This study presents a numerical modeling of a sodium silicate gel system (inorganic gel) to mitigate the problem of excess water production, which is promoted by high heterogeneity and/or an adverse mobility ratio. A numerical model of six layers was represented by one quarter of five spot pattern with two thief zones. CMG-STARS simulator was used that has the capabilities of modeling different parameters. The gelation process of this gel system was initiated by lowering the gelant's pH, and then the reaction process proceeded, which is dependent on temperature, concentration of the reactant, and other factors. An order of reaction of each component was determined and the stoichiometric coefficients of the reactants and product were specified. The purpose of this study is to develop a thorough understanding of the effects of different important parameters on the polymerization of a sodium silicate gel system.
This study was started by selecting the optimum gridblock number that represents the model. A sensitivity analysis showed that the fewer the number of gridblocks, the better the performance of the gel system. This model was then selected as a basis for other comparisons. Different scenarios were run and compared. The results showed that the gel system performed better in the injection well compared to the production well. In addition, the treatment was more efficient when performed simultaneously in injection and production wells. Placement technology was among the parameters that affected the success of the treatment; therefore, zonal isolation and dual injection were better than bullhead injection. Lower activator concentration is more preferable for deep placement. Pre-flushing the reservoir to condition the targeted zones for sodium silicate injection was necessary to achieve a higher recovery factor. Moreover, different parameters such as adsorption, mixing sodium silicate with different polymer solutions, effects of temperature and activation energy, effects of shut-in period after the treatment, and effects of reservoir wettability were investigated. The obtained results were valuable, which lead to apply a sodium silicate gel successfully in a heterogeneous reservoir.
The use of acid is an important well maintenancetool in removing near wellbore damage to restore a reservoir's natural permeability and represents one of the most economic options in managing base decline. The selection of acid maintenance candidates however can be a complex process, particularly in wells completed across multiple sands, involving many factors both on the surface and subsurface. As a consequence, individual acid maintenance jobs have had a mixed success rate historically, with certain jobs resulting in a lack of response, or worse, higher water production rates and equipment failures.
This paper uses the Wilmington Oil Field, located in southern California, as a case study to examine the typical characteristics associated with low volume acid maintenance success and provides a novel approach using machine learning (ML) algorithms to aid in the screening and selection of future candidates. The developed algorithms, which make use of the open-source statistical software R, is trained based on results from over 500 producer and 3900 injector acid maintenance jobs that were executed at the field and incorporates predictors from the following groupings determined from literature and subject matter experts (SMEs): Production/injection history, Reservoir properties, Acid type and volume, Delivery mechanism, Formation damage, Well completion design, and Surface facility properties. Over 100+ predictor variables were compiled and screened using supervised feature selection to identify those variables providing the greatest explanatory power. A series of machine learning models: Logistic Regression (LR), Support Vector Machine (SVM), Random Forest (RF), and Gradient Boosting Machines (GBM)) were then used in a classification task to successfully predict whether a producer acid maintenance job would be economic.
The logistic regression model ultimately yielded the best classification results (71% prediction accuracy for the producer jobs and 77% for the injector jobs) and proved to be the ML algorithm with the best balance of accuracy, interpretability, and ease of implementation in the field. The model robustness is examined by applying the algorithm outside of the training and test datasets, to acid maintenance jobs executed in 2016-17 and shows similar predictive accuracy. As a result the model is being actively used to automatically screen for treatment candidates among all 700+ producers and 400+ injectors in the Wilmington Field, which are then validated by SMEs before being executed. The overall process has resulted in significant cost savings by both improving the performance of the acid maintenance program and greatly reducing the amount of time spent by technical staff in selecting candidates. These results indicate that ML algorithms can be effective analytical tools not only for ‘big data’ problems (i.e. largen, time series datasets) which are featured heavily in industry literature, but also for smaller datasets thus opening up a variety of potential applications that can be deployed by surveillance teams alongside traditional approaches.
Yong, Li (Research Institute of Petroleum Exploration and Development) | Baozhu, Li (Research Institute of Petroleum Exploration and Development) | Benbiao, Song (Research Institute of Petroleum Exploration and Development) | Weimin, Zhang (Research Institute of Petroleum Exploration and Development) | Qi, Zhang (Research Institute of Petroleum Exploration and Development) | Xiong, Lihui (Research Institute of Petroleum Exploration and Development)
For the same reservoir geological model, different simulation models could be obtained through history match calibration by different engineers. In other words, there are certain uncertainties within the calibrated simulation models. So how to reduce the uncertainty during history matching is still a problem. This paper presents how to quantify the waterflooding uncertainty and reasonably forecast waterflooding performance through reservoir simulation for a large multi-layered sandstone reservoir in Middle East.
