Improved completion design and field development strategies have provided commodity price resilience by sustained efficiency gains across most major US Shale plays. This rapid evolution in completion practices, however, has created behind pipe opportunities. Refracturing offers a viable solution to maximize on these opportunities, however, its effectiveness is dependent on a variety of factors. The present paper explores the implementation of refracturing as a re-development strategy in legacy shale plays and evaluates it as a truly multivariable problem.
The paper takes into consideration petrophysical parameters, initial completion design, chemical composition, formation quality, time from original completion, refrac completion design and production performance to quantify impact on refrac KPIs such as IP ratio, EUR ratio, decline trend impact, amongst others. The paper does this by using an ACE (alternating conditional expectation) non-linear regression model that incorporates the KPI’s as response variables and utilizes the transforms of a wide range of input variables to identify cause and effect relationships. By running this analysis across multiple legacy shale plays, including the Haynesville, and Barnett, the paper provides best-practices to maximize refracturing success.
While refrac can offer a viable solution in obtaining incremental production, depending on the basin, a refrac can be a tenth of the expense of a new well and can beneficially impact the production from the existing well. In most cases, the analysis found EUR predictions improved by 30% - 200%. While correlations varied across basins and completion design, an inverse correlation was found between refrac KPIs and initial frac intensity.
Although, refracturing in horizontal shale wells is a well-established practice, a significant amount of analysis on their performance is focused on one or two key variables. The present paper adds to the existing body of literature by using data analytics and machine learning to evaluate this strategy from a truly multivariable standpoint. The paper also provides best practices to evaluate and predict refrac performance to de-risk refrac as a field re-development strategy.
In the past ten years, hydraulic fracturing technology and strategies have made major improvements in the operational efficiency and economic performance of shale well completions. Much of this advancement was derived in the past three years as a response to the global downturn in oil and gas commodity pricing. Mature shale plays across the United States have a surplus inventory of horizontal wells employing highly inefficient completions styles. Amid the low oil pricing environment, operators in the Bakken and Eagle Ford were capable of revitalizing these prior generation wells with great success through re-fracturing programs. In many cases, production of these re-fractured wells rivaled the production of newly drilled and completed shale wells both in terms of initial production post re-fracture as well as extended interval cumulative production. These re-fracturing programs allowed producers to achieve tremendous gains in production while minimizing drilling activity. Although re-fracturing began as a highly economical method to improve production during a time of depressed oil pricing, it is still being used today to improve the production of additional wells recognized as top-tier candidates.
By developing a specific set of criteria to select wells for re-fracturing, these programs can be successfully employed in the Appalachian Basin to improve the economics of gas wells, mitigating the effects of highly discounted natural gas pricing. After the explanation of well candidacy, an economic sensitivity analysis was implemented to illustrate the impacts a strong re-fracturing program could make for operators in the Northeast through a comparison of public data showing production and total reserves for both in and out-of-basin re-fracturing programs. Additionally, while this paper focuses on re-fracturing as it relates to shale formations it also includes information as to how re-fracturing relates to conventional formations.
After looking at the incremental economics of re-fracturing programs implemented in shale plays across the United States and in-basin data, the impacts of gas well re-completion can be fully quantified and understood through the application of probabilistic modeling. Additionally, this modeling further delineates re-completion candidacy by identifying which wells pose higher risks in economic metrics.
Very little information has been published regarding the impacts a re-fracturing program could have in the Appalachian Basin. As the field matures, the topic of re-completions will become increasingly important, and this analysis will allow operators to have a greater understanding of the impacts of refracturing shale gas wells in the Northeast.
