Pigging of Once Through Steam Generators (OTSGs) indicated various types of scales, the most predominant of these being silicates of hardness causing ions. It was noted that scaling propensity can potentially go up with higher Steam Quality (SQ) as the reject stream gets concentrated with ions. However, models suggested that there are benefits of higher SQ in enhancing fuel savings (8%) and electricity savings (2%) when SQ was increased by 20%. The challenges of higher SQ were noted in terms of increased scaling tendency and therefore the need for improved softening. In Field D, the service cycle, the backwash cycle, and the brining cycle were optimized leading to a gain in throughput and reduction in salt consumption. Service cycle improvement gained 30 % to 130 % in throughput between two regenerations, backwash cycle improvement by fluidizing the bed to nearly 35% helped gain 10% in throughput, and reduction of brining cycle from 75 minutes to 48 minutes helped reduce salt consumption by 56% without impacting the throughput. In Field B, a six month pilot revealed that shallow shell resins where ion-exchange is more efficient due to inert core (better intra particle diffusion control) can enhance the throughput by 30% - 80% and simultaneously reduce the number of regenerations by 15 – 30%. Resin fouling is still a major challenge to contend with as oil can foul the resin and throughput can decline by 0.5 – 3 folds. In a plant operation, where there are multiple softener and brine vessels, there is a need to optimize them as a system. Reliability, Availability, and Maintainability (RAM) Models are used in Field C to a) Address equipment configuration optimization with impact on capital capacity expansion project scope b) Understand how net softwater delivery capacity was affected by increases in inlet hardness and c) Assess through a comparison scenario, if the large cost of addressing the valve issue in an upstream nutshell filter was worth the lost production opportunity related to unplanned downtime.

This study aims to compare the roles of rock and crude oil in improving recovery by low salinity water injection (LSWI) and, particularly, to explore the significance of micro-dispersion formation in LSWI performance. Core samples and crude oil were taken from two carbonate reservoirs (A and B) in Abu Dhabi. The oil samples were selected such that one of them would form micro-dispersion when in contact with low salinity brine while the other would not. A series of coreflood experiments was performed in secondary and tertiary modes under reservoir conditions. First, a core sample from reservoir A was initialized and aged with crude oil from reservoir A and a core sample from reservoir B was initialized and aged with crude oil from reservoir B. The cores were then swapped, and the performance of low salinity injection was tested using rock from reservoir A and crude from reservoir B, and vice versa. For the first set of experiments, we found that the crude oil sample capable of forming micro-dispersion (we call this oil "positive", from reservoir A) resulted in extra oil recovery in both secondary and tertiary LSWI modes, compared to high salinity flooding. Moreover, in the secondary LSWI mode we observed significant acceleration of oil production, with higher ultimate oil recovery (12.5%) compared to tertiary mode (6.5%). To ensure repeatability, the tertiary experiment was repeated, and the results were reproduced. The core flood test performed using "negative" crude oil that did not form micro-dispersion (from reservoir B) showed no improvement in oil recovery compared to high salinity waterflooding. In the "cross-over" experiments (when cores were swapped), the positive crude oil showed a similar improvement in oil recovery and the negative crude oil showed no improvement in oil recovery even though each of them was used with a core sample from the other reservoir. These results suggest that it is the properties of crude oil rather than the rock that play the greater role in oil recovery. These results suggest that the ability of crude oil to form micro-dispersion when contacted with low salinity water is an important factor in determining whether low salinity injection will lead to extra oil recovery during both secondary and tertiary LSWI. The pH and ionic composition of the core effluent were measured for all experiments and were unaffected by the combination of core and oil used in each experiment. This work provides new experimental evidence regarding real reservoir rock and oil under reservoir conditions. The novel crossover approach in which crude oil from one reservoir was tested in another reservoir rock was helpful for understanding the relative roles of crude oil and rock in the low salinity water mechanism. Our approach suggests a simple, rapid and low-cost methodology for screening target reservoirs for LSWI.

