bluuebunny/crossref_metadata_2025 huggingface dataset:
Uncertainty Evaluation of Wellbore Stability Model Predictions
Authors: Udegbunam John Emeka , Aadnøy Bernt Sigve , Fjelde Kjell Kåre
Published: June 2014

There is an increasing concern in the oil and gas industry regarding wellbore stability problems. The need to improve well operations becomes more imperative as the operators move towards more challenging and harsher environments such as ultra-deep waters and high-pressure and high-temperature (HPHT) fields.

Different inconsistencies affect many previous wellbore stability analyses, resulting in incorrect results, or results that cannot be extended to other well configurations by well planners. Typical wellbore fracture and collapse models provide single-point estimates of the geopressures. The model input data may be uncertain. Failure to capture these uncertainties has led to poor predictions.

The purpose of this work is to investigate typical fracture and collapse models with respect to uncertainties in the input data with a stochastic method. Uncertainties in the input data, which include in-situ stresses, rock strength data, and pore pressure will be evaluated, to show how these contribute to the cumulative uncertainties in the model predictions.

In this approach, the input parameters are assigned appropriate probability distributions. The distributions are then applied in the wellbore stability models. By means of Monte Carlo simulations, the uncertainties are propagated, and the histograms of the outputs are generated. Two types of distributions—triangular and uniform—are applied, to see how the choice of the input-parameter distributions will influence the model predictions.

Sensitivity analysis is also carried out. This is to ascertain the most significant input parameters, which are largely responsible for the cumulative uncertainties or variabilities in the critical fracturing and collapse pressures.

The proposed methodology can help in reducing many drilling problems such as circulation loss, stuck pipe, and well collapse. As a result, the industry may save much non-productive time. In addition, well planners will have improved information to make critical decisions.
How Farmers, Graziers, Miners, and Gas-Industry Personnel See Their Potential for Coexistence in Rural Queensland
Authors: Everingham J.. , Collins N.. , Rifkin W.. , Rodriguez D.. , Baumgartl T.. , Cavaye J.. , Vink S..
Published: June 2014

The rapid expansion of the coal-seam-gas (CSG) sector in Queensland has fueled debate on the sector's contributions to community sustainability in a rural economy dominated by the farming of food and cotton, cattle grazing, coal mining, and a modest level of tourism. For example, will the impacts of CSG extraction on surface and groundwater have sustained negative impacts on the growing of grain, and if so, what should one expect of the CSG industry today?

The intensity of debate is accompanied by an array of operating conditions placed on CSG projects by the state government, extensive media coverage, and a focus on what it takes to maintain a “social license to operate.” Such a context is a challenge for resource companies committed to sustainability principles and to contributing to the social, economic, and institutional development of the communities in which they operate as well as to the conservation of biodiversity and integrated approaches to land-use planning.

In this context, our research explored perceptions of the social and environmental impacts in two local government areas of rural Queensland. We surveyed and interviewed stakeholders affected by—and/or influential in—decision making and the management of mining, CSG extraction, and agriculture in these areas. We asked their views on the state of the environment, the economy, social fabric, human capital, and local infrastructure, comparing today to 5 years ago. Their responses reveal how this contested arena harbors “wicked” problems: issues that are hard to formulate in simple terms and in which every potential solution has irreversible consequences. Our findings suggest further that the successful coexistence of multiple industries and a social license to operate for CSG companies depend on effective management by resource companies, and by regulators, of operating practices, off-site impacts, and the distribution of benefits.
Simulation of Hydrate Dynamics in Reservoirs
Authors: Vafaei M.T.. T. , Kvamme B.. , Chejara A.. , Jemai K..
Published: June 2014

Gas hydrates in reservoirs are generally not in thermodynamic equilibrium, and there may be several competing phase transitions involving hydrate. Formation of carbon dioxide (CO2) hydrates during aquifer storage of CO2 involves roughly 10 vol% increase compared with groundwater. Dissociation of hydrate toward undersaturated fluid phases involves the same level of contraction. Hydrate phase transitions are generally fast (scales of seconds) compared with mineral dissolution and precipitation, and it is unlikely that a time-shifted explicit coupling to geomechanical analysis will be able to capture the appropriate dynamic couplings between flow and changes in stress. The need for geomechanical integrity of the storage site therefore requires a reservoir simulator with an implicit solution of mass flow, heat flow, and geomechanics. And because CO2 involved in hydrate is also involved in different geochemical reactions, we propose a scheme where all possible hydrate formation (on water/ CO2 interface, from water solution, and from CO2 adsorbed on mineral surfaces) and all different possible dissociations are treated as pseudoreactions, but with kinetics derived from advanced theoretical modeling. The main tools for generating these models have been phase-field-theory (PFT) simulations, with thermodynamic properties derived from molecular modeling. The detailed results from these types of simulations provide information on the relative impact of mass transport, heat transport, and thermodynamics of the phase transition, which enable qualified simplifications for implementation into RetrasoCodeBright (RCB) (Saaltink et al. 2004). The primary step was to study the effect of hydrate growth or dissociation with a certain kinetic rate on the mechanical properties of the reservoir. Details of the simulator and numerical algorithms are discussed, and relevant examples are shown.
Pressure Evolution and Production Performance of Waterflooding inn-Heptane-Saturated Fired Berea Cores
Authors: Rezaei N.. , Firoozabadi A..
Published: June 2014