Production data and analytical models derived from coupling the linear flow in the reservoir and the linear flow in hydraulic fractures were used in this study to optimize fracture spacing for maximizing productivity of shale oil and gas wells through refracturing. This study concludes that productivity of multi-fractured horizontal wells is inversely proportional to the fracture spacing. The shortest possible fracture spacing should be used to maximize well productivity through refracturing. This supports the practice of massive volume fracturing where as many as perforation clusters with the shortest possible spacing are used for pumping massive proppant into the created hydraulic fractures. Production data analysis indicates that the multi-fractured horizontal oil and gas wells could have higher productivity if they were fractured with less perforation cluster spacing. Mathematical model analysis implies that reducing the cluster spacing from 70 f t t o 15 f t t h r o u g h r e f r a c t u r i n g c a n d o u b l e d w e l l p r o d u c t i v i t y, w i t h t h e M i n i m u m Re q u i r e d C l u s t e r S p a c i n g (MRCS) determined by well completion constraints (packers, perforation clusters, and casing couplings). Result can be checked for fracture trend interference on the basis of analyses of pressure transient data or production data.
Application of horizontal drilling and hydraulic fracturing technique has made development of shale gas reservoir successful in the United States during the past decade. Chasing its operational success, researchers have been studying to understand the fundamentals of shale gas production, which will provide valuable information to assist in optimization of shale reservoir development. Unfortunately, the mechanism of shale gas production has not been fully revealed so far, and most reservoir simulation models are adopting the mechanism of coalbed methane production to forecast shale gas development process, which might not be the real case.
In this paper, instead of using numerical simulation model, artificial intelligence and data mining techniques are implemented to study the controlling factors of shale gas production and understand the impacts of reservoir, completion and stimulation parameters in a dynamic manner only according to the field data. A database of Marcellus shale reservoir is generated by integrating information such as well locations, well trajectories, reservoir characteristics, completion, hydraulic fracturing, and production parameters, etc. Neural network models are trained to learn the key performance impacting factors on shale gas production in a dynamic manner, which could assist reservoir management decisions.
With maturing oil fields there is an increasing focus on improving the oil recovery factor and pushing the envelope toward a 70% target. This target is indeed very challenging and depends on a number of factors including enhanced oil recovery (EOR) methods, reservoir heterogeneities, displacement efficiency, and reservoir sweep. Other factors also play a role including vertical sweep due to flow behind the casing, well integrity issues, presence of conductive faults, or fractures. Proper surveillance performed to evaluate the injectant plume front, reservoir conformance, well connectivity, assessment of the integrity of wells, and other factors can be crucial for the success of the project and its future development.
The paper discusses special downhole logging techniques including a set of conventional multiphase sensors alongside high precision temperature (HPT) and high-definition spectral noise logging (SNL-HD). It was run to provide complete assessment of the injection – production distribution and any associated well integrity issues that might impair the lateral sweep of injectants into the target layer. This will be done for an injector and producer pair near the wellbore area. The operation was carried out with a tool string that contained no mechanical parts and was not affected by downhole fluid properties. It was conducted under flowing and shut-in conditions to identify flow zones and check fracture signatures. It also provided multiphase fluid velocity profiles.
The results of the survey allowed for in-depth assessment of borehole and behind casing flow, confirming lateral continuity, and provided an assessment of production-injection outside the pay zone. Results will allow for better well planning and anticipation of possible loss of well integrity that might impair production in the future. Combining the behind casing flow assessment with borehole multiphase flow distribution can be used for production optimization by sealing unwanted water contributing zones.
Khedr, Sherine (BP Exploration Operating Co) | El-dabi, Fady (BP Exploration Operating Co) | Nashaat, Mohamed (BP Exploration Operating Co) | Mohiuldin, Ghulam (BP Exploration Operating Co) | Galal, Alaa (BP Exploration Operating Co) | Slim, Teddy (BP Exploration Operating Co) | Hughes, Andrea (BP Exploration Operating Co) | Morris, Lyndsay (BP Exploration Operating Co) | Ramsay, David (BP Exploration Operating Co) | El-wakeel, Wael (BP Exploration Operating Co) | Mubarak, Hussein (BP Exploration Operating Co) | Smith, Jeffrey (BP Exploration Operating Co) | Munger, Robert (BP Exploration Operating Co)
Giza Fayoum Completions was the second campaign of the West Nile Delta project. The campaign consisted of eight cased-hole gravel pack subsea wells. The Giza Fayoum campaign was sanctioned in August 2017 with an execution start date five months later. In this time, the well designs were finalized, downhole completion equipment manufactured, and the execution plan approved. A high rate water pack sand control technique was designed to deliver an estimated production rate of 120 MMscf/d / well. It was planned to deliver eight wells over a period of 5 months from Q1 2018 giving an average of two and a half weeks per well. Seven of the eight wells were cleaned up through a large bore completion landing string system. Each well was flowed to high rate temporary well test equipment installed on the DP semi-submersible rig to a gas rate of 65 MMscf/d, with PLT logs conducted.
