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Vidma, Konstantin (Schlumberger) | Bremner, Samuel Edward (Schlumberger) | Ziyat, Sophia (Schlumberger) | Choo, Daryl (Schlumberger) | Abivin, Patrice (Schlumberger) | Yusuf, Temiloluwa Iyenoma (Schlumberger)
Abstract Near-wellbore diversion during acid fracturing or matrix acidizing is widely used to improve reservoir coverage and to save time spent on zonal isolation. It is particularly useful in offshore operations where efficiency is crucial. Diversion is typically achieved by dynamic placement of degradable solid particulates into perforations, wormholes, and/or fractures to divert the treatment fluid to understimulated zones. The diverting material must maintain integrity and mechanical strength during the operation before degrading at the downhole temperature in the presence of stimulation fluids. Whereas currently used materials work very well in a wide temperature range, at temperatures below 140°F (60°C), finding an appropriate diverting material that balances the trade-offs between surface shelf-life, stability during treatment, and fast downhole degradation is a challenge. This paper presents a novel low-temperature diverter that pushes the degradable diverter temperature limit down to 70°F (21°C). The new material was deployed in a matrix acidizing job performed on an injector well in the North Sea. Field deployment was preceded by an extensive laboratory testing program to verify diversion efficiency and acceptable degradation. The novel diverter was deployed in a restimulation treatment of a 10-year-old injection well where BHT was reduced to 70°F (21°C) due to long term injection of cold water. An acidizing treatment was designed to incorporate 4 diversion pills of the novel diversion material. All diversion pills were placed without extra operational time or operational issues. All four pills showed an instant pressure response of more than 250 psi as well as a sustained pressure increase of more than 100 psi, providing an indication of effective fluid diversion. The well was switched to injection mode less than 36 hours after the end of treatment without any flowback, providing a tremendous gain in operational efficiency. The post-treatment injection rate increased by 150% for several days, demonstrating significant and fast diverter degradation, despite the low temperature. The injection rate later stabilized at more than twice the pretreatment injectivity. The results demonstrate the viability of the novel low-temperature diverter in wells with BHT of 70 to 140°F (21 – 60 °C).
Summary Reserves estimation is an essential part of developing any reservoir. Predicting the long-term production performance and estimated ultimate recovery (EUR) in unconventional wells has always been a challenge. Developing a reliable and accurate production forecast in the oil and gas industry is mandatory because it plays a crucial part in decision-making. Several methods are used to estimate EUR in the oil and gas industry, and each has its advantages and limitations. Decline curve analysis (DCA) is a traditional reserves estimation technique that is widely used to estimate EUR in conventional reservoirs. However, when it comes to unconventional reservoirs, traditional methods are frequently unreliable for predicting production trends for low-permeability plays. In recent years, many approaches have been developed to accommodate the high complexity of unconventional plays and establish reliable estimates of reserves. This paper provides a methodology to predict EUR for multistage hydraulically fractured horizontal wells that outperforms many current methods, incorporates completion data, and overcomes some of the limitations of using DCA or other traditional methods to forecast production. This new approach is introduced to predict EUR for multistage hydraulically fractured horizontal wells and is presented as a workflow consisting of production history matching and forecasting using DCA combined with artificial neural network (ANN) predictive models. The developed workflow combines production history data, forecasting using DCA models and completion data to enhance EUR predictions. The predictive models use ANN techniques to predict EUR given short early production history data (3 months to 2 years). The new approach was developed and tested using actual production and completion data from 989 multistage hydraulically fractured horizontal wells from four different formations. Sixteen models were developed (four models for each formation) varying in terms of input parameters, structure, and the production history data period it requires. The developed models showed high accuracy (correlation coefficients of 0.85 to 0.99) in predicting EUR given only 3 months to 2 years of production data. The developed models use production forecasts from different DCA models along with well completion data to improve EUR predictions. Using completion parameters in predicting EUR along with the typical DCA is a major addition provided by this study. The end product of this work is a comprehensive workflow to predict EUR that can be implemented in different formations by using well completion data along with early production history data.