This work presents experimental results and interpretation of injection pressure and recovery performance of waterflooding in strongly water-wet fired Berea cores saturated with n-heptane. The experiments were conducted at constant injection rate at room conditions, and the effects of injection rate and initial water saturation on the oil-recovery performance and dynamic-injection pressure were investigated. Elements of surprise were observed in the injection-pressure data. The pressure profiles showed four distinct regimes, each governed by capillary or viscous forces. At low capillary numbers (Ca=uμ/σ<10–6), capillarity governed two pressure regimes, corresponding to the core inlet and outlet. In the early part of waterflooding, pressure stayed constant for a considerable time before hydrodynamic pressure gradient could overcome the capillary pressure gradient. After viscous forces dominated, a linear increase in injection pressure over time was observed up to breakthrough time. A sudden pressure rise was observed close to breakthrough because of capillary retention at the core outlet. The pressure became constant after the breakthrough when the water- and oil-saturation distributions were stabilized. Changing the injection rate by an order of magnitude in the range from 2.2 to 22.2 pore volumes (PV)/D (equivalent to Ca = 10–7 to 10–6) did not appreciably change the oil-recovery performance; similar breakthrough time and final oil recovery were observed. The effect of initial water saturation was also investigated. When lowering the initial water saturation beyond that established in oil flooding, production performance and injection pressure were similar to those of a core without the initial water saturation. The injection pressure at breakthrough was found to decrease with increase of the initial water saturation. Waterflooding was modeled by including the capillary pressure and excellent agreement was obtained with experimental results of production and injection pressure. We find that in the absence of in-situ saturation measurements, the injection pressure is a better variable for tuning the model parameters compared with the production history alone.
Intelligent Integrated Management for New Ventures in High Risk Developing Countries
Authors: Haider Muhammad Ali , Abdullah Sheikh Muhammad , Khalid Ramiz , Mirajker Meryam , Haider Batool Arhamna
Published: June 2014

The world is becoming flatter through global integration and ‘smarter’ through interconnected communication and com-merce. For oil and gas organizations this means finding ways to launch business ventures in new regions. While Afghanistan is a high risk zone with negative trade balance, weak currency & infrastructure, extreme security conditions and cultural di-versity, it is estimated to possess substantial reserves of oil and gas that may shake up Central Asia’s increasingly competitive energy contest.

The proposed framework is a step by step model which by using core competency check, decision metrics, balance scorecard models, cost equations, intelligent forecasting tools and several critical domains of knowledge management, makes sure that the organization takes right decisions regarding the manner of activities strategizing and execution, in mesh of diversified challenges. The SCOR model is integrated with processes that identify potential risk elements throughout the supply chain in Afghanistan, taken as base cases, and defines metrics to assess the potential impact of these risk elements. The framework thus developed has been used to build powerful simulation models that integrate discrete event simulation and spreadsheets. The simulation models are hierarchical and use sub models that capture activities specific to supply chains and breaks it down into further sub levels to evaluate the supply chain performance.

The model enables full leverage of capital investment, creation of a supply chain road map, alignment of business functions, reducing complexities in distribution network, and an average of two to six times return on investment. By maximizing predictability and controlling risk through excellence and efficiency in the upstream supply chain for Oil & Gas, this model provides an excellent tool for intelligent integrated management for any region that has similar mesh of chal-lenges as faced in Afghanistan.
ESP "Smart Flow" Integrates Quality and Control Data for Diagnostics and Optimization in Real Time (Part of KwIDF Project)
Authors: Al-Jasmi A.. , Nasr H.. , Goel H. K. , Moricca G.. , Carvajal G. A. , Dhar J.. , Querales M.. , Villamizar M. A. , Cullick A. S. , Rodriguez J. A. , Velasquez G.. , Yong Z.. , Bermudez F.. , Khain J..
Published: June 2014

Intelligent digital oilfield (iDOF) operations include the transfer, monitoring, visualization, analysis, and interpretation of real-time data. Enabling this process requires a significant investment to upgrade surface, subsurface, and well instrumentation and also the installation of a sophisticated infrastructure for data transmission and visualization. Once upgraded, the system then has the capability to transfer massive quantities of data, converting it into real information at the right time.