New water treatment facilities in the Gulf of Mexico include a seawater Sulfate Removal Unit (SRU) to mitigate reservoir souring and scaling. The general industry sulfate target for offshore SRU is usually 20 mg/L or even 40 mg/L; however, some facilities may require <10 mg/L of sulfate in injection water, which makes water quality monitoring more critical and challenging. Current industrial practice relies on only pressure drop and a constant cleaning interval frequency to perform SRU maintenance which may result in reduced membrane life due to frequency cleaning or severe membrane fouling without the capability to predict fouling based on process conditions. The machine learning techniques applied will fill the gap and deliver a prediction model based on both simulation and real-time field data. This model will track and monitor the system key performance indicators (KPIs) including pressure, membrane fouling factor (FF), permeate sulfate concentration etc. The monitoring and prediction of these KPIs provide estimates on when the next maintenance procedure is required, track membrane system status for troubleshooting and actions, and optimize membrane performance by tuning operation conditions.

Matrix acidizing is a common but complex stimulation treatment that could significantly improve production/injection rate, particularly in carbonate reservoirs. However, the desired improvement in all zones of the well by such operation may not be achieved due to existing and/or developing reservoir heterogeneity. This paper describes how a new flow control device (FCD) previously used to control water injection in long horizontal wells can also be used to improve the conformance of acid stimulation in carbonate reservoirs. Acid stimulation of a carbonate reservoir is a positive feedback process. Acid preferentially takes the least resistant path, an area with higher permeability or low skin. Once acid reacts with the formation, the injectivity in that zone increases, resulting in further preferential injection in the stimulated zone. Over-treating a high permeability zone results in poor distribution of acid to low permeability zones. Mechanical, chemical or foam diversions have been used to improve stimulation conformance along the wellbore, however, they may fail in carbonate reservoirs with natural fractures where fracture injectivity dominates the stimulation process. A new FCD has been developed to autonomously control flow and provide mechanical diversion during matrix stimulation. Once a predefined upper limit flowrate is reached at a zone, the valve autonomously closes. This eliminates the impact of thief zone on acid injection conformance and maintains a prescribed acid distribution. Like other FCDs, this device is installed in several compartments in the wells. The device has two operating conditions, one, as a passive outflow control valve, and two, as a barrier when the flow rate through the valve exceeds a designed limit, analogous to an electrical circuit breaker. Once a zone has been sufficiently stimulated by the acid and the injection rate in that zone exceeds the device trip point, the device in that zone closes and restricts further stimulation. Acid can then flow to and stimulate other zones This process can be repeated later in well life to re-stimulate zones. This performance enables the operators to minimise the impacts of high permeability zones on the acid conformance and to autonomously react to a dynamic change in reservoirs properties, specifically the growth of wormholes. The device can be installed as part of lower completions in both injection and production wells. It can be retrofitted in existing completions or be used in a retrievable completion. This technology allows repeat stimulation of carbonate reservoirs, providing mechanical diversion without the need for coiled tubing or other complex intervention. This paper will briefly present an overview of the device performance, flow loop testing and some results from numerical modelling. The paper also discusses the completion design workflow in carbonates reservoirs.

This paper will focus on a new system for separation of water in downhole horizontal wells. The advantages with the system are related to the fact that the water produced from the well is not lifted to the surface, but re-injected into suitable parts of the reservoir, either for pressure support or for diposal. The method of water separation and re-injection has been evaluated for oil producing fields. The paper presents details of the technical solutions and analysis done related to the financial analysis/payback. The mechanical design is basically a main pipe section of a few meters of length, with a special geometry utilizing gravity-based separation. A technical and economic analysis of a downhole processing plant (DPP) using a horizontally installed water/oil separator has been performed. The Improved Oil Recovery (IOR)part has been analysed with a relevant flow simulation tool. Based on the given reservoir depth/pressure, flow rate, viscosity/density and water cut, the simulations show that a significant improved production rate/income can be achieved by extracting the produced water downhole and performing re-injection into the producing reservoir to maintain reservoir pressure. In addition, the expected lifetime of the well is increased by several years. The conclusion is that the earlier the separator is installed, the greater the total well income. In addition, details regarding not only multi-lateral wells through level 5 junctions but also production string with separator and valve system has been evaluated and is concluded to be feasible for the well in question The removal of water downhole has several advantages, for example the removal of the water column up to the surface will reduce the reservoir back pressure and will improve recovery /production rates. In addition, not lifting the water will reduce energy consumption/CO 2 footprint, and removal of water will reduce surface processing and possible re-injection and chemical treatment cost. In general, water separation downhole is advantageous, due to the higher pressure.