Abstract Theia Energy discovered a prospective unconventional hydrocarbon resource in the Ordovician Lower Goldwyer Shale (LGS) located on the Broome Platform of the onshore Canning Basin. The collation, processing, analysis and interpretation of all available regional data culminated in a successful exploration well, Theia-1 (drilled in 2015), which intersected a 230 ft gross oil column between 4,910–5,140 ft (based on slim-hole log and core analyses). Theia-1 recovered continuous core and wireline log data required to analyse and assess the geological properties necessary for a commercially viable shale oil and gas resource and quantify the volumes of hydrocarbons in-place. Petroleum system modelling carried out in the basin confirmed the prospectivity of the LGS and a potential additional mature hydrocarbon resource in the deeper Nambeet Formation some 2,000 ft below the LGS. The Nambeet is believed to exhibit higher maturity and extensive thickness reaching over 2,000 ft across a significant region of the Broome Platform. The Nambeet Formation adds substantial wet gas prospective resources in addition to those already discovered in the LGS. This paper outlines Theia Energy's exploration strategy in the onshore Canning Basin utilizing shale specific play elements from which the early exploration program was designed and assessed following the drilling of Theia-1. Subsequent specialized testing of core and independent expert analysis have confirmed the reservoir quality, charge, completion quality and producibility of the LGS. In particular, proppant embedment and fracture conductivity tests indicate exceptional flow characteristics of the LGS. The abundance of oil and gas prospective resources in the onshore Canning Basin is significant to the northwest region of Western Australia. The establishment of an unconventional petroleum resources industry would bring pivotal increased activity to its vacillating economy which is currently relying on mining, offshore petroleum development and tourism. Whilst the development and export of the resource would substantially add to economic opportunity for the region, the establishment of much-needed infrastructure would kickstart further economic opportunity such as: mining, downstream manufacturing including fertilisers, irrigated agriculture and cattle farming. Plans are under development for the implementation of major renewable energy projects in the region which can co-exist with an unconventional resource project.
Cornelio, J. (University of Southern California) | Razak, S. Mohd (University of Southern California) | Jahandideh, A. (University of Southern California) | Cho, Y. (University of Southern California) | Liu, H-H. (Aramco Americas) | Vaidya, R. (Aramco Americas) | Jafarpour, B. (University of Southern California)
Abstract A physics-assisted deep learning model is presented to facilitate transfer learning in unconventional reservoirs by integrating the complementary strengths of physics-based and data-driven predictive models. The developed model uses a deep learning architecture to map formation properties to their corresponding production responses using a low-dimensional feature space representation. Transfer learning is accomplished by first training the network weights using production data from a mature shale play and combining the learned weights with limited data from a new unconventional field to generate a predictive model. The simulated data provides approximate production predictions for input parameters of the target field, for which the source data may not provide a good prediction. The resulting model has a superior performance to simulation-based and data-driven predictions alone. The results indicate that (1) physics-based simulated data can facilitate production predictions when out-of-range (unseen) input parameters have to extrapolate from data, and (2) transferring the weights learned from the source field to the target field can add valuable information to enhance the prediction performance of the target field. Introduction There has been a significant increase in the development of unconventional reservoirs in recent decades, particularly tight oil reservoirs in the United States. These tight oil formations often have extremely low permeability and are not economically exploitable using traditional drilling and completion techniques used for conventional high permeability reservoirs. Fortunately, due to the advancement in key technologies, in particular hydraulic fracturing and horizontal drilling, these low permeability shale formations can be stimulated to induce the production of hydrocarbons (King, 2010). However, the traditional flow equations that are well documented and studied for conventional wells have not been applied to tight oil reservoirs. Traditionally, the development of conventional reservoirs relies heavily on numerical reservoir simulators (Altman et al., 2020, Aziz et al., 1979). These simulators provide a reliable prediction that assists in decision-making for resource development. They are built using well-studied and trusted physics-based analytical expressions that are solved during the simulation to provide prediction responses. Since these physics-based simulation models are based on analytical equations, they have the advantage of being able to produce a prediction response for any possible range of input variables, and this allows them to easily extrapolate to any range of data. Additionally, simulation models can be run for any combination of input variables and enable the collection of large amounts of simulated data for all possible scenarios. However, the equations used in simulation models are not able to provide dependable predictions for unconventional tight oil resources since the complex physical relation of flow from tight formations and fractures along with the fracture generation is poorly understood. Additionally, there are various components in the field that are not always accounted for when building simulation models (Fung et al., 2016). These limitations make simulation models unreliable to be used to develop unconventional reservoirs.
