Day 2 Wed, April 10, 2019最新文献

{"title":"Adaptive Forecasting of Natural Gas Resources, Production, Infrastructure, and Prices","authors":"L. Virine","doi":"10.2118/195232-MS","DOIUrl":"https://doi.org/10.2118/195232-MS","url":null,"abstract":"\u0000 An oil and natural gas producer should continuously analyze industry fundamentals such as supply, demand, storage, transportation, and pricing to make informed operational and business decisions. An oil and gas producer should be able to adapt to frequently changing industry environment by adjusting its operation: increasing or curtailing production, drilling and connecting new wells, obtaining new financing, locking in future natural gas prices, etc. In order to provide an input to the decision-making process, the adaptive management methodology needs to be applied.\u0000 Forecasts of hydrocarbon resources, production, infrastructure, and pricing are very sensitive to technological improvements, pricing changes, new discoveries, and other major events, the impacts of which are difficult to predict. One method to improve the quality of a forecast is to apply adaptive management process. The adaptive management methodology implies assuming supply and demand strategy, creating multiple scenarios for allocating oil or gas demand to different areas or regions, evaluating these scenarios, and performing detailed forecast for selected scenarios. One important step of adaptive management is monitoring of actual drilling and production activities. Based on this information original assumptions can be updated.\u0000 The result of the analysis is production, prices, and infrastructure forecast. The paper presents an example of a production forecast that is generated using adaptive management process.","PeriodicalId":11150,"journal":{"name":"Day 2 Wed, April 10, 2019","volume":"60 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87257252","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Uncertainty Assessment of Burgan Marrat Carbonate Reservoir using Response Surface Modelling to Plan Early-Stage Field Development","authors":"Asrar Al-Shammari, Jeannire Gutierrez, S. Sinha, O. Al-Shammari","doi":"10.2118/194631-MS","DOIUrl":"https://doi.org/10.2118/194631-MS","url":null,"abstract":"\u0000 Burgan Marrat, a deep carbonate reservoir was transferred from exploration to development team for an accelerated production of the newly discovered oil. This multi-billion barrel reservoir is spread over 450 km2, has more than 40 faults, 8 compartments with large variation in oil-water contact and reservoir/fluid characteristics. The objective of this work is to understand the key uncertainties and quantify their impact on the reservoir offtake rate and oil recovery by conducting uncertainty assessment.\u0000 An interdisciplinary team identified the key uncertainty parameters expected to have significant impact on the reservoir development. The range and probability distribution law for each parameter was set considering the uncertainties due to limited measurements or variation in interpretations. A Response Surface Model (RSM) was created to evaluate the uncertainties by using a base dynamic model and applying an appropriate experimental design, which allowed to efficiently study the uncertainty space with a feasible number of simulations. Using the RSM, the primary effects and interaction between parameters were quantified to rank the uncertainties based on their impact on field production.\u0000 Key uncertainty parameters were identified including eight OWCs, six fault transmissibilities, horizontal and vertical permeability multipliers, and porosity multiplier. Latin Hypercube was found to be the appropriate Experimental Design for the study considering 17 parameters and the need of building a reliable RSM that includes interactions between them. The design recommended 155 simulation cases, which were prepared and submitted automatically by the software.\u0000 Multi-time Responses were analyzed qualitatively to identify the top 5 uncertainties having material impact on field production over 20 years considering 6 existing wells and 30 new well locations. The RSM quantitative evaluation showed three parameters (OWC2, OWC4 and OWC1) having a total effect on the response higher than 10%; followed by PERMX and OWC3 with less than 5%. The other 12 parameters have total effects less than 2%, and the interactions effect is less than 0.5% for any interaction between two parameters. Contrary to the intuition, none of the faults proved impact on the reservoir production.\u0000 The results prove very useful to make a right development and appraisal strategy in early life of the reservoir. The new well locations can be ranked and prioritized to optimize the development and effectively appraise the areas with high risks.