Historical Drilling Research Articles

Research on adaptive feature optimization and drilling rate prediction based on real-time data

In the drilling process, the rate of penetration (ROP) is an essential indicator of drilling efficiency. Accurate prediction of the rate of penetration (ROP) is crucial for improving drilling efficiency and minimizing costs. Conventional ROP predictions are typically made post-drilling, often resulting in low accuracy and limited applicability. To predict ROP more efficiently and accurately, an adaptive feature-optimized ROP prediction method based on real-time data was proposed. Initially, a fusion feature selection algorithm based on historical drilling data was designed and optimized using the Particle Swarm Optimization algorithm (PSO). On this basis, adaptive feature optimization was performed on real-time drilling datasets, and four different machine learning ROP prediction models were established using the selected feature parameters. The result shows that compared with the non-adaptive methods, the accuracy of the ROP prediction model using adaptive feature optimization is improved. The improvements are 27%, 44%, 47% and 47%, respectively, it demonstrates the significant advantages of using the designed adaptive feature optimization.

Characterizing Natural Hydrogen Occurrences in the Paris Basin From Historical Drilling Records

AbstractThis study investigates natural hydrogen (H2) occurrences in the Paris Basin, using Optical Character Recognition (OCR) technology to analyze an extensive, yet underexploited, database that contains historic drilling records. The potential of natural hydrogen has been largely unexplored in conventional oil and gas wells. Utilizing the in‐house CVAGeoDB database based on public well data, which includes well logs, mudlogs, and End Drilling Reports (EDRs) in PDF image format, we applied the Tesseract‐OCR Engine to convert these documents into searchable formats for efficient data analysis. Our analysis revealed several H2‐bearing wells across French sedimentary basins. The hydrogen occurrences in the Aquitaine Basin may be explained by the geological context and in particular the presence of a mantle body at shallow depth. On the contrary, the detection of H2 in the Paris Basin cannot be explained in a straightforward manner as the presence of ultramafic or U‐rich rocks is poorly documented so far. In the Paris Basin, H2 has been detected in four main formations: the Lusitanian, the Dogger, and Triassic aquifers as well as in the basement. The highest hydrogen concentration (52 vol%) was measured in the Dogger aquifer. These wells are primarily located along the Bray Fault, indicating at least a structural influence on H2 distribution. Finaly, the presence of serpentinzed dunite from the Lizard complex associated with the bedrock may have played the role as a source for H2. This research demonstrates the effectiveness of OCR in reassessing historical drilling data for natural hydrogen exploration, highlighting the need for comprehensive exploration methodologies in this emerging field.

Advanced Drilling Optimization through Predictive Data Analytics and Machine Learning Pipeline

The paper provides a pattern and methodology to optimize drilling in the oil and gas industry through integration of data analytics and machine learning. Drilling operations have unpredictable subsurface conditions, which leads to operational inefficiencies. My methodology ingests historical drilling data, real-time sensor data, and geological data to train machine learning models. I discuss the implementation and analysis of a data analytics framework that collects and preprocesses data streams, and send the data for machine learning. The paper offers keywords aimed at enhancing discoverability, indexing, clarity, and visibility. The introduction section details context, relevance, objectives, scope and structure of the paper. The Problem Statement section details business problem. The solution section provides methodology to address the identified problem. The architecture diagram section illustrates the system architecture and design. The architecture review details the selected architecture. The implementation section provides steps to implement solution, detailing the specific tools, technologies, and methodologies utilized in its development. The implementation for Proof of Concept (PoC) section provides a strategy as how to plan for the implementation of the solution at the organization level. The use cases section provides details about what a business can derive information to make decision. The impact section details the business value. The extended use case section so how the proposed solution can be implemented across diverse industries and domains, highlighting the potential for widespread applicability.

Research on the Rate of Penetration Prediction Method Based on Stacking Ensemble Learning

ROP is an important index to evaluate the efficiency of oil and gas drilling. In order to accurately predict the ROP of an oilfield in Xinjiang working area, a ROP prediction model based on the historical drilling data of this working area was established based on stacking ensemble learning. This model integrates the K -nearest neighbor algorithm and support vector machine algorithm by stacking ensemble strategy and uses genetic algorithm to optimize model parameters, forming a new method of ROP prediction suitable for this oilfield. The prediction results show that the accuracy of ROP prediction by this method is up to 92.5%, and the performance is stable, which can provide reference for the optimization of drilling parameters in this oilfield and has specific guiding significance for improving the efficiency of drilling operations.