Preformed particle gels (PPGs), a type of hydrogel, have been widely applied to control the conformance of reservoirs owing to their robust gel chemistries. Traditional PPGs are polyacrylamide-based hydrogel compositions which can withstand neither higher temperatures nor high salinity conditions. There are many deep oilfield reservoirs worldwide which demand PPG products with a long term hydrolytic and thermal stability at the temperatures of higher than 120 °C. Current PPGs neither remain hydrated nor retain polymer integrity at these temperatures. A unique high temperature-resistant hydrogel composition (HT-PPG) was developed with exceptional thermal stability for greater than 18 months in North Sea formation temperature (~130 °C) and formation water environments. HT-PPG described herein can swell up to 30 times its initial volume in brines of different salinity for North Sea. The effects of salinity and temperature on swelling, swelling rate, and rheological behavior was studied. These HT-PPGs exhibit excellent strength with storage modulus (G’) of over 3,000 Pa at the swelling ratio of 10. Thermostability evaluations were performed in North Sea brines with variable salinity at temperatures of 130 °C and 150 °C and found to be stable for 18 months with no loss of molecular integrity at the higher temperature. Laboratory core flooding tests were conducted to test its plugging efficiency to fracture. HT-PPGs showed good plugging efficiency by reducing the permeability of open fracture and did not wash out during waterflooding. Overall, HT-PPG is a novel product with excellent hydrothermal stability that make it an ideal candidate for conformance problems associated with reservoirs of high temperature and salinity conditions.

In this study, Layer-by-Layer (LbL) assembled polyelectrolyte multilayered nanoparticles were developed as a technique for targeted and controlled release of enzyme breakers. Polyelectrolyte multilayers (PEMs) were assembled by means of alternate electrostatic adsorption of polyanions and polycations using colloidal structure of polyelectrolyte complexes (PECs) as LbL building blocks. High enzyme concentrations were introduced into polyethyleneimine (PEI), a positively charged polyelectrolyte solution, to form an electrostatic PECs with dextran sulfate (DS), a negatively charged polyelectrolyte solution. Under the right concentrations and pH conditions, PEMs were assembled by alternating deposition of PEI with DS solutions at the colloidal structure of PEI-DS complexes. Stability and reproducibility of PEMs were tested over time. This work demonstrates the significance of PEMs as a technique for the targeted and controlled release of enzymes based on their high loading capacity, high capsulation efficiency, and extreme control over enzyme concentration. Entrapment efficiency (EE%) of polyelectrolyte multilayered nanoparticles were evaluated using concentration measurement methods as enzyme viscometric assays. Controlled release of enzyme entrapped within PEMs was sustained over longer time periods (> 18 hours) through reduction in viscosity, and elastic modulus of borate-crosslinked hydroxypropyl guar (HPG). Long-term fracture conductivity tests at 40℃ under closure stresses of 1,000, 2,000, and 4,000 psi revealed high fracture clean-up efficiency for fracturing fluid mixed with enzyme-loaded PEMs nanoparticles. The retained fracture conductivity improvement from 25% to 60% indicates the impact of controlled distribution of nanoparticles in the filter cake and along the entire fracture face as opposed to the randomly dispersed unentrapped enzyme. Retained fracture conductivity was found to be 34% for fluid systems containing conventional enzyme-loaded PECs. Additionally, enzyme-loaded PEMs demonstrated enhanced nanoparticle distribution, high loading and entrapment efficiency, and sustained release of the enzyme. This allows for the addition of higher enzyme concentrations without compromising the fluid properties during a treatment, thereby effectively degrading the concentrated residual gel to a greater extent. Fluid loss properties of polyelectrolyte multilayered nanoparticles were also studied under static conditions using a high-pressure fluid loss cell. A borate-crosslinked HPG mixed with nanoparticles was filtered against core plugs with similar permeabilities. The addition of multilayered nanoparticles into the fracturing fluid was observed to significantly improve the fluid- loss prevention effect. The spurt-loss coefficient values were also determined to cause lower filtrate volume than those with crosslinked base solutions. The PEI-DS complex bridging effects revealed a denser, colored filter cake indicating a relatively homogenous dispersion and properly sized particles in the filter cake.

