments.

Real-time monitoring of key surface and down-hole parameters is becoming an essential part of gaining the privilege to operate a drilling campaign. In 2009 a pilot project was started to develop a new architecture to transform the way drilling data was captured and stored. The project was successful and began operation in Q4 2013. The main objectives of the project were: Implement an ISA99 (cyber security) compliant architecture for data capture and remote accessProvide a vendor neutral single source for all realtime and historic drilling data on the platformMake this data available to anyone anywhere within the companyDrive the implementation of WITSML for all interfaces

The objectives were met and the result is a consistent history of all wells that is now forming the basis of learning and continuous improvement. The final solution is based on a virtualised architecture with a fully redundant infrastructure engineered from the ground up to maximise the amount of remote support and minimise the impact on the offshore organisation.
Removing Risk and Cost from Remote Operations through Intelligent Practices
Authors: Dickson David
Published: June 2014

The Arctic is the latest O&G frontier, opening new fields in North West and North Central Russia, Norway, Greenland, Alaska and Canada. The locations imply cold, remote, dark and harsh environments that bring about new challenges to operate in a safe environment while optimizing production and productivity. Furthermore, staffing these assets can provide additional challenges, with increased costs associated with transportation, personnel safety, and often-times high turnover rates.

Vast improvements in operations are possible by adding intelligence locally in the producing asset and linking the asset into an enterprise-wide collaborative work environment. This has the effect of greatly reducing the personnel and systems footprint on remote platforms, wellheads and subsea; thus removing risk and cost from operations while improving reliability in such environments. Furthermore, these environments enable institutionalization of best practices between assets, with the goal of true knowledge management

We will examine the latest advances in Remote Operations and Remote Collaboration infrastructure and tools and examine the benefits that they bring to operating companies. We will also articulate how these concepts can be incorporated into the project design cycle to improve delivery and how this can influence the supplier / operator relationship during the commissioning phase, but also over the entire life cycle of the asset.
Samarang Integrated Operations (IO): Well Performance Workflows Enable Continuous Well Status and Performance Monitoring
Authors: B Ahmad M Zul , Sayung Colinus Lajim , Wong Lee Hin , Salim Muzahidin Muhamed , Mohd Som Mohamad Kasim , Kurniawan Rudy , Biniwale Shripad
Published: June 2014

Samarang field is located offshore Sabah, East Malaysia with first oil in 1975. Majority of the platforms are provided with fully pneumatic instrumentation / control and shutdown systems, with no provision for remote monitoring/control. This has caused limitation in acquiring data for monitoring and analyzing hence optimizing the asset. The field is undergoing a major redevelopment project with Integrated Operations (IO) being part of initiatives that covers re-instrumentation, telemetry and telecommunication infrastructure installation, Collaborative Working Environment construction and Workflows implementation.

The limitation of status quo instrumentation situation has posed challenges for Samarang asset to monitor flowing status of the wells. Consequently, a number of indirect inferences were being used to determine the status and uptime of the wells including sporadic well head observation (i.e. "feeling" or "touching" the well head assembly for vibrations) and well head fluid sampling. Added to the complexity is the flow from multiple strings and wells commingling in production headers in each of the well platforms, it is not uncommon to have cases wherein the individual string or well’s actual status and production contribution is unknown for many days (or even weeks). At best, Well Testing, which is a direct measurement of the well or string’s deliverability, is carried out once a month.

This paper describes a novel methodology of implementing workflow to achieve continuous well status monitoring objective. Workflow that combines the data feeding and processing through data driven logics as well as well models driven logics has enabled continuous well status awareness. The workflow has enabled the followings: Continuous well rate estimation using nodal analysis well model by automating data input and result output processWell flowing or quitting status inference by using wellhead pressure, temperature, valve status, gas lift injection pressure, MIG, pump voltage and frequency for natural, gas lifted as well as ESP wellsAutomated notification of well status through Tri-node Collaborative Working EnvironmentFaster reaction and decisionReduction of production deferment and increase awareness to the well status and performance