Based on the results of detailed geological characterization, dynamic description and parameter uncertainty analysis, three fine geological models are built, which stand for upside model, expected model and downside model. Then parameter sensitivity on waterflooding performance is conducted based on sector model simulation, and waterflooding development strategies are also optimized. The results are firstly applied for the three full field model calibration by reservoir history matching. After that the calibration models are used for waterflooding performance forecast and the performance uncertainty are also quantified.
Take a large multi-layered sandstone reservoir in Middle East as an example. The MU reservoir is still under primary depletion with only 5% recovery currently, and waterflooding is urgent. Firstly, sector models are used for parameter sensitivity analysis and development strategy optimization. Then based on parameter sensitivity analysis results, the three full-field model are all calibrated with good history match. And different model calibration need different parameter adjustment, such as downside model has stronger aquifer support than that of upside model and expected model because of the poorer connectivity. So different models show different characteristics, such as most of west-south flank of MU reservoir are flooded for Downside model, while only some local area and some zones are water flooded for Expected and Upside model. Then waterflooding performance of different development plans are forecasted and compared based on the optimum development strategies and calibrated models. Furthermore, the performance uncertainty are quantified based on the three models.
This paper offers a methodology and a case study of reservoir simulation history matching in order to reduce uncertainty and better waterflooding performance forecast for a large sandstone reservoir in Middle East. Comparison of the three models can help to better understand the reservoir. And the results are valuable for the following development options decision making. It also provides a reference for performance forecast and uncertainty analysis of similar reservoirs.
Identifying, risking, and maintaining subsurface integrity is of critical importance to a variety of geologic subsurface operations including geothermal, oil and gas production (conventional, unconventional, fractured crystalline, heavy-oil fields), mining, natural gas storage, and sequestration of CO2 and hazardous waste. Predicting and mitigating out-of-zone fluid migration includes but goes beyond maintaining well integrity: it relies on technical understanding of top and fault seals, reservoir and overburden deformation, production/injection-induced stress changes, reservoir management, completions design and engineering, hydraulic fracturing/height containment, wastewater disposal, induced seismicity/fracture reactivation, and reservoir monitoring (e.g., geodetic and downhole measurement and interpretation). Subsurface integrity excludes surface facilities and spill response but includes regulations regarding subsurface activities.
In this paper we present and synthesize examples of subsurface containment loss from oil and gas fields that are documented in the open literature. We then discuss common risk areas or themes in subsurface containment geomechanics that are important to subsurface integrity and illustrate with some general examples how some of these could be investigated by using geomechanical models.
Containment of produced or injected fluids within their intended wellbores or geologic subsurface zones in oil and gas fields is widely recognized as a critical part of exploration and production (E&P) activities in conventional and unconventional plays and reservoirs. For example, it is a primary objective while drilling exploration, appraisal, development, and production wells. Maintaining the integrity of wellbores and subsurface geologic elements can potentially minimize drilling and operational risk. Effectively managing injection pressures, volumes, and rates of fluids in producing fields depends critically on adequately defining the geomechanical limits set by geologic elements such as overburden, caprock, top seals, faults, and evolving in situ stress states (including reservoir pressures). Characterization of the mechanical integrity of the subsurface relies upon obtaining baseline measurements including lithology, petrophysical and mechanical properties, pore pressure, and stress state that are best obtained during field appraisal and development, before production begins. Because the consequences of subsurface containment loss to an operator or partner can be significant, including both direct and indirect costs (e.g., clean-up cost, loss of production, and damage to reputation), even for small events, containment-related activities have assumed a larger share of enterprise risk as technologically more challenging fields are evaluated and placed into production .
"Litigation against unconventional gas producers; lessons from the US experience."
Richard M Lightfoot, Casconsult Pty Ltd
In North America, exploration and production of oil and gas from unconventional sources principally shale, but also tight sandstones and coal seams – is more developed than elsewhere in the world. The presence of large shale, tight gas, and coal seam gas reserves has led to exploration throughout the world.
In Australia, the unconventional gas industry is most developed in Queensland, is seeking to expand in New South Wales and South Australia, and is prospective in Western Australia the Northern Territory, and, to a much lesser extent Victoria.