\u0000 Uncertainty assessment has value throughout the life of the reservoir. However, this study indicates that its application in early life of the reservoir can bring immense value. An uncertainty analysis on the reservoir production helps in decision-making regarding the number of wells and their locations to reach a target production by managing the risks.","PeriodicalId":11150,"journal":{"name":"Day 2 Wed, April 10, 2019","volume":"59 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89080232","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrated Reserves Management Using Portfolio Approach: A Case Study","authors":"M. Al-Bahar, A. Al-Sane, A. Bora, A. Kumar, A. Mendjoge, P. Dhote, Y. Antonevich, M. Back, A. Kassim, David Mason, M. U. Sethi, E. Siddique","doi":"10.2118/194669-MS","DOIUrl":"https://doi.org/10.2118/194669-MS","url":null,"abstract":"\u0000 Management of oil and gas resources and reserves has always been complex process as the company’s portfolio consists of resource and reserves volumes with varying degrees of uncertainty and maturity levels of projects. Some of the hydrocarbon volumes are from resources that are highly uncertain and require technology imprevoments or breakthroughs. However, for strategy formulation of the country/company needs consideration of all hydrocarbon volumes that can generate value in the future. The prioritization of development strategies for its reservoirs based on rigorous technical and economic assessments while protecting the national interests is a challenging task.\u0000 Kuwait Oil Company (KOC) has been using multiple systems for both asset and business planning processes that is not optimized for faster turnaround. The proposed integrated and automated reserves management solution provided a structured environment for systematic economic evaluation and portfolio optimization. It facilitates the visualization of key reservoir parameters delivering full understanding of the forecasted reserves, production and economic potential of the entire company. It indentifies gaps between reserves and detailed development plans based on technical and commercial criteria. By Optimizing the project timing and economics results in reduction of budgetary expences, increase in portfolio revenue and greater confidence for the company. Ranking the investment opportunities helps in allocating resources appropriately amongst different projects in a systemic manner to ensure profitability of the company. This approach provides ease to KOC in modeling complex scenarios and quickly evaluate a wide range of different development strategies catering for risk and uncertainty\u0000 This paper describes current industry challenges in resource and reservoir management, and an integrated approach to reserves, economics and portfolio management envisioned for Kuwait Oil Company (KOC) which will assist in identifying optimal reservoir development options to meet any defined strategic goals. The results and benefits gained after deployment of pilot will also be explained in the paper. This integrated approach for optimization of Asset Action Plans is a unique solution and would prove beneficial for our industry.","PeriodicalId":11150,"journal":{"name":"Day 2 Wed, April 10, 2019","volume":"16 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81698147","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Does Higher Viscosity Improve Proppant Transport?","authors":"Tanhee Galindo","doi":"10.2118/195192-MS","DOIUrl":"https://doi.org/10.2118/195192-MS","url":null,"abstract":"\u0000 The use of high viscosity friction reducers (HVFR) as alternatives to guar-based fluids to improve proppant transport and lessen formation damage has increased rapidly. While several product options are available, the criteria for selection of a product has focused on viscosity at 300 RPM (511s-1) that meets or exceeds that of linear gel fluids. However, there has been limited data available on what the target viscosity should be, how it influences the fluid's ability to transport sand, and the potential for damage to proppant conductivity. This study presents methodology used to screen HVFR's and results on product performance, which identified a need for alternative specifications to viscosity to achieve maximum performance.\u0000 The proppant transport capacity in dynamic conditions was evaluated for twenty-eight commercially available friction reducers and HVFR's in field waters which could have up to 40,000 TDS. A slot flow apparatus was used to mimic fluid flow through a fracture under different shear and flow rate conditions. Viscosity and elasticity measurements were also obtained using an advanced rotational rheometer. For comparison, linear gel and crosslinked guar fluid were also evaluated.\u0000 While viscosity at 300 RPM (511s-1) and more recently high viscosity at lower shear rates, have been used for selection of HVFR's, these parameters alone do not indicate proppant carrying capacity. The authors did not find a correlation between higher viscosity and better proppant transport, rather they propose that too high a viscosity can negatively impact transport. The results provided insight into the effect of flow rate on proppant transport, with some HVFR's that exhibited higher viscosities at low shear, losing their transport capacity at the same low shear. Elasticity testing of those same products suggested that HVFR's have a critical elasticity range at which they will provide optimal performance. Polymer residuals were also evaluated on proppant post-test and compared to traditional linear gels and crosslinked fluids. Results suggested potential for damage if HVFR's are used without breakers. Different viscosity targets should be set when selecting a HVFR and coupled with other testing criteria such as elasticity and dynamic proppant transport.