Holistic autonomous model for early detection of downhole drilling problems in real-time

Due to the recent increase in drilling operations complexity, the frequency of undesirable downhole events occurring while drilling a well is in ascend trend leading to substantial growth in non-productive time. Consequently, overall drilling costs become sky-high, a moment in which earlier and precise detection of the downhole drilling problems becomes a crucial factor in cost reduction. This paper presents an intelligent algorithm that can automatically analyze real-time drilling data and accurately detect and verify the presence of the most common downhole drilling problems upon their effective inception, which allows corrective measures to be applied at the appropriate time, resulting in a reduction of the negative impact and the associated cost of the detected downhole failure. The presented algorithm relies on constructing a risk predictive window by integrating a stochastic model with a data-driven model driven from real-time data of the surface and /or subsurface drilling parameters to detect the downhole problems. The process starts by building predictive models for predefined drilling parameters. Based on the natural distribution of the Residual Errors (REs) obtained while building the productive model, the best probability model that fits the REs data is picked. The statistical properties of the selective probabilistic models and the real-time predictive values of the predefined drilling parameters are used to generate multiple dimensional risk predictive windows; the indicated risk predictive window could have one or two dimensions, depending on the number of pre-built productive models. The downhole drilling problem is detected by observing and comparing the real-time measured value of the used drilling parameters with the risk predictive window; consecutive data points located outside the risk predictive window are considered abnormal. An alarm is triggered when the number of sequent outliers reaches a predetermined boundary. The developed algorithm was tested on a historical drilling dataset in which different downhole incidences occurred. The results show that the algorithm successfully detected all of the events at an average of 120 min before the officially recorded time.

Framework for automated generation of real-time rate of penetration models

Due to highly uncertain underground conditions, most estimations of drilling and geological parameters must be performed using numerical modeling, thus by fitting empirical models to measurement data or by using an approach based on data analysis. In this paper, a combination of these two solutions is proposed for a realistic replication of historical drilling data in a drilling software simulator environment e.g., the DrillSIM:600 at Drilling Simulator Celle (Clausthal University of Technology). The whole process ranging from the modeling over the model evaluation and selection to the integration in the simulator environment is integrated within the presented framework. For this study several empirical models and five machine learning algorithms were applied to benchmark the performance on predicting the drilling parameter Rate of Penetration (ROP) using data from a single geothermal well located in northern Germany. The results of the comparison between the classical and the data driven models prove that the use of data analysis methods is a very valuable alternative to explore, describe, diagnose, and predict the underground conditions and drilling parameters. Those can be used to optimize the entire drilling process by replicating critical situations, recommending better practices or emphasizing the proper performance of a whole drilling project. Thus, by turning raw historical data in valuable insights, the further education of decision makers and rig crews can be significantly enhanced.

Exploration-resource assessment of productive felsic volcanic centers in the Paleoproterozoic Penokean Volcanic Belt of northern Wisconsin, Michigan and east-central Minnesota, USA