Shammam, F. O. (Missouri University of Science and Technology) | Alkinani, H. H. (Missouri University of Science and Technology) | Al-Hameedi, A. T. (Missouri University of Science and Technology / American University of Ras Al Khaimah) | Dunn-Norman, S. (Missouri University of Science and Technology) | Al-Alwani, M. A. (Missouri University of Science and Technology)
Abstract Over the past decade, the oil industry witnessed an expansion in the refracturing activates instead of drilling and fracturing new wells. This work aims to test the efficiency of the refracturing treatments by analyzing the post refracturing production trend of wells in the most active shale plays in the United States (Bakken, Niobrara, Marcellus, Permian, Eagle Ford, Barnett, and Haynesville). FracFocus was used to collect data of more than 130,000 wells in the United States completed between 2012 and 2019. In this study, 39 refractured wells (Barnett wells were vertical, Niobrara wells were deviated, and the other shale plays were horizontal) in the created database were further processed by adding their production data to analyze the production data of the refractured wells and test the efficiency of refracturing as a stimulation technique to increase production. In terms of production gain, the results showed that the selected wells in the Eagle Ford shale play yielded the highest production gain from refracturing with a 174% increase of production post refracturing followed by Bakken (160%), Marcellus (133%), Barnett (46%), Niobrara (43%), Haynesville (34%), and Permian (32%), respectively. Overall, the highest production gain from refracturing is achieved during the second month after refracturing and the decrease of production gain starts during the third month after refracturing. On the other hand, the results showed that there are more factors than formation type and perforation length that need to be considered to predict the production response of refracturing as some wells showed a high gain during the first three months after refracturing, while other wells showed a lower production gain during the first three months after refracturing. Moreover, the refracturing operations have shown a production increase in vertical, deviated, and horizontal wells. Introduction Since the oil price drop in 2011, refracturing old wells and producing from shale reserves have become a new trend in the oil industry in the United States. Refracturing operations aim to maximize production through refracturing old fractured wells (Jacobs, 2015). The technology itself is not new and it has been known and active in the United States since the 1970s. However, the process of refracturing horizontally drilled multi-staged wells is a new technology that started to appear in the industry back in 2011 (Dutta, 2017). Since the oil price drop in 2011, refracturing shale reserves started to emerge in the industry due to the size of the unconventional reserves and the economic viability of producing through refracturing (King, 2014). To highlight the economic efficiency of refracturing, when comparing the cost of refracturing an existent well and fracturing a new well in the Eagle Ford, it was found that the cost of producing through a refracture is 1 to 1.5 million dollars, while the profit of producing through a new fracture is estimated to be 2 to 4 million dollars (Fu et al., 2017). Refracturing operations have some drawdowns associated with the availability of data on the surface and their rate of success is determined by many factors (Yanfang & Salehi, 2014). Therefore, it is important to consider all the associated factors of success of a refracturing operation and include a refrac plan in the initial stage of the well development phase to get a high return of investment in a short period (Dutta, 2017). One of the main factors of the refracturing operation success is the formation of the refrac. The refracture formation depends on the pressure distribution around the pre-existent fracture and the cluster spacing between the fracture stages. In some cases, a new fracture would be initiated and reaching more of the un-depleted spots in the reservoir, which dramatically increases the production of the well. However, in other cases, the refracture would be initiated through reopening the initial fracture (Fu et al., 2017). All these factors contributing to the refracture formation can lead to a high level of uncertainty that requires an intensive analysis of data before starting a refracturing operation.
ABSTRACT: Hydraulic fracture height is one of the most difficult parameters to measure yet understanding height growth is becoming increasingly salient in the economic success of unconventional wells in multi-layer structures, particularly for projects with increased well density development. Downhole tiltmeter fracture mapping by passive monitoring of elasto-static microdeformation offers high sensitivity to fracture height. This work aims at presenting a workflow to integrate advanced microseismic analysis and tiltmeter fracture mapping to resolve dimensions of fracture with a non-uniform opening. The algorithms are implemented in a real-time fracture monitoring program which selects the best fit and superposes final-state and transient models on measured micro-deformation. We apply the presented technique to synthetic and field case studies and, for the first time, present transient tilt characteristics using heatmap visualization of slow deformation (tilt waterfall). Our motivation for the present study is to take advantage of the newly developed downhole instruments that convey a combined array of geophones and tiltmeters and can be installed at greater depth and temperature to monitor and evaluate fracture to as hot as 177°C (>12000ft). 1. Introduction Hydraulic fracturing in unconventional reservoirs is a complex process controlled by the pumping parameters, rock mechanical properties, in-situ stress state, and multi-scale discontinuities (e.g., layering and interfaces, faults, natural fractures). Thereby it is poorly characterized by standard models unless discrepancies are resolved by introducing fudge factors (Warpinski et al. 1994). Downhole Tiltmeter Fracture Mapping (DTFM) is a unique technique that measures induced microdeformation near the fracture face and unravels the evolution of the volumetric distribution of fluid-driven fracture during treatment as well as after pumping stops. Fracture height, dip, volume, azimuth, opening, horizontal components, and complexity are among the parameters that impact the tilt response and can be potentially determined by DTFM if enough tiltmeters are located optimally. As depicted in Fig.1, the field deployment of DTFM to monitor the underground operation entails placement of at least one vertical, linear and wireline-conveyed array of tiltmeters in an offset well (Wright et al. 1998b). The array of tiltmeters is conveyed to the same depth range targeted by the treatment well. It is carefully deployed to ensure that enough data can be recorded from above and below the fracture depth. The acquisition unit samples tilt sequentially in time at each tiltmeter normally with a sampling rate of < 5 HZ.