The transformation of raw data into information is achieved through intelligent, automated work processes, which are referred to here as "smart flows," which assist engineers in their daily well surveillance activities, helping make them more productive and improve decision making. A major oil and gas operator in the Middle East has invested in such an infrastructure and is developing a set of smart flows for key activities and work flows for its production operations, with the ultimate goal of improved asset performance.

The project includes a smart flow to monitor, diagnose, and optimize wells that include electric submersible pumps (ESP); 50% of the wells in this field use ESPs. The ESP smart flow includes leading-edge technologies, such as: variable speed drive controller, subsurface equipment and sensors, advanced diagnostics based on artificial-intelligence agents, analysis of sensors signals, and automatically identifying ESP optimum operating conditions.

Using a steady-state nodal-analysis model combined with an artificial intelligent technique, the ESP smart flow is designed to provide rapid diagnostics and optimization in real time, generating actions, such as decreasing and increasing the pump frequency and choke setting. The ultimate benefit is to detect the signals that foresee unexpected well downtime and predict ESP system pump failures. The paper describes the main functionalities of the ESP smart flow as a powerful optimization tool that is capable of providing an interactive monitoring system that can assist operations personnel in managing ESP-operated wells.
Maximizing the Value of Real-Time Operations for Diagnostic and Optimization at the Right Time (KwIDF Project)
Authors: Al-Jasmi A.. , Goel H. K. , Al-Abbasi A.. , Nasr H.. , Velasquez G.. , Carvajal G. A. , Cullick A. S. , Rodriguez J. A. , Scott M..
Published: June 2014

Although oilfield workflow automation processes have been implemented in the oil and gas industry during the last decade, the full impact and value of these technologies has yet to be realized. Tremendous potential still exists to implement new technology to maximize production, increase operational efficiency, and reduce down time/non-productive time. The Kuwait Integrated Digital Field project (KwIDF) is a novel intelligent digital oilfield operation for Kuwait Oil Company, the operator of the Sabriyah field in North Kuwait.

The project has successfully implemented improvements in field's operational efficiency by reducing the down time in artificial lift completion, increasing well productivity, and preventing water production. This paper provides an overview of the project from the perspective of field data acquisition, data analysis, model analysis, diagnostics, and operational optimization conducted in "right time" in the operator’s state-of-the-art collaboration center.

The automated workflow system orchestrates integrated solutions that not only provide monitoring in real time, but also enable diagnostics and optimization for individual wells. The automated workflow integration and orchestration conducted by the production team within a collaborative work environment covers the following aspects described in this paper: production surveillance (including alarming and alert events), well performance, production losses, artificial lift optimization, and key performance monitoring.
Impact of WITSML Data Surveillance on Shallow Casing Points
Authors: Khudiri Musab M , James John A , Gadri Waleed I , Bu Khamsin Ali H , Sanie Faisal S , Miyajan Ramzi A , Abbas Mazin Y , Kashif Muhammad , Jovin Tony
Published: June 2014

This paper describes the continued and increasing impact of the Wellsite Information Transfer Standard Markup Language (WITSML) on Drilling & Workover real time operations. Saudi Aramco— the biggest user and primary supporter of this industry standard — wants to share a new successful application of WITSML to their drilling activities.

Saudi Aramco Drilling & Exploration teams have commenced a project for the picking of Shallow Casing Points remotely from the Exploration and Petroleum Engineering Center (EXPEC). It has been observed from past experience that the sending of geologists to rig sites just to pick these Casing Points had always required significant manpower resources that could be better utilized for other frontline exploration jobs. In addition there is a sharply increased risk associated with the sending of these geologists to the remote field locations, since almost all of them are reached by travelling long distances by road.

The Rate of Penetration (ROP) is generally the only measured parameter that is available to assist with the picking of shallow Casing Points. By comparing this with the measured ROP, which is available from offset wells, known formation markers are identified and this allows the Casing Point depth to be chosen. In the project that is described by this Paper, exploration geologists were able to successfully identify the formation tops for most of the common surface formations in Saudi Arabia and thereby enable the picking of the Casing point in several pilot wells. This is an important milestone in the ongoing efforts of providing more cost--effective solutions for shallow sections, by using continuous real time data that is now being recorded from the spud of a well to the completion. This is being achieved remotely by using a real--time solution, called the Real Time Data Transmission and Viewer Service (RTDTVS), recently implemented at Saudi Aramco to collect the data from all of the drilling service contractors in a standardized format. This solution is referred to in this Paper subsequently as the "Aramcolink."