\u0000 This paper provides insight into the need for development of standardized test criteria for HVFR selection. Further testing and screening of HVFR's will help increase the understanding of key factors influencing sand transport and their effect on proppant pack conductivity.","PeriodicalId":11150,"journal":{"name":"Day 2 Wed, April 10, 2019","volume":"296 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76350188","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Empirical Correlations for Quick and Accurate Hydrate Formation Prediction - Which One to Apply?","authors":"A. Khanna, R. Burla, S. Patwardhan","doi":"10.2118/194601-MS","DOIUrl":"https://doi.org/10.2118/194601-MS","url":null,"abstract":"\u0000 Natural gas hydrate formation is a costly and challenging problem for the oil and gas industry. Prediction of hydrates have been carried out through rigorous and laborious solving of mathematical equations called equations of state (EOS) which give accurate results but require appropriate setup and time. Few examples of such equations of state currently used by industry benchmarked software tools include Peng-Robinson (PR), Cubic-Plus-Association (CPA), Soave-Redlich-Kwong (SRK) etc. which more or less provide us with an accurate hydrate stability curve i.e. a pressure-temperature profile for a given composition, which allows us to keep the pressures and temperatures (operating conditions) out of the hydrate stability zone.\u0000 Hydrate stability curves are a function of the composition of the fluid (gas) being produced. Compositional changes in the percentage of C1 to C7+ components of gas, would not only affect the specific gravity, but would also change the hydrate stability curve of the gas significantly.\u0000 Previous studies have been aimed at finding a quick and precise prediction method for hydrate formation, so as to make swift arrangements to counter any chance of flow assurance issue. Different empirical correlations have been developed on the basis of the composition of the gas being produced that take into consideration the pressure and predict the temperature of hydrate formation. Multiple data points, i.e. fluid compositions from different areas/fields are considered and correlations have been developed to fit the hydrate stability zones of these data points which were found through a more accurate equation of state. As the initial data sets for each correlation are different, the possibility of any two correlations giving the correct and same prediction is very low.\u0000 This paper gives an insight into how different empirical correlations like Hammershmidt, Motiee, Makogon, Towler and Mokhtab etc., that have already been derived can be used with better accuracy for a set of different fluid compositions and specific gravities. A sensitivity analysis is done on the performance of each correlation against the accurate hydrate curves found out through the software tool, using different available equations of state. The data points picked here are random and were not included in any data sets adopted for derivation of the correlation.\u0000 Furthermore, the mimicked hydrate curve from this new method is cast against the software simulated hydrate curve for a flow assurance steady state simulation study with two deepwater gas wells with different gas compositions. The results of the study suggest that the use of the imitated hydrate curve through analytical approach works well in predicting the hydrate stability zone. It would also not require any software proficiency, would give quick results and would cost a fraction compared to the state of the art simulators.","PeriodicalId":11150,"journal":{"name":"Day 2 Wed, April 10, 2019","volume":"21 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81849030","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integration of Drilling, Geology and Geophysical Data: Developing High Resolution Predrill Wellbore Stability Model for Ultra-Deepwater Field Development","authors":"Ashutosh Kumar, Jayanta Dutta, N. Bhardwaj, K. Gunasekaran","doi":"10.2118/194683-MS","DOIUrl":"https://doi.org/10.2118/194683-MS","url":null,"abstract":"\u0000 The key objective of this study was to develop a high resolution wellbore stability model for planned highly inclined development wells of an ultra-deepwater field through integrating geological, geophysical, petrophysical and drilling data to design optimized drilling mud weight window.\u0000 This study describes a customized high resolution wellbore stability modelling process for development wells in ultra-deepwater setting, where shale and sandstone have different pore pressure and stress magnitudes. Un-calibrated and calibrated seismic velocities along with offset well data were used to generate the high resolution pore pressure model for the overburden shale section. Laboratory based geo-mechanical tests, petrophysical logs and offset well events were integrated for the estimation of sub surface stresses and rock mechanical properties for overburden shale and sandstone. Subsequently, separate wellbore stability model was built to estimate the shear failure gradient for overburden shale and sandstone.