In the light of the US experience, which has included claims of mechanical failures and inappropriate waste treatment and disposal, leading to groundwater contamination, induced seismicity and hazardous fugitive emissions, government and scientific agencies have produced thousands of studies of the perceived benefits and risks associated with the gas.
In each jurisdiction where unconventional gas extractions has been proposed, governments have been developing legislative regimes for resource allocation and for the managing of risks, through statutes, regulations, standard, and codes of practice.
In the USA, landowners and other citizens who believe that unconventional gas extraction has caused damage to land, water, human and animal health, have resorted to ligation seeking to recover damages, principally by bringing tortuous claims in negligence, nuisance and trespass. In some jurisdiction, actions have also been based on strict liability and legislated rebuttable presumptions of liability.
The paper summarises some cases brought in the USA, to identify the basis of the claims and to analyse their outcomes. In particular, claims brought in tort, and the potential for such claims brought in Australia must be considered.
All sections of the Unconventional Gas Industry need to become aware of their continuing responsibilities. Corporations require an intimate knowledge of the law, its interpretation and the need to minimise exposure to financial, environmental and health risks.
Bans or moratoria on hydraulic fracturing are in place or being considered worldwide. In large part, these actions stem from relatively data-free media presentations of risks associated with hydraulic fractions. Our objective is to analyze the influence of media and public perceptions in shaping policy related to hydraulic fracturing and to use this evaluation to provide insight on balancing science with public perception in judging political risks and guiding public policy. By balancing science with public perception, good policy and a social license to operate result. We conducted a literature review of the role of media in influencing public opinion on political issues and then focused the conclusions found in the literature onto the topic of hydraulic fracturing. We evaluated the influence of media, including movies, television, and traditional new outlets, as well as internet sources such as blogs, news aggregators, nongovernmental organization (NGO) campaigns, and social media, and then compared these sources to the influence of published scientific literature in shaping public perception and political and regulatory oversight of hydraulic fracturing. The results of our analysis show that the large disconnect between scientific data and public opinion makes it difficult for elected officials and regulatory agencies to develop well-founded policies that regulate hydraulic fracturing in a manner that is accepted by both the public and industry. Based on these results, our study illustrates that public officials need to balance public opinion with data-rich scientific studies and analysis, and then weigh political risk when crafting legislation and public policy.
Pico, Antonio (Pacific Rubiales Energy) | Aboud, Jesús (Pacific Rubiales Energy) | Parraga, Felipe (Pacific Rubiales Energy) | Martinez, Jose Antonio (Pacific Rubiales Energy) | Lopez, Gonzalo (Pacific Rubiales Energy)
The central region of the Llanos Basin in Colombia has been characterized by an extensional structural style, where the overall fault pattern consists of normal faults oriented approximately N30°E, dipping East. The structures of the oil fields in Casanare Province have been defined by this type of faults. In this work we establish, for the Casanare Province, the existence of compartmentalized structures formed by the junction between N60° E en-échelon faults and N30E normal faults. In this interpretation, en-échelon faults and folds play a major role in oil accumulations. 3D seismic multi attributes, including volume curvature, coherency and ant tracking, were used to reduce the uncertainties associated with the seismic and well data in order to improve geological constraints, in folds, faults and associated fracture zones. As a result, a new strike-slip fault pattern was interpreted, consistent with a wrench zone, as proposed by Wilcox, et al (1973).
Operators of steamflood projects seem to prefer low pressure steam zones in their operations. The difference between steam zone temperature and initial reservoir temperature drives all energy requirements, which are usually the largest single cost in a steamflood project. However, lower steam zone pressure implies lower drawdown available for production. And lower steam zone temperature implies higher oil viscosity and therefore lower oil production rate. The influence of steam zone pressure and temperature on oil production rate is large. Theoretically, the influence on ultimate recovery (residual oil saturation) is moderate to none. Since costs encourage lower steam zone pressure and productivity encourages higher steam zone pressure, there should be an economic optimum.
The rate of change of energy requirements and oil production rate with respect to changes in steam zone temperature and pressure are determined analytically. If the reservoir geology is conducive to gravity drainage, even by a very tortuous path, then low steam zone pressure is highly favored. Lowering steam zone pressure usually comes at the cost of increased withdrawals, so it is important to carefully consider the requirements, consequences, and benefits on a case-by-case basis. A recommended method for this analysis is discussed. Significant project improvement after a pressure reduction has been reported. These production improvements and steam zone pressure in major steamflood projects are discussed.