Five productive felsic volcanic centers have been identified in the Paleoproterozoic Penokean Volcanic Belt (PVB). Each center hosts at least one potentially economic polymetallic volcanogenic massive sulfide (VMS) deposit. To date, these drill-defined (inferred + indicated + measured) resources collectively contain over 93 million tonnes of VMS-style, base (Cu, Pb, Zn) and precious metal (Ag, Au) mineralization including nearly 4 million ounces of gold. This does not include smaller, less defined (mostly inferred) deposits in the belt that would increase the total to at least 150 million tonnes. From this resource base only 1.73 million tonnes of actual ore production has occurred. However, previous positive feasibility studies completed on the Crandon (1994), Lynne (1995) and most recently (2020) Back Forty deposits verify a total of approximately 44 million tonnes, or 47% of the total drill-defined resource base, are potentially minable reserves. Currently the PVB resource base remains as unrealized new wealth.Mineral resource assessments completed in 1996 and 2007 collectively suggest there is a high probability of at least 4 to 22 (average ~13) or more VMS deposits remaining to be discovered in the Ladysmith-Rhinelander complex and to a lesser extent the Wausau complex of the PVB. These newly discovered VMS deposits will fill out the tonnage distribution for this belt by following a natural geometric (log normal) progression consistent with established grade-tonnage models. It is postulated that among these will be one giant (>100 million tonnes) deposit. If verified, potentially economic VMS mineralization hosted by the PVB would be comparable to other productive Paleoproterozoic greenstone belts in the Canadian Shield such as Flin Flon (>200 million tonnes) or even approach that of the prolific Neoarchean Abitibi (~775 million tonnes).Exploration to date suggests that many of these undiscovered VMS deposits will be identified in five, highly permissive felsic volcanic centers. These centers, which comprise less than 2% of the known belt, are distributed within the Highway 8 intra-arc rift basin of the 1,880 to 1,860 Ma old Ladysmith Rhinelander volcanic complex. Exact aerial boundaries are poorly defined. However, extrapolation of geophysical, drill hole and rare outcrop data provides a reasonable estimate. Each productive center is stratigraphically associated with major, district-scale, commonly mineralized, meta-argillite formations or formational groups. Felsic centers are identified in the Wausau complex but have thus far been barren of significant VMS-style mineralization as is the adjacent Wausau basin.Future exploration for new VMS deposits should be focused within the productive felsic centers where a number of prospective targets and prospects have been previously identified. Other significant felsic centers likely exist within the Highway 8 basin particularly in Cambrian sandstone-covered areas along the western and eastern margins of the belt. Additionally, at least one felsic center may be present in the Milaca complex which could have VMS potential.Of particular note is the VMS potential of a second mostly Cambrian sandstone-covered, greenstone belt in the Marshfield subterrane (Eau Claire complex). Geophysical data suggest possible back-arc or intra-arc rift basins may be present and historical drilling has identified at least one VMS occurrence. This highly prospective volcanic complex is essentially new hunting ground with its own deposit tonnage distribution of potentially supergene-enriched VMS deposits. Based on criteria set out in a 2007 mineral assessment, this belt has the potential to host at least 1 to a maximum of 15 deposits.

Real-time monitoring and early warning of well leakage based on big data analysis

In petroleum drilling engineering operations, complex lost circulation accidents not only affect the efficiency of drilling operations, but serious lost circulation may cause wellbore failure. The occurrence of lost circulation accidents is affected by various factors such as formation conditions, engineering parameters, and operating dynamic parameters. The conventional focus of lost circulation research is to analyze the mechanism of lost circulation, but the data such as engineering parameters and operating dynamic parameters when lost circulation occurs are insufficiently utilized. At present, the field of drilling engineering has accumulated a large amount of historical drilling data, and the complicated occurrence of lost circulation accidents often has regional statistics. How to use big data technology to establish the correlation model between lost circulation and parameters, reason and analyze the main influencing factors of lost circulation, then use the established correlation model comparative analysis. After the data model comparative analysis, it can make different specifications of responses and early warnings for data anomalies with different weights, so as to reduce the impact on drilling operations while avoiding lost circulation accidents.

Recent advances in the study of Arctic submarine permafrost

AbstractSubmarine permafrost is perennially cryotic earth material that lies offshore. Most submarine permafrost is relict terrestrial permafrost beneath the Arctic shelf seas, was inundated after the last glaciation, and has been warming and thawing ever since. As a reservoir and confining layer for gas hydrates, it has the potential to release greenhouse gasses and impact coastal infrastructure, but its distribution and rate of thaw are poorly constrained by observational data. Lengthening summers, reduced sea ice extent and increased solar heating will increase water temperatures and thaw rates. Observations of gas release from the East Siberian shelf and high methane concentrations in the water column and air above it have been attributed to flowpaths created in thawing permafrost. In this context, it is important to understand the distribution and state of submarine permafrost and how they are changing. We assemble recent and historical drilling data on regional submarine permafrost degradation rates and review recent studies that use modelling, geophysical mapping and geomorphology to characterize submarine permafrost. Implications for submarine permafrost thawing are discussed within the context of methane cycling in the Arctic Ocean and global climate change.