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.
Using Predictive Analytics for Asset Management: A Case Study of Early Warning Prediction Application
Authors: Ajayi A.. , Akinyemi O.. , Kurdi M..
Published: June 2014

Producing assets face a pressing demand to minimize unplanned maintenance. The use of basic monitoring consoles such as DCS, are limited in scope, provide isolated views and reactive in nature. This paper presents a case study of using predictive analytics in an offshore oil production facility. The facility operations performance is constantly monitored by sensors sitting across an entire installation, measuring relevant information such as temperatures, pressure levels and flow rate at different time intervals.

Predictive analytics was applied to integrate all relevant data for proactive maintenance. The predictive model uses advanced analytics to estimate problem specific KPIs that is used to generate automated monitoring, alerting and event specific reports. These help to provide advance notice of impending failures and minimizing maintenance-related disruptions in operations.

The production facility consists of many integrated components as part of the production process. Continuous workings of these components are required to meet production targets. However, some critical components malfunction without warnings and, in the worst case, halt altogether resulting in short term production loss. The purpose of the predictive model was to use data from the entire process to find any measurable characteristics that may serve to warn that these detrimental situations are approaching. Moreover, the project also aimed at providing suitable diagnostics of the situation. In this technical paper, we described a successful application of an innovative statistical method for proactive asset management using predictive analytics.

The predictive models were able to successfully provide warnings of impending failures for the component of interest and identify root causes of such impending failures.
Integration of Operations, Safety and Security Assurance
Authors: Arango G.. , Flichy P.. , Jose S. J.
Published: June 2014

Overview

There is an emerging consensus in our industry and in regulatory agencies about the need to improve our visibility of operations and to standardize as well as orchestrate the execution of operation processes to achieve integrated operations, safety and security assurance.

The complexity and risk of real-­-time exploration and production (E&P) operations is growing steadily along several axes: geology, operational environment, technology, distributed multi-­-discipline teams and multi-­-company teams. Operational performance, safety, and security assurance demand a high degree of situational awareness and real-­- time coordination.

At present, situational awareness is based on the visualization and monitoring of sensor data and, in some cases, of video feeds. Although data, video and audio travel through digital channels, they are rarely correlated or integrated. Decision makers are confronted with large amounts of data that are difficult to parse in real time and monitoring cannot be sustained over long periods of time because of distractions and fatigue. Furthermore, most decision making and coordination is based on people-­-to-­-people communication. These interactions are rarely captured, shared or integrated with other forms of data.

Other sectors involved in complex, high-­-stakes, real-­-time operations face similar conditions, for example, transportation, public safety or the military. They have learned to leverage digital technology to develop a "common picture of the operation" shared by all actors in a theater of operations. Sharing a common picture of the operation enables effective right-­-time response, efficient collaboration, and consistent decision making,

In this paper we outline:

The case for integration of operations, safety, and security assurance to create a common operations picture The capabilities of digital platforms to support a common picture of the operation How those capabilities can be leveraged in E&P operations.
Remote Communication, Collaboration and Cognition
Authors: Lomer Jocelyn
Published: June 2014

As operators search for hydrocarbons in increasingly remote and hazardous locations, so communications between the rig and head office become more challenging. The electronic media we use currently – email, telephone, electronic data transfer – all filter information, inhibiting collaborative cognition. This in turn can lead to misunderstanding of pivotal information, increasing risk to equipment, people, and indeed business value.

In this paper we will describe how the use of fully collaborative technology, backed by wide ranging psychological research into how people communicate and collaborate both in a face-to-face setting and in a variety of remote situations, can be used to optimise collaboration in the most challenging situations, reducing risk, and significantly increasing rapid, accurate decision-making in the field.

The Digital Oilfield is a reality, and the most significant change taking place is in the way in which people work in a collaborative environment. While there has been significant research into how different disciplines can work together, very little, if any, has gone into the way in which we collaborate remotely, and how that can be improved.

Our research, extending the findings by the Universities of Cambridge, Kings College London, and Surrey, demonstrates conclusively that the provision of a remote collaborative environment that most closely resembles a face-to-face meeting – natural, intuitive, and able to handle complex tasks – improves knowledge sharing and interpretation, expands thought and memory processes, and in so doing, adds significant, measurable value to remote operations.
Data Mining Methodologies Enhance Probabilistic Well Forecasting
Authors: Holdaway Keith R.
Published: June 2014

Decline Curve Analysis (DCA) is one of the most common tools to predict oil and gas well performance and determine an estimated ultimate recovery based on historical production data. Probabilistic approaches have evolved to provide a measure of uncertainty in such estimates. However, engineers have held onto the belief that such quantification of uncertainty is largely subjective. Consequently there is an innate reluctance to adopt probabilistic methodologies owing to the assumption of prior knowledge of the relevant parameters and reservoir properties distributions.