Information from dual-zone drill-stem tests (DSTs) and vertical interference tests, especially between oil and water zones, is very valuable for reservoir characterization under dynamic conditions. Despite the critical information that can be gathered for field development decisions, it is also an uncommon test type at a DST scale because of the advanced downhole test string design and operational complexity. This paper describes the objective-driven test design for a multi-layered carbonate reservoir and how the test sequence was modified in real-time to increase the value of information. An unconventional multi-zone well test with flexible on-demand control functionality was executed to resolve vital reservoir uncertainties for field development, including vertical interference between zones, individual zone characteristics and to confirm reservoir boundaries. Reservoir simulations were performed to decide the test sequence to create interference between different reservoir layers, while considering other test objectives, simultaneously. A DST string with wirelessly-activated downhole tools and flexible control options allowed to modify the test program on the fly, based on real-time data analysis and performance of each zone. One of the zones was also tested and characterized without flowing fluids to surface by making use of real-time downhole data. This complex, unorthodox well test operation was chosen to resolve multiple reservoir uncertainties in a single DST run, which would have normally required multiple different DSTs. Operations included flowing different zones individually, including acidizing operations, and the sequence was monitored and modified on the fly to maximize the value of data. Vertical interference between oil and water zones were also monitored to determine test conditions. Reservoir simulation studies helped choose the optimum test sequence to create the required interference by avoiding any disturbance in the interference data from other pressure transients during the test. During the test, downhole and surface testing data was transmitted to town in real-time and analyzed by the petro-technical team to guide the operational procedures. Downhole equipment was controlled wirelessly by acoustic commands to change the test design, depending on the data analysis. This thick carbonate formation was tested pre- and post-acid, to evaluate stimulation efficiency. Also, by testing the well at different flowrate and pressure conditions, information regarding future production well behavior was obtained. A low-pressure water zone was also tested without bringing fluids to surface, using a type of closed chamber test which was made possible by analyzing real-time downhole data from different depths. Multiple crucial objectives for field development decisions were planned and successfully obtained using an engineered DST string design. The confirmed reliability of complex DST string and wireless telemetry in difficult environment enabled well test efficiency gains to solve multiple challenging dynamic reservoir evaluation problems, simultaneously. These novel solutions bring new types of data and information to the exploration and appraisal teams to answer connectivity questions in a cost and time effective manner.

Traditional Microbial Enhanced Oil Recovery (MEOR) technology assumes the oil recovery is increased by the biosurfactant generating by the subsurface bacteria. However, we identified that increased recovery factor is mainly contributed by stimulating the indigenous bacteria to plug the preferred waterflooding channels, which was proved at laboratory and some high-permeable oilfield, but never implemented in the waterflooding of tight oilfield. This paper presents a comprehensive study on Bio-diversion technique by stimulating indigenous bacteria covering lab research and filed operation lasting 18 months. The lab research comprised: (1) feasibility research using modified recipe and field sample on the stimulation of indigenous microorganisms; and (2) Evaluation of effectiveness of the stimulation based on lab results. A field pilot, consisting of 10 injectors, 10 producers, injecting and producing from multi-zones, reservoir temperature is about 160 F, permeabilities range from 30 md to over 100 md, daily water injection rate is about 2,000 BWPD, pre-treatment water cut is over 90%. It is observed that the water cut has decreased from 98% to 80% gradually (3-6 months after injection). Besides, the water injection index test indicates that the injection profile becomes more evenly after 9 months of microbial nutrient injection because the stimulated bacteria reduce the permeability of more permeable zones and reduce the permeability heterogeneity in the vertical direction. Sharing the field results with the industry may inspire the operators to consider one alternative environmentally friendly and cost-effective approach to increase the recovery factor of tight oil reservoirs. From the technical viewpoint, the field pilot proves that the major mechanisms of MEOR is sweeping the unswept oil by injecting the microbial nutrient to the reservoir to stimulate the indigenous bacteria to block the preferred waterflooding channels.