Shammam, F. O. (Missouri University of Science and Technology) | Alkinani, H. H. (Missouri University of Science and Technology) | Al-Hameedi, A. T. (Missouri University of Science and Technology) | Dunn-Norman, S. (Missouri University of Science and Technology)
ABSTRACT: Refracturing old wells instead of drilling and stimulating new wells has become a new trend in the United States due to the oil prices falling in 2011. This work aims to disclose all refracturing activities in the most active shale play in the United States (Bakken, Niobrara, Marcellus, Permian, Eagle Ford, Barnett, and Haynesville) in terms of techniques, candidate selection, fracturing fluid types, and the number of refracs in one well. FracFocus was used to collect data of over 130,000 wells in the United States that were completed between 2013 to the end of 2019. The refractured wells were extracted from the database and the fracturing fluid types were classified as slickwater, linear gel, cross-linked gel, hybrid, and not reported treatments based on the presence of key chemical ingredients. After processing the data, there were over 1200 wells refractured across the most active shale plays in the United States. The results showed the most common fluid type used in refractured wells is hybrid. In terms of shale plays, Niobrara was the most active shale play with over 280 refractured wells followed by Bakken, Eagle Ford, Marcellus, Permian, Barnett, and Haynesville, respectively. Furthermore, the refracturing activities in each well were further analyzed and clustered into two groups; one or two refracs since some wells were refractured more than one time. However, over 95% of the wells were only refractured once. Moreover, refrac candidates can be identified based on the following factors; the original wells' cluster spacing, well spacing, proppant distribution, fracture orientation, production response from initial fracture, reservoir thickness, and permeability. The optimal ranges of the aforementioned parameters were provided to achieve the best results in terms of saving money and providing the best productivity. This will help optimizing future refracturing operations in the United States and all across the world.
Abstract A seven-step workflow to help subsurface teams establish an initial thesis for optimal completion design (cluster spacing, proppant per cluster) and well spacing in emerging / under-explored resource plays is proposed and executed for the Powder River Basin Niobrara unconventional oil play. The workflow uses Rate Transient Analysis (RTA) to determine the parameter and then walks the reader through how to sequentially decouple the parameter into its constituent parts (frac height (h), number of symmetrical fractures achieved (nf), permeability (k) and fracture half-length (xf)). Once these terms were quantified for each of the case study wells, they were used in a black oil reservoir simulator to compare predicted verses actual cumulative oil performance at 30, 60, 90,120 & 180 days. A long-term production match was achieved using xf as the lone history match parameter. xf verses proppant per effective half-cluster yielded an R value of > 0.90. 28 simulation scenarios were executed to represent a range of cluster spacing, proppant per cluster and well spacing scenarios. Economics (ROR and/or NPV10/Net Acre) were determined for each of these scenarios under three different commodity pricing assumptions ($40/$2.50, $50/$2.50 and $60/$2.50). An initial thesis for optimal cluster spacing, proppant per designed cluster and well spacing were determined to be 12’, 47,500 lbs and 8-14 wells per section (based on whether or not fracture asymmetry is considered) when WTI and Henry Hub are assumed to be $50 & $2.50 flat.