The objective of this paper is to explicate the development of an improved probabilistic approach to estimate reserves and well performance based on historical production data. This methodology precludes the assumption of prior distributions by adopting a bootstrap workflow that is implemented to construct probabilistic estimates with specified confidence intervals from historical production data. It is a statistical approach to assess the uncertainty of estimates objectively, removing the subjective nature of prior assumptions.

We shall discuss an automated selection criteria workflow for time series and forecast periods resulting in more robust and accurate DCA. The methodology1 abides by a "more rigorous model-based bootstrap algorithm" that encapsulates the appropriate steps to preserve the inherent characteristics of a time series data set that show an overall decline trend.

The paper also explores other potential advanced analytical techniques to gather knowledge from historical upstream data so as to identify wells within an asset that require some remediation based on real-time performance observations. Cluster analysis could improve engineers’ convenience in analyzing wells by separating them into groups based on decline curve shapes (patterns) and other reservoir properties. We shall define some processes that implement soft computing techniques to aggregate the DCA results with disparate upstream data via a data driven methodology. Pattern recognition and classification are important steps that underpin data mining, and we shall explicate a suite of workflows to enable a well optimization solution.
Transforming Health, Safety and Environment Strategy and Culture Using Social Business
Authors: Weitner M.. , Hatler D..
Published: June 2014

Over the past several years, the health, safety and environment (HSE) management paradigm has been shifting from a command-and-control, compliance-oriented model to a stakeholder management, market-based model. This new model is enabling organizations to differentiate themselves in the market through reduced operational risk, enhanced corporate brand and increased shareholder value. Organizations are finding it necessary to align HSE management processes with their overall business strategies and adopting a shared vision that represents the collective aspirations of the organization and its key stakeholders. This shift requires companies to dismantle what have previously been considered impervious internal organizational silos and open up conduits of communication between all stakeholders. Because this shift significantly impacts the culture of an organization, they can use social business tools, techniques and practices to ensure a more successful transformation and adoption to this new HSE paradigm.

Social business can help organizations better engage relevant resources and expertise, improve real-time communication and decision making, and enhance transparency and situational awareness. In this paper, the authors discuss how social business can be applied to the business of health, safety and environment management to support this paradigm shift from a liability managed program to an asset managed program. Such a shift will help companies evolve from a compliance reporting focus to a collaborative management process that encompasses their workers, partners, customers, shareholders and even the communities in which they operate.
Inflow Monitoring in Intelligent Wells using Distributed Acoustic Sensor
Authors: Xiao J.. , Farhadiroushan M.. , Clarke A.. , Khalifa Q.. , Mulhem A.. , Forero Reyes H.. , Parker T. R. , Shawash J.. , Milne H. C.
Published: June 2014

Intelligent well completions enable production and/or injection to be controlled and optimized across multilateral reservoir zones. The Distributed Acoustic sensor (DAS) is a promising technology for a number of wellbore monitoring applications such as distributed flow profiling. The DAS system can provide real-time monitoring across several zones equipped with Inflow Control Valves (ICVs) and Inflow Control Devices (ICDs) that are used to optimize the production and extend the life of the reservoir.

The new intelligent Distributed Acoustic Sensor (iDAS) uniquely allows the simultaneous recording of acoustic energy along many kilometers of optical fiber deployed along the wellbore. The system uses a novel digital optoelectronics detection technique that captures the amplitude and phase of the acoustic waves generated and propagated along the wellbore over a wide frequency (8mHz – 100kHz) range with a high dynamic range (>120dB). A number of signal processing techniques have been developed for processing a large array of acoustic data that can be recorded along the wellbore for monitoring the inflow at different zones.

There are a number of intelligent well completions with fiber optic cable installations in Saudi Arabia. The DAS system described here can be retrofitted to the existing installations both with the multimode fibers, which were originally installed for the Distributed Temperature Sensor (DTS), and with single-mode fibers that are used for telemetry to point optical sensors.

The paper will report on the first survey results of the DAS measurement in an intelligent well that is equipped with ICVs. The results will show how the DAS system can be used to monitor the completion components such as by listening to the inflow noise across ICVs and ICDs and indicate the inflow contributions from different zones. The paper will present the first DAS survey using multimode fibers that was installed for the DTS measurements.
Application of Inflow Well Tracers for Permanent Reservoir Monitoring in North Amethyst Subsea Tieback ICD wells in Canada
Authors: Montes Andrew , Nyhavn Fridtjof , Oftedal Gaute , Fævelen Erlend , Andresen Christian , Leung Edmund , Wikmark Vidar
Published: June 2014

North Amethyst is the first subsea tieback field development for Husky Energy’s White Rose project, located off the East Coast of Newfoundland and Labrador, Canada. The geographical location presents some of the harshest weather conditions in the world due to the elevated sea states and ice conditions. The North Amethyst field achieved first oil in 2010 and at the end of December 2011, had three production wells and three water injectors. Further wells are planned as part of the development.