There are mainly two types of solids in the oil field waters; Suspended Solids (SS) and Total Dissolved Solids (TDS). While it is easy to remove SS from water, removal of TDS requires the application of advance filtration techniques such as reverse osmosis or ultra-filtration. Because these techniques cannot handle high volumes of the oilfield waters with high TDS content, produced waters originated from hydraulic fracturing activities cannot be treated by using these advance technologies. Thus, in this study we concentrated on the pretreatment of these waters. We investigated the feasibility of the Coagulation, Flocculation, and Sedimentation (CFS) process as pretreatment method to reduce mainly SS in Produced Water (PW) samples. We collected samples from 14 different wells in the Permian Basin. First, we characterized the water samples in terms of pH, SS, TDS, Zeta potential (ZP), Turbidity, Organic matter presence and different Ion concentration. We tested varying doses of several organic and inorganic chemicals, and on treated water samples we measured pH, TDS, SS, Turbidity, ZP and Ions. Then, we compared obtained results with the initial PW characterizations to determine the best performing chemicals and their optimal dosage (OD) to remove contaminants effectively. The cation and anion analyses on the initial water samples showed that TDS is mainly caused by the dissolved sodium and chlorine ions. ZP results indicated that SS are mainly negatively charged particles with absolute values around 20 mV on average. Among the tested coagulants, the best SS reduction was achieved through the addition of ferric sulfate, which helped to reduce the SS around 86%. To further lessen SS, we tested several organic flocculants in which the reduction was improved slightly more. We concluded while high TDS in the Permian basin does not implement a substantial risk for the reduction of fracture conductivity, SS is posing a high risk. Our study showed, depending on components of the initial PW, reuse of the pretreated water for fracturing may minimize fracture conductivity damage.

Enhancing oil recovery from thick heterogeneous carbonate reservoirs poses great challenges, be it through waterflooding or gasflooding. In this study, a three-layer 3D physical model was established based on artificial core technology and scaling criteria, taking into account the mineral composition, petrophysical properties, pore structure, wettability, heterogeneity, dynamic, bottom aquifer, interlayers, and well pattern. Experiments were carried out under circumstance of high temperature and high pressure. A numerical simulation model incorporated with local geological characteristics was built for subject well-area unit. The development process and ultimate oil recovery of conventional water injection, gas-assisted gravity drainage (GAGD), edge-bottom water injection (EBWI), and a method of combination of GAGD and EBWI proposed in this paper, named CGE were studied. For this kind of reservoirs, the experiments showed that, oil recovery of GAGD and EBWI were 40.01% and 37.11%, respectively, higher than conventional waterflooding process, while CGE had the most potential with oil recovery 43.85%. The numerical simulation showed that, oil recovery of CGE was 49.87% and the water cut was extremely low in the first 11 years. GAGD significantly increased Bond Number and had strong water control ability, but it relied on the pressure accumulation, thus there was a non-effective period. EBWI had no obvious non-effective periods, and thus enhancing oil recovery in the early stage through forced gravity displacement. CGE is a feasible and efficient combination development method, although there is still a problem of water control in the later stage. In addition to the research of EOR methods, this paper also helps broaden the means of researching carbonate reservoirs and design more schemes, based on the successful implement of the experiments.

High water cut is a serious problem for mature oilfields in China. Water injection paths are intersected with each other, injectors and producers are distributed in a more and more complicated pattern, while low-productivity layers are more focused. Conventional zonal water injection technologies require repetitive operation with wirelines and cables, causing extensive tests and low efficiency. However, an intelligent zonal water injection string consisting of several preset cable packers, water injection pressure gauges, formation pressure gauges and downhole flow meters has simply optimized water injection parameters and efficiently developed all reservoirs in some China's mature oilfields. Horizontal drilling and extended reach well drilling technologies are developing by high speed, we are faced by more critical borehole conditions, which has brought more challenges to water adsorption testing of horizontal intervals and deployment of zonal water injection instruments. Compared with vertical wells, the water adsorption test and string running are more challenging for horizontal wells, in which we are faced by many a problem during zonal water injection, such as competitive slack off and tight pull, excessive or inadequate water injection, complicated operation process, etc. There are several common challenges arising from zonal water injection, such as tight pull, slack off and repetitive operation. A full set of wireless intelligent water injection string for horizontal wells has been proposed. Based on pressure pulse water distribution technique, the water injection string is eligible for multi-stage adjustment, so it is possible to finalize testing, adjusting, injection, measurement, downhole data collection as well as automatic error correction in one run during water injection. A dedicated trial shows that integration of remote wireless control and artificial automation may is applicable, as packers are set securely and released easily, in order to adjust opening of each water injection nozzle on the ground. Therefore, this completion and water zonal water injection string enables precise water injection by means of data remote control. The first trial was accomplished in Ghawar Oilfield, Saudi Arabia, showing acceptable results. Integration of remote wireless control and artificial automation requires a wireless water injection string that combines testing, adjusting, injection, measuring and data collection in one trip, providing us with adequate downhole data. Thus, the complete water injection process for each zone is precisely monitored and controlled on the ground.