\u0000 This study suggests that the mud weight (MW) window in the overburden is primarily governed by two parameters – (i) sand-shale pressure equilibrium state, and (ii) stress anisotropy. The intervals where the sand and shale are not in pressure equilibrium state (i.e. shale pressure > sand pressure), the minimum MW requirement is defined by either pore pressure or shear failure gradient (SFG) of shale formation. Whereas, maximum limit is marked by fracture gradient of relatively less pressured sand formation. Therefore, in such intervals mud weight window becomes much narrower (~1 ppg) than those intervals where sand and shale is in pressure equilibrium (~1.6 ppg). This study also highlights the increase of minimum MW requirement (SFG) in some intervals having relatively higher stress anisotropy. The minimum MW requirement within the main reservoir section having thin intra-reservoir shale is controlled by the SFG of the sand formation, as strength is lower in the reservoir sand than intra-reservoir shale. Results show the importance of high resolution modelling in order to capture pressure uncertainty, thin sands, sand/shale pressure equilibrium state, stress anisotropy and its effects in defining the optimum mud weight window. Based on analysis, further risk zonation was done to highlights intervals prone to wellbore collapse and mud loss.\u0000 This paper illustrates how the integrated high resolution wellbore stability modeling would help in optimum mud weight planning for highly deviated / horizontal wells to minimize the drilling risks and non-productive time (NPT), especially for challenging field development settings (deepwater, ultra-deepwater, high stress, High pressure High temperature).","PeriodicalId":11150,"journal":{"name":"Day 2 Wed, April 10, 2019","volume":"92 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88122770","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Digital Technology Optimizes Unconventional Well Planning by Integrating Cross-Domain Expertise","authors":"Chukwuka Akpenyi, Zhaoguang Yuan, Daniel D. Carson, Zachary Hebert","doi":"10.2118/195202-MS","DOIUrl":"https://doi.org/10.2118/195202-MS","url":null,"abstract":"\u0000 Traditionally, petroleum exploration and development teams have utilized workflows and software which require single instance installation and cater to domain-specific needs. Design results from one domain would require incorporation into applications of other associated domains to deliver team-wide engineering. This is often time consuming, requiring multiple review meetings and extra administrative effort for the drilling engineer.\u0000 To add to the complexity, whenever iterations or sensitivity evaluations are needed across the entire plan, there is often no simple platform within which all the required processes can be managed, requiring engineering evaluations to be executed across multiple software. An example is hydraulics which is required for mud design, bottom hole assembly (BHA) and bit design, hole cleaning and borehole stability aspects of drilling. Although all these engineering considerations evaluate the same fluid properties, they typically sit on separate engines and are only integrated by criteria and thresholds in the final plan and not through concurrent engineering design.\u0000 This paper presents a new cloud deployed well construction planning solution, that aims to resolve these historical challenges by enabling multiple processes to be connected and executed from a common contextual dataset in a single system. For example, the hydraulics design is coherent across all design tasks which increases planning efficiency and plan quality. The entire solution also integrates across domains, from geology and geomechanics to drilling engineering and service company planning. This coupled with project orchestration, team collaboration and data management provide further productivity gains and cost savings for the entire team.\u0000 This paper summarizes the digital well construction planning solution and provides case study examples of how cross domain experts plan concurrently in a single common system. This approach allows a teamwide focus on planning better wells faster in a single engineering solution. Case studies show how the well planning team was able to improve cross-discipline collaboration between engineering and geoscience as well as interactions with service companies. Overall, the well planning time was reduced significantly, and the reliability of the well design was ensured through the engineering validation of each task. The integrated digital well planning solution proved to be a more cost-effective solution for well planning and ensured the high-quality delivery of drilling programs.","PeriodicalId":11150,"journal":{"name":"Day 2 Wed, April 10, 2019","volume":"19 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84343850","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Elastic Friction Reducer Facilitates Proppant Transport and FR Residual Analysis Provides Insight into Potential Formation Damage","authors":"Liang Xu, J. Ogle, T. Collier, J. French, R. Nichols, Brian M. Simmons","doi":"10.2118/195229-MS","DOIUrl":"https://doi.org/10.2118/195229-MS","url":null,"abstract":"\u0000 High viscosity friction reducers (HVFRs) are an important component of slickwater hydraulic fracturing applications. To continue to treat multiple clusters effectively within longer laterals, even for stages near the toe area, a high molecular weight HVFR polymer, such as polyacrylamide, is commonly used to overcome pipe friction at 1 gal/Mgal or lower. To carry proppant into fractures, it is commonly assumed that the higher viscosity the HVFR yields, the better the proppant transport, necessitating higher HVFR concentrations than 1 gal/Mgal. However, a field study within the Anadarko Basin demonstrates that viscosity is not necessarily the best indicator of how efficient HVFRs carry proppant. Instead, HVFR elasticity might play a more important role during proppant transport.