To counter imbalance in the horizontal flow profile that can lead to early water or gas breakthrough, the field development strategy employed Inflow Control Device (ICD) technology. The ICD technology application was the first offshore on the East Coast of Canada.

A method of proving effective horizontal clean-out and flow distribution for the ICD technology was necessary. However, due to the subsea configuration complexity, semi-submersible rig costs and delays due to unfavorable weather conditions, the prospect of production logging the horizontal wells was deemed a high risk and expensive operation.

To overcome these hurdles, unique inflow tracer technology was used in tandem with the ICDs to provide validation of clean-out and horizontal flow distribution. The North Amethyst producers were equipped with unique oil and water soluble tracers placed along the horizontal, embedded in the ICD screens. The tracer technology’s objectives were to monitor the zonal contributions during clean-out and during the production phase. Water tracers were to monitor and identify the location of zonal water breakthrough.

Topside fluid samples were analyzed, and tracer concentrations provided the basis for extracting well inflow information. The utilization of inflow tracer systems in collaboration with other reservoir engineering tools has provided validation of horizontal contribution and feedback about individual ICD nozzle placement. This paper will document the design, execution, and analysis of the tracer results in two initial North Amethyst ICD producers.
WellPlanET — Smart & Efficient Drilling Well Program by Saudi Aramco
Authors: Radhwi A. O , Amer M. M. , Idrees H.. , Fakhruddin A.. , Hazzazi M. A.
Published: June 2014

Drilling and Workover activities generate a lot of information that can be further used to improve the optimization of future activities and reduce: costs, drilling time and the time drilling engineers require to prepare a drilling program. To address this concern, Saudi Aramco developed the Well Planning Engineering Integrated Tools (WellPlanET). The well planning process is the most critical activity during drilling and completion. It starts by capturing the requirements from Exploration & Reservoir Engineering, and ends with a drilling program outlining the drilling execution plan. Supplements and revisions of the original plan may occur during the execution. This planning process involves consideration of many data types, including: formation pressures, offset well data, reservoir location, time, cost, etc. Overlooking any single data aspect could lead to severe drilling problems and time losses, especially for an Oil & Gas Operator like Saudi Aramco, where the Drilling & Workover agenda includes a large number of wells, of different types, and the operational involvement of many stakeholders.

For that reason, Saudi Aramco has recently commissioned a new Well Planning Engineering Integrated Tools (WellPlanET) environment as a one box solution for drilling engineers to facilitate, plan, manage and streamline the well design in a simple, yet smart way. This involves a new re-engineering D&WO Planning Systems environment and workflows from desktop- based to a more integrated web-based environment that employs Aramco data repositories (structured, unstructured, file systems, etc.), application portfolio (in-house, vendor, real-time, historical, Drilling, Exploration, PE, etc.) and workflows to deliver users requirements and address the Drilling & Workover strategic goals and plans. It also provides a systematic way of generating, validating, simulating and optimizing the Drilling Program during both pre-drilling, execution and post-drilling phases.

WellPlanET is a comprehensive integrated knowledgebase that ultimately facilitates well planning engineering, and advanced well design optimization. The system automates capturing all Drilling Program planning data (over 14 different data types such as Trajectory, Mud designs, Wellhead designs, etc.) in a structured manner to establish a complete integrated well planning repository to enable many advanced engineering modules such as Prediction, Simulation and Artificial Intelligence analysis features, using historical and planning data with full integration with key industry standards systems such as Geo- Pressure & Geomechanics analysis tools, Drilling Fluids and Well Hydraulics optimization tools, BHA/Wellhead/CrossSection designing tools to optimize the overall drilling program.

This paper shares Saudi Aramco’s experience in building and deploying WellPlanET as a smart and efficient way of generating the drilling well program.
Formation-Resistivity Theory: How Archie Equations, Shaly-Reservoir Models, Conductive Rock-Matrix Model, and Dual-Triple-Porosity Models Are Related
Authors: Iheanacho Philip C.
Published: June 2014

The estimation of hydrocarbon pore volume (HCPV) from resistivity logs can be quite troublesome in some complex heterogeneous reservoirs. Most water-saturation/formation-resistivity models that work well for some reservoirs give unreliable results for others. No single model works for all types of reservoir scenarios.