Foam stability primarily determines the efficiency of foam induced conformance control especially when fractures exist in formations. In this work, a well-defined nanocellulose fibrils (NCF) strengthened CO 2 foam (NCF-st-CO 2 foam) was proposed aiming to improve the conformance of tight formations with fractures. The bulk characteristics of NCF-st-CO 2 foam including foamability, foam stability and texture were thoroughly investigated in a high-pressure and high-pressure (HT-HP) cell. Afterward, foam flow in fracture models was simulated intending to correlate the generated differential pressure with the parameters of foam quality, fracture aperture and fluid velocities, which helped to understand the foam generation, propagation and mobility in fractures. The capacity of this foam in controlling conformance and improving oil recovery in a fractured core was finally evaluated. Conventional CO 2 foam (without NCF) was used as the reference throughout this work. The results indicated that the addition of NCF into CO 2 foam considerably retarded the liquid drainage and bubble coalescence, which consequently stabilized the CO 2 foam especially in the presence of crude oil. NCF-st-CO 2 foam presented dense bubbles and a thick framework as observed visually from the cell. The flow behaviors of CO 2 foam in fractures were largely determined by the bulk foam stability. NCF-st-CO 2 foam could be generated in-situ (aperture from 0.5 mm to 5.0 mm) and then properly propagate throughout the fractures at a low mobility without any plugging issues. In core flooding tests conducted on the model with fracture aperture of 0.5 mm, the NCF-st-CO 2 foam injection exhibited a delayed breakthrough, which finally led to an incremental oil recovery of 8.6% OOIP after conventional CO 2 foam treatment. These results demonstrated the promising potential of NCF-st-CO 2 foam in conformance control in tight formations.

The Greater Kuparuk Area, located on the North Slope of Alaska, began production in 1981 and has produced over 2.5 billion barrels to date. The area contains six oil fields flowing into three central processing facilities with 47 drillsites and over 1,200 production and injection wells. The facilities are primarily gas constrained due to limits from the gas lift compressors, and secondarily water constrained due to injection pump capacity. An optimization program using the equal slope concept is currently in use for lift gas allocation. A previous attempt to more rigorously optimize the production system using commercial software resulted in better lift gas allocation, but computation time lead to the cessation of its use for daily optimization. The objective of this work was to develop a fast, flexible optimization model that recommends well status, lift gas rates, and water injection rates. The model uses field data and data generated by the previous surface models to develop the hydraulic models as well as current facility conditions and constraints. The model contains four components. The first was a function that estimates producer and injector performance. The second is a function that gathers and interpolates well performance models with physics-based models. Third, the drillsite header pressures were estimated using a neural network. Finally, a genetic algorithm is used to search for the optimal well status, lift gas rate, and water injection rate for each well. Connections were made to databases to run the model using field conditions at any time over the last five years. The hydraulic model for three phase flow utilizes a neural network, whereas a simpler linear based model is used for the water injection system. The hydraulic model was rigorously back tested using field data over a two-year period with weekly model retraining. Drillsite header pressures deviated 6 psi on average from actuals, which is on par with commercial software. The optimization converges in under 90 seconds in a single facility optimization run. The recommendations from the optimization program are expected to increase oil rate 1.5% in the existing system. While production optimization using genetic algorithms and neural networks has been presented for over 20 years, there are not many, if any, known industry applications of optimizing the production and injection networks simultaneously using neural network models. The program was written in Python and deployed on cloud computing. The tool is used to calculate daily net oil benefit per well, prioritize shut-in wells when the facility is constrained, and optimize injection pumps and drillsite configurations. Additionally, the model is designed to accept new engineer-specified source wells to understand the impact of backout when developing new projects. Overall, the model has provided a platform for engineers to make optimization decisions in a complex, interdependent system.