\u0000 Secondly, HVFRs 1 gal/Mgal or higher could potentially plug the proppant pack or form a filter cake on the rock surface, causing formation damage. Although previous laboratory methods to determine potential formation damage exist, results are difficult to correlate with field applications; hence, the conclusions remain elusive. A relatively new analysis procedure yielding improved assessments of residual HVFR concentrations for both flowback and produced waters, which aid understanding potential formation damage after hydraulic fracturing, is discussed.","PeriodicalId":11150,"journal":{"name":"Day 2 Wed, April 10, 2019","volume":"10 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86931689","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Feasibility of Gas Injection in Gas Cap for Decline Management of a Mature Offshore Field","authors":"A. Thapliyal, Sudeb Kundu, Suparna Chowdhury, Deepika Singh, Harjinder Singh","doi":"10.2118/194570-MS","DOIUrl":"https://doi.org/10.2118/194570-MS","url":null,"abstract":"\u0000 Pressure maintenance by gas injection in gas cap is one of the well-established methods for improving the ultimate recovery. Gas injection in the crestal part of reservoir into the primary or secondary gas cap for pressure maintenance is generally used in reservoirs with thick oil columns and good vertical permeability and this process is called gravity drainage. This paper comprises methodology and results of study to evaluate the feasibility of gas injection in gas cap for maintenance of reservoir pressure and to envisage incremental oil gain of a mature offshore carbonate field located in western offshore of India.\u0000 Field has already produced more than 30% oil of its initial inplace volume. Water injection was started after 4 years of production and currently field is producing oil with 90% water cut. After one year of initial production phase the field producing GOR rose to two to three fold of its initial value mainly due to contribution of gas from gas cap. Depletion of gas cap gas made significant adverse impact on reservoir pressure and also fast pressure depletion from crestal part had allowed water breakthrough of injection and aquifer water to oil producers. At this stage to reduce the decline rate of wells for maximizing the future recovery without drilling of new wells and also without extension of existing infrastructure, the injection of gas in depleted small gas cap have been studied.\u0000 In order to evaluate the feasibility of gas injection in depleted gas cap and its overall impact on oil recovery, three aspects were seen. First the optimized quantity of gas injection and its sensitivity along with the number of gas injectors were decided through reservoir simulation. Therefore, suboptimal oil producers falling within gas cap area are chosen for conversion to Gas injectors. Secondly injection gas requirement for the process will be fulfilled partly through the recycling of produced gas and rest from free gas production from another pay of the same field. Finally it is examined that current existing facility of gas compression will sufficiently cater the additional requirement of gas compression. The process will have additional 10 to 11% contribution in future oil production.\u0000 The process of charging gas cap will provide additional support over ongoing water injection leading to a significant additional oil recovery by reducing the oil decline rate.","PeriodicalId":11150,"journal":{"name":"Day 2 Wed, April 10, 2019","volume":"62 10 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77437109","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrated Approach to Evaluate Rock Brittleness and Fracability for Hydraulic Fracturing Optimization in Shale Gas","authors":"M. I. Mohamed, M. Salah, Y. Coskuner, M. Ibrahim, C. Pieprzica, E. Ozkan","doi":"10.2118/195196-MS","DOIUrl":"https://doi.org/10.2118/195196-MS","url":null,"abstract":"\u0000 A fracability model integrating the rock elastic properties, fracture toughness and confining pressure is presented in this paper. Tensile and compressive strength tests are conducted to define the rock-strength. Geomechanical rock properties derived from analysis of full-wave sonic logs and core samples are combined to develop models to verify the brittleness and fracability indices. An improved understanding of the brittleness and fracability indices and reservoir mechanical properties is offered and valuable insight into the optimization of completion and hydraulic fracturing design is provided. The process of screening hydraulic fracturing candidates, selecting desirable hydraulic fracturing intervals, and identifying sweet spots within each prospect reservoir are demonstrated.","PeriodicalId":11150,"journal":{"name":"Day 2 Wed, April 10, 2019","volume":"130 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80139492","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}