This paper presents the theory of formation resistivity in porous media. The paper develops the theory from the parallel-resistivity model and then extends it for the series-resistivity model.

When applied for clean sand, the theory derives Archie equations from the first principle. The derivations show that both porosity exponent and saturation exponent are of the same origin and should have the same name. A better name for both parameters should be the tortuosity exponent of a component with respect to its fraction in a control volume. It is also advantageous to treat as a single parameter rather than two separate parameters.

In addition, this theory derives new shaly-sand models for estimating HCPV. These new shaly-sand models can be used for different types of shale distribution by adjusting the value of a single parameter in the models. The formation-resistivity theory is also used to derive formation-resistivity models for conductive rock-matrix reservoirs and dual-triple-porosity reservoirs. A new equation for calculating the composite-porosity exponent is also developed.

Field data are used to validate this work. The theory, when applied for each scenario, derives formation-resistivity models for estimating the reliable HCPV of different reservoir scenarios and types. Moreover, the strength of this theory is its ability to generate models that closely resemble models that have proved to work well for the reservoir cases for which they were developed. Although this work does not test the theory for the cases of tight-sand, shale-gas, and other unconventional reservoirs because of the unavailability of such data, the author is of the opinion that the theory can easily be extended for such reservoirs if the necessary data are available.
Modeling of Shale-Erosion Behavior in Aqueous Drilling Fluids
Authors: Maghrabi Shadaab , Kulkarni Dhanashree , Teke Kushabhau , Kulkarni Sandeep D. , Jamison Dale
Published: June 2014

Numerous shale-stability issues can occur while drilling with water-based muds (WBMs), including shale sloughing and cutting disintegration. These issues can be detrimental to the formation and pose difficulties with respect to rheology control, possibly reducing the rate of penetration (ROP). A "shale-erosion test" is a well-known laboratory test used to characterize the erosion of cuttings in WBMs.

This paper documents a mathematical modeling tool known as an artificial neural network (ANN) used to model the erosion behavior of shale cutting in WBM. The ANN model establishes complex relationships between a set of inputs and an output based on computational modeling. For ANN modeling of shale-erosion behavior, the shale mineralogy and fluid composition constitute a set of inputs, while experimentally obtained "% erosion or % recovery" of the cuttings from the shale-erosion test represent the output.

Experimental data for building the ANN model was obtained by performing approximately 150 standard shale-erosion tests using five different shales with varying mineralogy and WBMs with varying salt concentrations/types, shale stabilizers, and mud weights. For every test conducted, the input data (shale and fluid characteristics) and the output data (% recovery) was incorporated into the ANN model. The ANN model was then run to establish relationships between inputs and the output, which exhibited excellent correlation with R2 ≈ 0.85–0.90. The ANN model was successfully validated for an independent set of shale-fluid interactions.

With the novel ANN model in place, erosion behavior of cuttings could be predicted in advance, thereby reducing the number of trials necessary in technical service labs. Mud engineers can use this model on a real-time basis as the shale chemistry varies with the depth of the formation drilling. The model could provide convenient measurement of fluid performance, enabling fluid optimization necessary to obtain desired shale behavior in advance, thereby minimizing drilling risks and costs associated with these oftentimes unpredictable shales.
Optimizing Lateral Lengths in Horizontal Wells for a Heterogeneous Shale Play
Authors: Chorn Larry , Stegent Neil , Yarus Jeffrey
Published: June 2014

A successful evaluation and development program in oil- and gas-bearing shales requires considerable analysis and investment, not to mention optimization to help ensure a profitable outcome. Accelerating optimization, reducing capital expenditures, and improving lifecycle net present value (NPV) for the asset are reasonable goals. Seven shale properties are key drivers to help achieve successful play economics. However, the heterogeneity of shales makes well location selection difficult without appraisal well logs and geostatistical mapping of shale property quality. The analysis method allows operators to quickly high-grade areas within a large, heterogeneous shale play using logging suites from a limited number of wellbores in the play. Further, the methodology has been extended to quantify the play's potential reward versus risk distribution for in-fill drilling investments. This study extends the method to optimizing lateral lengths of horizontal wells. Geostatistics provides a means to determine correlation lengths of aggregate shale properties known to be critical to successful economics. The correlation length is used to determine the appropriate length of the horizontal well lateral, restricting it within the highest rock quality for stimulation effectiveness and production rates. Because optimal lateral lengths can be predicted using this approach, it is now possible to pinpoint the best wellhead location, the best landing point for the horizontal portion of the well, and set the optimal length of the lateral. This reduces the drilling of unproductive lateral lengths and targets stimulations. By shortening the "trial-and-error" evaluation lifecycle stage using this methodology, an operator can develop an asset more quickly and at less cost than with previous approaches.
Imbibition and Water Blockage in Unconventional Reservoirs: Well Management Implications During Flowback and Early Production
Authors: Bertoncello A.. , Wallace J.. , Blyton C.. , Honarpour M.. , Kabir C. S.
Published: June 2014