Operators prefer to keep steam zone pressure as low as possible since pressure and temperature have a one-to-one relationship, temperature level above initial temperature drives all energy requirements (energy for steam zone growth, energy for heat losses, and energy produced and lost from wellbores and pipelines), and energy required for a steamflood project is usually the largest single operating cost. Some documented projects have steam zone pressure lower than tire pressure. A sampling of industry experience is given in Table 1.
In addition to the cost side, there is an incentive to develop as large a steam zone as possible. Several papers show pre-steam and post-steam core analyses with noted oil saturation changes. In Kern River Field, for example, "oil saturation is significantly reduced wherever a steam zone develops and is only slightly reduced in an underlying hot water zone?? (reference 2).
The Inglewood oil field is located along the Newport-Inglewood fault trend of the Los Angeles basin, California. The field has undergone several phases of development since its discovery in 1924. The field’s initial development was based solely on drilling topographic highs and establishing production mostly from the Pliocene zones where the geologic structure was more fully understood. Geologic data during the first 70 years of production consisted of formation tops identified from well logs taken from wells that were drilled to the Pliocene through upper Miocene.
From 2003 to 2006, older, middle Miocene zones have been the target of new development. Results from recently drilled wells indicate that that geologic structure is still a dominant factor in accurately understanding and identifying deeper zones in the field with new reserves. These lower zones are structurally complex reservoirs that present challenges both in characterization and subsequent development. Thirty-six of forty development wells into the lower most zones have been logged with conventional triple combo openhole logging suites and electrical micro-image logs. Information from the image logs has been used to accomplish the following:
This paper presents the results of a comprehensive study to improve our understanding of high-mobility-ratio waterflood (HMRWF) and to improve performance prediction. Published data on heavy-oil water-injection field projects are limited. Several successful HMRWF projects have been reported, and they show significant oil recovery at high watercut. However, the range of reported recovery is large—waterflood recoveries of approximately 1 or 2% to 20% of original oil in place (OOIP) have been reported for similar reservoirs. Higher viscosities result in lower recovery.
Mechanistic studies using fine-scale simulations show that the viscosity (or mobility) ratio primarily controls oil recovery response, and that the recovery is lower at higher viscosity ratios. Further, viscous fingers dominate high-viscosity-ratio floods, and mobile water can significantly reduce recovery. Field-scale simulation results indicate that heterogeneity plays a more important role for a HMRWF than conventional waterfloods. The amount of primary production before the start of the waterflood has a larger effect on incremental oil recovery for high-mobility-ratio floods. Further, highly-correlated, thin, thief zones reduce recovery of HMRWF more severely, and rock wettability (relative permeabilties) strongly influences oil recovery. These results indicate that, in addition to reservoir geology, accurate viscosity and relative permeability measurements are essential for a reliable performance prediction.
Waterflood has been conducted in many high viscosity reservoirs in the past, and several water injection projects in high viscosity reservoirs are ongoing and planned around the world (Oefelein and Walker 1964; Jennings 1966; Roark 1960; Nelson 1976; Woodling et al. 1993; Jenkins et al. 2004; Adams 1982; Edgson and Czyzewski 1985; Kasraie et al. 1993; Smith 1992; Lim et al. 1993; Ko et al. 1995; Etebar 1995; Pallant et al. 1995; Foerster et al. 1997; Yang et al. 1998; Forth et al. 1996; Yao 1999; Hanafy 1999; Cook et al. 2000; Jayasekera and Goodyear 2000; Capeleiro Pinto et al. 2001). However, published data on HMRWF performance is limited and results are sometimes conflicting. Further, it has been postulated that some of the recovery mechanisms might be different (Cook et al. 2000). It is apparent from the literature that our understanding of HMRWF performance is inadequate.
This paper presents the results of a comprehensive study to provide improved insight into mechanisms governing HMRWF and to help to improve performance prediction. The specific objectives were to: (1) evaluate published field data, (2) determine key parameters that govern the process using analytical methods and fine-scale mechanistic numerical models, and (3) quantify the effects of reservoir heterogeneity on HMRWF field performance. Accordingly, the paper is divided into four parts. The first presents a review of published field data. Next, definitions of mobility ratio are examined and a preferred definition is proposed. This is followed by a fine-scaled mechanistic modeling of HMRWF to identify key parameters. Finally, field-scale simulations are conducted to delineate key differences between HMRWF and conventional waterflood.