Utilizing indicator kriging to identify suitable zones for manual drilling in weathered crystalline basement aquifers

Abstract: Manual drilling offers a practical and affordable method of increasing access to groundwater supply in regions struggling with economic water scarcity. However, manual techniques are limited to specific hydrogeological contexts and must be sited appropriately. Indicator kriging is proposed as an interpolation method that builds upon previous efforts to identify suitable zones for manual drilling, particularly in weathered crystalline basement aquifers. This approach allows for heterogeneity within weathering profiles and provides probability mapping of success for regional planning. Modeling was conducted in the Upper East Region of Ghana using available borehole-log data, including: well yield, static water depth, laterite thickness, depth to hard rock, water quality parameters, and the degree of weathering. Indicator kriging interpolations for depth to hard rock predicted binary variables with over 90% accuracy. The model predicts that drilling into highly weathered layers will often be necessary to reach the required depths for groundwater use, emphasizing the importance of percussion techniques. The results suggest that suitable zones occur near Bolgatanga, Bawku, and Zebila, which coincide with historical drilling efforts in the central and eastern portions of the region.

Deep reflection seismic imaging of iron‐oxide deposits in the Ludvika mining area of central Sweden

ABSTRACTReflection seismic data were acquired within two field campaigns in the Blötberget, Ludvika mining area of central Sweden, for deep imaging of iron‐oxide mineralization that were known to extend down to 800–850 m depth. The two surveys conducted in years 2015 and 2016, one employing a seismic landstreamer and geophones connected to wireless recorders, and another one using cabled geophones and wireless recorders, aimed to delineate the geometry and depth extent of the iron‐oxide mineralization for when mining commences in the area. Even with minimal and conventional processing approaches, the merged datasets provide encouraging information about the depth continuation of the mineralized horizons and the geological setting of the study area. Multiple sets of strong reflections represent a possible continuation of the known deposits that extend approximately 300 m further down‐dip than the known 850 m depth obtained from historical drilling. They show excellent correlation in shape and strength with those of the Blötberget deposits. Furthermore, several reflections in the footwall of the known mineralization can potentially be additional resources underlying the known ones. The results from these seismic surveys are encouraging for mineral exploration purposes given the good quality of the final section and fast seismic surveys employing a simple cost‐effective and easily available impact‐type seismic source.

Improved Wellbore Stability in North Sea Lark and Horda Shales Through Shale/Fluid-Compatibility Optimization

Summary Offshore wells drilled in the central and northern North Sea have historically suffered from borehole-instability problems when intersecting the Upper/Lower Lark and Horda Shale formations using either water-based mud (WBM) or oil-based mud (OBM). A wellbore-stability investigation was performed that focused primarily on improving shale/fluid compatibility. It was augmented by a look-back analysis of historical drilling operations to help identify practical solutions to the borehole-instability problems. An experimental rock-mechanics and shale/fluid-compatibility investigation was performed featuring X-ray-diffraction (XRD) and cation-exchange-capacity (CEC) characterizations, shale accretion, cuttings dispersion, mud-pressure transmission, and a new type of borehole-collapse test for 10 different mud systems [WBM, OBM, and high-performance WBM (HP-WBM)]. The results of this investigation were then combined with the results of a well look-back study. The integrated study clearly identified the root cause(s) of historical well problems and highlighted practical solutions that were subsequently implemented in the field. The borehole-instability problems in the Lark and Horda Shales have a characteristic time dependency, with wellbore cavings occurring after 3 to 5 days of openhole time. The problems were not related to mud-weight selection but were instead caused by mud-pressure invasion into the shales, which destabilizes them over time. An experimental testing program revealed that this effect occurs in both WBM and OBM to an equal extent, which explains why nonoptimal field performance has historically been obtained with both types of mud systems. New HP-WBM formulations were identified that improve upon the mud-pressure invasion and borehole-collapse behavior of conventional OBM and WBM systems, yielding extended openhole time that allows the hole sections in the Lark and Horda Shales to be drilled, cased, and cemented without triggering large-scale instability. Look-back analysis also indicated that secondary causes of wellbore instability, such as barite sag, backreaming, and associated drillstring vibrations, should be minimized for optimal drilling performance. A new HP-WBM system, together with improved operational guidelines, was successfully implemented in the field, and the results are reported here.