Kazak, Ekaterina S. (Lomonosov Moscow State University) | Kazak, Andrey V. (Center for Hydrocarbon Recovery, Skolkovo Institute of Science and Technology) | Bilek, Felix (Dresden Groundwater Research Centre)
Summary In this study, we aim to develop a new integrated solution for determining the formation water content and salinity for petrophysical characterization. The workflow includes three core components: the evaporation method (EM) with isotopic analysis, analysis of aqueous extracts, and cation exchange capacity (CEC) study. The EM serves to quickly and accurately measure the contents of both free and loosely clay-bound water. The isotopic composition confirms the origin and genesis of the formation water. Chemical analysis of aqueous extracts gives the lower limit of sodium chloride (NaCl) salinity. The CEC describes rock-fluid interactions. The workflow is applicable for tight reservoir rock samples, including shales and source rocks. A representative collection of rock samples is formed based on the petrophysical interpretation of well logs from a complex source rock of the Bazhenov Formation (BF; Western Siberia, Russia). The EM employs the retort principle but delivers much more accurate and reliable results. The suite of auxiliary laboratory methods includes derivatography, Rock-Eval pyrolysis, and X-ray diffraction (XRD) analysis. Water extracts from the rock samples at natural humidity deliver a lower bound for mineralization (salinity) of formation water. Isotopic analysis of the evaporated water samples covered δO and δH. A modified alcoholic ammonium chloride [(NH4Cl)Alc] method provides the CEC and exchangeable cation concentration of the rock samples with low carbonate content. The studied rock samples had residual formation water up to 4.3 wt%, including free up to 3.9 wt% and loosely clay-bound water up to 0.96 wt%. The latter correlates well to the clay content. The estimated formation water salinity reached tens of grams per liter. At the same time, the isotopic composition confirmed the formation genesis at high depth and generally matched with that of the region's deep stratal waters. The content of chemically bound water reached 6.40 wt% and exceeded both free and loosely bound water contents. The analysis of isotopic composition proved the formation water origin. The CEC fell in the range of 1.5 to 4.73 cmol/kg and depended on the clay content. In this study, we take a qualitative step toward quantifying formation water in shale reservoirs. The research effort delivered an integrated workflow for reliable determination of formation water content, salinity lower bound, and water origin. The results fill the knowledge gaps in the petrophysical interpretation of well logs and general reservoir characterization and reserve estimation. The research novelty uses a unique suite of laboratory methods adapted for tight shale rocks holding less than 1 wt% of water.
Chan, S. A (College of Petroleum Engineering and Geosciences, King Fahd University of Petroleum and Minerals) | Hassan, A. M (College of Petroleum Engineering and Geosciences, King Fahd University of Petroleum and Minerals) | Humphrey, J. D (College of Petroleum Engineering and Geosciences, King Fahd University of Petroleum and Minerals) | Mahmoud, M. A (College of Petroleum Engineering and Geosciences, King Fahd University of Petroleum and Minerals) | Abdulraheem, A. (College of Petroleum Engineering and Geosciences, King Fahd University of Petroleum and Minerals)
ABSTRACT In this study, we applied machine learning approach to estimate the mineralogical compositions based on elemental data acquired using x-ray fluorescence (XRF) instruments. Artificial neural networks (ANN) was used to develop new models to provide continues profiles of quartz, calcite, and clay minerals using profiles of Na, Al, Si, K, and Ca. Thereafter, the mineral-based brittleness index (MBI) was estimated using the predicted profiles of quartz, calcite, and clay minerals. The obtained results showed that the developed models can provide accurate predictions for the mineralogical profiles and brittleness index, with R of around 0.96. Finally, new empirical correlations were extracted from the ANN models, which can provide accurate and quick estimations for the mineralogical composition. The ANN-based equations were validated using testing data; very acceptable performance was obtained with R2 higher than 0.95. This work therefore will have benefit in obtaining high-resolution mineralogy using XRF data without sending many samples for XRD laboratory measurements. Eventually, the predicted mineralogy can be used to quantify the BI and enable accurate predictions that result in better de-risking strategies and evaluating successful unconventional plays in terms of estimations of source-rock quality, identification of sweet spots, and designing/executing well placement and hydraulic fracturing stages. 1. INTRODUCTION Because of low porosity and insufficient permeability to allow the hydrocarbons flow naturally, hydrocarbons within organic-rich mudstones or referred to as "unconventional” typically extracted by a combination of vertical and horizontal drilling followed by multi-staged hydraulic fracturing. Fracking will increase effective permeability and allows the hydrocarbon to be released and economically produced (Lee et al., 2011; Sone and Zoback, 2013; Dong et al., 2017). Several key parameters were used to evaluate sweet spot as well as designing drilling, completion and stimulation parameters. Therefore, it is important to identify rock compositions and understand the factors affecting their properties, known as brittleness index (BI).