Driven by field logistics in an unconventional setting, a well may undergo weeks to months of shut-in following hydraulic-fracture stimulation. In unconventional reservoirs, field experiences indicate that such shut-in episodes may improve well productivity significantly while reducing water production. Multiphase flow mechanisms were found to explain this behavior. Aided by laboratory relative-permeability, capillary pressure data, and their dependency to stress in a shale-gas reservoir, the flow-simulation model was able to reproduce the suspected water blocking behavior. Results demonstrate that a well resting period improves early productivity while reducing water production. The results also indicate that minimizing water invasion in the formation is crucial to avoid significant water blockage.
Well Design Evolution Towards the First Commercial Unconventional Gas Flowrate in Europe
Authors: Thwaites Nicholas , James Lynne
Published: June 2014

The demand for indigenous supplies of natural gas in the UK and other countries in Europe has driven operations in the unconventional gas arena since the 1990s. In Coal Bed Methane (CBM) there have been attempts in the UK, Belgium, Germany, France and Poland.

Dart Energy and its heritage company, Composite Energy, have been active in CBM in the UK since 2004, drilling 25 CBM wells in the UK, including 10 appraisal and development wells on the Airth field in central Scotland. A further 4 appraisal wells were drilled by the previous operator of the Airth field in the 1990s.

The local Carboniferous coal geology, as with most European coals of Carboniferous age, is characterised by thin, numerous, low permeability, undulating coal seams. A number of different well designs were tried over the 14 Airth wells to meet the challenges of the local geology: initially vertical fracture stimulated wells; moving to geosteered multi-lateral horizontal wells, either intersecting a vertical well at the end of the horizontal section or as ‘updip’ branches off a motherbore without an intersection and finally multilateral geosteered horizontal wells intersecting a vertical well at the start of the horizontal section.

The evolution in well design incorporated learnings from drilling operations, reservoir geology and production operations for each type of well architecture and advances in drilling technology in other CBM provinces around the world, adapting them to answer the particular subsurface problems encountered in the Airth field. Eventually, through this evolutionary learning process, Dart Energy was able to announce a commercial flowrate of 0.7MMscf/d from Airth 12 in January 2013, a multi-lateral horizontal well with a vertical well intersection at the start of the horizontal section.

This paper describes the journey to that success, charting the evolution of CBM production well design on the Airth field, recognising the geological factors that drive well design, an evolution that can be applied to Carboniferous coal systems with thin, numerous and structurally complex coal seams found in other parts of the UK and Northern Europe.
New Sponge Liner Coring System Records Step-Change Improvement in Core Acquisition and Accurate Fluid Recovery
Authors: Shale Les , Radford Steven , Uhlenberg Thomas , Rylance Jon , Kvinnesland Audun , Rengel Carlos
Published: June 2014

New sponge coring service and technology have been introduced to the oil and gas industry. Admittedly sponge coring has been an industry offering in some form for over twenty years but until now it has been plagued by chronic problems. The objective of sponge coring was to determine separate in-situ oil and water saturations of the formation materials. The problem with conventional coring has always been that the fluids would be expelled and lost from the core by the expanding gas while bringing it to the surface. The long-time solution was to surround the core with a special oil-absorptive (oleophilic) sponge material that would capture the expelled oil and hold it in place for laboratory analysis. The challenge was to fit the sponge tightly enough around the core to prevent fluid migration and mud contamination in the sponge-core clearance annulus, and yet avoid core jamming and sponge damage.

This new, more accurate sponge liner coring service is now in place, showing excellent results. A balance seems to have been achieved between smooth core entry and a properly fitting, pre-saturated sponge with virtually no fluid migration. This new service cuts and provides oil-absorptive sponge-encased 3½-in. diameter core in 30 ft lengths with a maximum downhole temperature and pressure of 195°F (90° C) and 15,000 psi (1,034 bar) respectively. Special vacuum pump service equipment and sealing system are utilized to pre-saturate the sponge liner with brine.

In late 2012 a major operator utilized this new and previously unproven system to core nearly 300 ft of sponge core in New Mexico, USA. The coring program used a special low-invasion coring fluid with a low spurt loss and a staged trip-out-of-the-hole schedule to minimize gas expansion/oil movement. The precision core bit that cut a tight-clearance core provided exceptional results with an average rate of penetration (ROP) of 10.4 ft/hr, with 97% core recovery and observable oil saturation in the sponge, indicating the system worked as designed. This case study will be described in detail within this paper.