What is Down Plunge of the Dobroyde Hill High-Sulphidation Epithermal Deposit, near Junee, NSW? An Emerging Carbonate-Base-Metal-Gold Epithermal System

Discovered by Getty Oil in 1983, the outcropping Dobroyde Hill 77k Oz gold high-sulphidation epithermal prospect is now known to transition into a carbonate base-metal epithermal gold system down plunge. The project is 50km north of Wagga Wagga and 10km north of Junee which is the far southern toe of the Junee-Narromine Volcanic Belt. It is hosted within a 4km long package of middle Ordovician andesitic to basaltic sub-marine volcanic rocks and early Silurian plagioclase and hornblende phyric shoshonitic andesite sub-marine breccias (Crawford 2014, 2017). Revival of the prospect was driven by field mapping armed with a TerraSpec Halo, ground magnetics and 3D IP and magnetic inversions (by Chris Moore, Moore Geophysics). This lead to the recognition of a 3m x 2km surficial dickite ± pyrophyllite ± kaolinite ± illite ± silica ± pyrite alteration in shoshonitic andesite breccias. Follow up drilling which targeted a zone 700m down plunge of the Dobroyde Hill resource was completed in partnership with the NSW Government through the New Frontiers cooperative drill funding scheme. This hole, NDD005, intersected a far larger system than expected, with 280m of intense dickite + pyrophyllite + kaolinite + pyrite ± illite ± silica alteration then 200m of unmistakable carbonate-base-metal-gold epithermal style alteration as presented in Corbett & Leach (1998). Evolution Mining’s giant Cowal Gold Mine (~8M Oz Resource) 120km north of Dobroyde is also characterised as carbonate-base-metal-gold epithermal. Both mineralising styles show a genetic link by overprinting relationships and both having associated broad low-grade gold and silver mineralisation with individual 1m intervals to 9.5g/t gold. NDD005 is interpreted to have stepped over the top of the main epithermal gold zone, hence the target remains open to further exploration. Additionally, this 700m down plunge gap between the new and historic drilling is completely untested and if mineralised could extend the strike length of the deposit to one kilometre.

Modern drilling management system based on field data monitoring

Drilling engineering is technology-intensive and involves many subjects and large amounts of data. To improve the quality of production and management, decisions need to be made based on the latest data to direct the work on-site. Therefore, it is necessary to establish a safe, reliable, and efficient drilling management system that can meet daily production requirements. In this study, we describe a real-time monitoring system of field data. The system comprises real-time collection of borehole drilling parameters, ground drilling parameters, on-site video and borehole position data, and wireless data transmission to site and rear managers. The system is based on real-time monitoring of field data, the recognition and prediction of the conditions inside the borehole, the wireless transmission of data, and rear-base data analysis and feedback modules. The rear managers can view the real-time and historical drilling data at any time and compare and analyze drilling data by using the rear software of the management system to optimize the drilling program and feedback to the site. The application of the management system in production suggests that it can significantly improve drilling efficiency, reduce drilling costs and accidents in wells, and improve the automation of drilling operations. Moreover, at the same time, it can also predict complex conditions and drilling accidents in time and provide reliable real-time data to drilling technicians for on-site decision making.