This successful, fast-paced campaign is the result of applying lessons learned from the former campaign; Taurus Libra and identifying additional efficiencies that would improve performance. The design similarities between the two campaigns permitted the team to extend the learning curve and deliver superb performance on Giza Fayoum.
As for safety performance, the campaign was delivered without any lost time incident. A rigorous approach to continuous improvement resulted in reducing the completion time to 12 days per well (not including rig move, de-suspension and suspension activities). The optimized bean up procedures supported by PLT data made it possible to reduce greenhouse emissions by 20%. The sand control technique resulted in a significant reduction of total skins. Moreover, the team succeeded in delivering the wells safely, ahead of plan and under budget while adhering to BP's overarching strategy of delivering safe, compliant and reliable wells.
The efficiencies, safety culture and technology used during this campaign are now being set as the standard for future campaigns in Egypt and beyond.
Descriptive Analytics is the first step of a three-step data-driven analytics workflow used for managing and optimizing completion, production and recovery of shale wells. The comprehensive data-driven analytics workflow for the unconventional resources is called Shale Analytics (
Shale Descriptive Analytics takes into account seven categories of field measurements;
Two conclusions have been achieved as the result of this study.
This paper describes a trial project to evaluate autonomous inflow control device (AICD) technology to better manage water production in a large heavy oil field in Colombia. The Cajua block is part of the Rubiales field is in the Llanos basin of Eastern Colombia, and has reserves estimated at 7.5 billion barrels. One of the main production challenges is the high water cut, or BSW, driven by strong aquifer flow in the underlying sands of the Carbonera formation. Many wells experience early water break-through and must be produced above 95% BSW for long periods of time. Horizontal wells typically produce up to 8000 barrels per day of total fluid with electric submersible pump (ESP) on cold production, and do not utilize any thermal recovery methods. The loosely-consolidated sandstone reservoir has variable water saturation and permeability, which has continuously frustrated operators'’ attempts to manage water production ever since the Rubiales field was first brought online in the 1980's.
In late 2018, a three well pilot project was initiated to evaluate the ability of inflow control technology to manage water influx at the sandface of the horizontal completions. Three wells in the Cajua block were equipped with AICD screens and swellable packers to evaluate oil production and water cut. The AICD technology works by limiting water inflow based on fluid viscosity. Each segment, or compartment, of the horizontal wellbore is isolated by swellable packers, and the AICD creates a higher or lower drawdown on the reservoir depending on the fluid properties, favoring the inflow of high-viscosity heavy oil over the low-viscosity water.
The early production results show that AICD completions can effectively manage water production by delaying water break-through and restricting water inflow from the reservoir. Each of the three trial wells responded positively to the autonomous ICDs, allowing engineers to produce heavy oil wells more effectively with lower cumulative water volumes.
This project marks the first implementation in South America of AICD technology with rate-controlled production (RCP) valves to manage water production in a heavy oil field. It is also the second application worldwide, after Canada, to show that AICDs can effectively to manage water cut in a heavy oil, cold-production scenario.