Research on High Density Oil-Based Drilling Fluid and Application in the Southern Edge of Junggar Basin, China

The southern edge of the Junggar basin has broad exploration potential. However, high-frequency complex drilling accidents in this area lead to the reduction of the average drilling speed and the extension of the drilling cycle. The main geological reason is that this area was affected by the process and developed high and steep geological structure. The nappe formation with a large dip angle and poor stability developed along faults. The major rock type of this E2-3a formation is mud-stone which has strong water sensitivity and can be hydrated and dispersed easily, which leads to the wellbore shrinkage and the borehole collapse. In order to improve the drilling speed in the southern edge of the Junggar basin and accelerate the exploration and development process, the drilling fluids associated with drilling problems in this area were investigated in this paper by combing the geological information and historical drilling records. Because of the special characteristics of this formation, it is concluded that the water-based drilling fluids previously used in this area are not suitable to solve the complex drilling conditions; a high density oil-based drilling fluid system has been developed for this area by conducting studies in the laboratory initially and being tested in the field later. In addition, its rheology, stability and pollution resistance performances were evaluated. Results show that, the rheology, the stability and pollution resistance capacities of the drilling fluid satisfy the drilling requirements. The fluid was applied in well H101 and the results show that the ROP of section 311.1 mm of the well was increased by 763% compared to the wells drilled in the same area and the total drilling time of well H101 was reduced by more than 80%, which was a historic breakthrough of the drilling speed in the southern edge.

Estimating the future supply of shale oil: A Bakken case study

We propose a new way to estimate the supply curve of remaining shale oil reserves in the U.S. Our method applies the principle of “successive sampling without replacement” to derive from historical drilling data maximum likelihood estimates of the number and productivity of remaining drilling sites. Unlike existing techniques, this approach identifies the portion of “technically recoverable” resources that can be developed economically at alternative price levels. For example, we estimate that 50% of remaining technically recoverable resources located in the Bakken play—roughly 8 billion barrels—could be developed economically if the oil price remains near $50/barrel. (L71, Q35, Q41).

Complete wavefield seismic structural, stratigraphic, geomorphic and elastic interpretation in the offshore Browse Basin

The first quantitative interpretation project in the Browse Basin that used complete wavefields from dual-sensor streamer data to characterise a variety of overburden and reservoir seismic structural, sedimentary and geomorphic features is discussed in this extended abstract. Having established that complete wavefield pre-stack angle data are amplitude versus angle (AVA) compliant, the authors analyse the elastic response from thin gas sands in a location where well control predicts a weak gas response in terms of the Vp/Vs ratio and negligible response in terms of the acoustic impedance. Various seismic expressions in the near-surface are better resolved using complete wavefield imaging, including deltaic deposits, potentially prospective patch reefs and intersecting channel systems, and shallow hazards associated with historic drilling failures appear to be resolvable with greater confidence. On the larger scale, the overall data interpretability is substantially enhanced in texture and character by broadband imaging of primary reflections, and then by subsequent reservoir characterisation. Initial (deeper) interpretation focused around mapping of the prospective Early Jurassic Plover Formation and the Early Cretaceous Upper Vulcan Formation, in which evidence of channelisation can be demonstrated on conventional migration volumes and reinforced using complete wavefield migration. Ultra-low frequency signal penetration to the deeper Triassic level has been limited historically, but the first complete seismic wavefield data analysis presented demonstrates that a combination of volume attributes provide substantially improved geologic information from the seafloor to the deepest targets.

Technology Focus: Drilling Management and Automation (September 2015)