Alshmakhy, Ahmed (Abu Dhabi National Oil Company) | Al Daghar, Khadija (Abu Dhabi National Oil Company) | Punnapala, Sameer (ADNOC Onshore) | AlShehhi, Shamma (ADNOC Onshore) | Ben Amara, Abdel (Silverwell Energy) | Makin, Graham (Silverwell Energy) | Faux, Stephen (Silverwell Energy)
Majority of the world's gas lifted wells are under-optimized owing to changing reservoir conditions and fluid composition. The gas lift valve (GLV) calibration is required with changing conditions. Apart from that, an allowance needs to be kept so that the valve change remains valid for longer time. Compounding this, when adjusting gas lift parameters, it was not easy for the gas lift operator to make data-driven decisions to assure continuous maximized production. These challenges are further amplified with dual completion strings: fluctuating casing pressure; unpredictable temperatures due to the proximity of the two strings; and inability to individually control the injection rates to each string. String dedicated to the formation with lower productivity and reservoir pressure tends to "rob" gas from other string. Operating philosophy in such cases end up producing from one string. Production optimization in such cases requires frequent intervention with attendant costs and risks thus presents an opportunity to re-imagine gas lift well design.
ADNOC in collaboration with Silverwell developed a Digital Intelligent Artificial Lift (DIAL) system, which consists of multiple port mandrels to be placed at GLV depths. These mandrels are connetced to the surface operating system with a single electrical cable. The ports can be selectively opened or closed by sending an electric signal from the surface unit. In addition, pressure and temperature sensors are also placed which help record these parameters in real time. Such a system enables the choice of depth, injection rate, loading and unloading sequence controlled from the surface. Realtime optimization is possible as pressure/temperature data helps draw accurate gradient curves. This system makes gas lift optimization possible in dual gas lift wells.
It has been estimated that this technology delivers a production increase approaching 20% for single completion wells, and exceeding 40% for dual-string gas lifted wells. Recognizing this opportunity, a business case and implementation plan were developed to pilot a dual-string digitally controlled gas lift optimization system.
This paper will describe, the screening phase, business case preparation, risk assessment and validation process, leading to this 1st worldwide implementation of a fully optimized dual completion gas lifted well. Implementation plan of novel digital gas lift production optimization technology in an onshore dual completion well. The completely original approach increases safety, efficiency, operability and surveillance.
Al-Alwani, Mustafa A. (Missouri University of Science and Technology) | Britt, Larry K. (NSI Fracturing) | Dunn-Norman, Shari (Missouri University of Science and Technology) | Alkinani, Husam H. (Missouri University of Science and Technology) | Al-Hameedi, Abo Taleb T. (Missouri University of Science and Technology) | Al-Attar, Atheer M. (Enterprise Products)
The goal of any hydraulic fracturing stimulation is to design and execute the appropriate treatment that is best suited for the stimulated reservoir. Selecting the best treatment must achieve the desired fracture geometry to maximize long-term well productivity and reserve recovery. The main objective of this study is to conduct detailed short and long-term production and well-to-well comparisons of the different types of fracture stimulation fluids in the Marcellus Shale play.
A database of more than 4,000 wells was integrated for this study. The wells were divided into four groups: water, gel, cross-linked, and hybrid fracs. Chemical data from FracFocus were gathered and processed then coupled with completion and production data to investigate the gas short and long-term production. Detailed monthly production data for the participating wells were captured from DrillingInfo database and utilized in this study.
This paper reports and compares the Marcellus gas initial production, the gas cumulative of the first month, first 6 months, first year, 2 years, and 5 years. The well productivity is tied to each hydraulic fracturing fluid type. The paper provides insights into the different completion trends in the Marcellus as well as the variations in stimulation parameters such as the volume of stimulation fluid and the amount of pumped proppants. The completion aspects of perforated lateral length are also taken into consideration and a comparison of the normalized production and stimulation parameters is also presented. The study shows that water fracturing fluids outperformed the other types of hydraulic fracturing fluids.
This paper introduces several data processing workflows that serve as a reference for individuals who are interested in mining and processing FracFocus database. It also documents the change in hydraulic fracturing fluid types and measures the effects of the fracturing fluid volume and total proppant pumped on the initial and cumulative production.