Technology Focus Drilling automation is the use of computer-assisted or -controlled devices in drilling a wellbore. It involves a considerable amount of technology, including mechanized and robotized surface equipment and semiautonomous downhole drilling tools; entire drilling systems composed of linked downhole tools, surface control systems, and remote monitoring; and data analytics. It includes both conventional overbalanced drilling and managed-pressure drilling. The economic drivers for automation are increasing complexity, data overload, efficient drilling, and safety, to name a few. Automated systems and equipment for drilling are under development by many, including equipment providers, service companies, and operators. Interested members of these companies have formed a consortium, the SPE Drilling Systems Automation Technical Section, which is promoting open data standards and protocols to exchange quality data in a safe and predictable manner. The group also looks outside the oil industry to learn from the route to automation taken by other industries. It has become clear that, while the technology and infrastructure for drilling automation exist, there are obstacles to commercial implementation. The primary hurdle is transitioning all the technology to the business environment. The many silos of our drilling industry make this technology-transfer problem quite challenging. The tension between technology and business is not new to the oil field or to any industry. You can have the most breathtaking technology, but, if there is no attempt to communicate the need for it, it will simply stagnate and never see the light of day. However, if the business side of the equation can envision the commercial benefits of a technology, the economic pull-through can revolutionize an industry. A means of communicating that vision is to develop a technology roadmap showing the developmental pathway the technology is following. A means of ensuring that all can take advantage of new technology and profit from innovation is to develop open systems using agreed-upon standards. A means of rewarding both developers and users is to implement systems- automation products by use of performance-based business models. One of the interesting developments in the last few years is an emerging understanding of the need to develop the communication infrastructure for a drilling operation. This infrastructure links all facets and players in a drilling operation: downhole, surface, remote, and enterprise. It forms the framework supporting open standards and enables the implementation of modern data analytics, real-time modeling, and control systems. The papers presented here represent a good overview of technology road-mapping of drilling automation, of modeling and simulation critical to automation, of drilling-management processes that make use of easily automated repetitive work flows, and of the value of quality data. The topics are innovative and thought provoking. Enjoy! JPT Recommended additional reading at OnePetro: www.onepetro.org. SPE 172151 Achieving Drilling Excellence Through Next-Generation Work Flows Enabled by Integrating Historical Drilling Data and Real-Time Data by Richard Mohan David, Abu Dhabi Company for Onshore Oil Operations, et al. SPE/IADC 173121 For Better or Worse: Applications of the Transfer-Matrix Approach for Analyzing Axial and Torsional Vibration by Roman J. Shor, The University of Texas at Austin, et al. SPE 173858 Possibilities, Limitations, and Pitfalls in Using Real-Time Well-Flow Models During Drilling Operations by Knut Steinar Bjørkevoll, Sintef Petroleum Research, et al.

Profitability of shale gas drilling: A case study of the Fayetteville shale play

Discussion on shale gas production sustainability raises the question of shale gas well profitability. The study presents a well economics model incorporating key geologic and production features of shale gas. The model is used to demonstrate analytically how profitability of a well may change depending on completion and local geology. We show how wells with the same expected production may have different profitability and, vice versa, how wells with different production profiles may appear to be equally attractive.These conclusions are demonstrated with the empirical analysis based on historical data for almost 4000 horizontal wells in the Fayetteville Shale Play, North Central Arkansas. We look at six productivity tiers across the play accounting for drilling cost variability related to the dramatic depth change (from <1500-ft to over 8000-ft) in the natural gas producing formation. The subdivision of the play into productivity tiers and depth zones accounts for intra-tier profitability variation and helps to explain historical drilling patterns and to predict future development patterns in the field as demonstrated for 2012 by Gülen et al.

Cost analysis of oil, gas, and geothermal well drilling

Abstract This paper evaluates current and historical drilling and completion costs of oil and gas wells and compares them with geothermal wells costs. As a starting point, we developed a new cost index for US onshore oil and gas wells based primarily on the API Joint Association Survey 1976–2009 data. This index describes year-to-year variations in drilling costs and allows one to express historical drilling expenditures in current year dollars. To distinguish from other cost indices we have labeled it the Cornell Energy Institute (CEI) Index. This index has nine sub-indices for different well depth intervals and has been corrected for yearly changes in drilling activity. The CEI index shows 70% higher increase in well cost between 2003 and 2008 compared to the commonly used Producer Price Index (PPI) for drilling oil and gas wells. Cost trends for various depths were found to be significantly different and explained in terms of variations of oil and gas prices, costs, and availability of major well components and services at particular locations. Multiple methods were evaluated to infer the cost-depth correlation for geothermal wells in current year dollars. In addition to analyzing reported costs of the most recently completed geothermal wells, we investigated the results of the predictive geothermal well cost model WellCost Lite. Moreover, a cost database of 146 historical geothermal wells has been assembled. The CEI index was initially used to normalize costs of these wells to current year dollars. A comparison of normalized costs of historical wells with recently drilled ones and WellCost Lite predictions shows that cost escalation rates of geothermal wells were considerably lower compared to hydrocarbon wells and that a cost index based on hydrocarbon wells is not applicable to geothermal well drilling. Besides evaluating the average well costs, this work examined economic improvements resulting from increased drilling experience. Learning curve effects related to drilling multiple similar wells within the same field were correlated.