While the industry is actively looking to increase efficiency, mitigate and remediate outcomes of extractive practices, there is a shift in requirement for the license to operate – from sustainability (balancing harm) to regeneration (giving more than taking). The sustainability phase continuum can be described as making moves from recycling to sustainability to regeneration. Movement through the phases may be thought of in terms of doing less harm to the planet (everything in it and on it) to giving more than taking from the planet. By mapping activities to specific phases, a representative picture of key current and potential areas/technologies for regenerative industry practice could provide mechanisms and strategies for evolving sustainability/regenerative enterprise strategies. The key takeaway: Improving resource efficiency efforts through nature-based solutions and regeneration of social and environmental conditions will materially increase positive impacts including lower carbon footprints.

An innovative technology called Data Physics* , which combines the predictive capacity of traditional numerical simulators with the speed and flexibility of machine learning, was applied to optimize a mature waterflood in the Neuquen basin in Argentina. A reservoir model was built by combining machine learning techniques with the partial differential equations of fluid flow as applied in conventional reservoirs simulatiors. The approach is probabilistic in nature, thereby supporting the quantification of uncertainty. Given the complex conditions of operation and control in secondary recovery projects, the dearth of data, which was inherently noisy, it is not feasible to define a unique deterministic solution. The proposed approach provides physically possible and statistically viable distributions (ranges and frequencies) of the variables affecting reservoir behavior. Due to its predictive capabilities, the reservoir model, created at a layer level using raw uninterpreted production and injection data, is capable of reproducing and predicting field production history. This enables continuous closed loop optimization and provides a program of injection water redistribution. The result is optimized production, and reserves development with reduced injection costs. As part of the assessment of different prescriptions, the operator wanted to evaluate the optimum way to cycle two sets of injectors to reduce water handling and injection costs. A robust connectivity model was built from the reservoir model which was then used to evaluate and compare the different alternatives to cycle injectors during two years versus an optimum injection redistribution. The results include production forecasts for the scenarios evaluated which, when executed, would allow the customer to reduce water cost while maintaining production levels unaltered.

The objective of this paper is to structure a data-driven-based workflow to design and optimize alkali-surfactant-polymer flooding ( ASP ) projects. Various objective functions from the techno-eco perspectives are considered to obtain comprehensive optimum ASP slug formulations and injection operation schemes. Several universal multi-layer neural networks ( MLNN ) are trained and they act as surrogate models of high-fidelity numerical simulation models to evaluate the objective functions involved in the optimization workflow. The input parameters considered by the machine-learning workflow include the reservoir rock and fluid properties, ASP slug formulation, and project design parameters. A physical equation of state, HLD - NAC equation, is employed to model the microemulsion phase behavior of the crude oil/brine/surfactant system. The validity of the surrogate models is confirmed via extensive blind testing applications with error margins of less than 5%. Thus, the MLNN can be employed as an expert system to assess the response functions of the ASP injection processes, including oil recovery, water cut reduction, pressure responses, etc. A hybrid global optimization workflow is structured by coupling the expert MLNN systems with particle swarm optimizer ( PSO ). Comprehensive techno-eco-assessments are carried considering the oil recovery, chemical slug utilization ratio (incremental oil production per unit mass of chemical additives), and project economics as objectives. This paper presents case studies to illustrate the robustness of the proposed workflow in optimizing the ASP injection projects considering multiple objective functions. The optimization work focuses on the design of ASP slug formulations and injection patterns. A sensitivity analysis is carried to investigate the trade-off factors between pairs of the objectives. Objective functions exhibiting a strong trade-off relationship can be included to structure Pareto front solutions, which enables the optimization workflow to find various optimized ASP formulations and injection schemes. The outcomes of this work not only provide field operators with various options to implement ASP injection processes but also generate stochastic assessments of the optimized objectives. This work develops a universal proxy model that is competent to generalize the microemulsion phase behavior that occurs in the ASP injection processes. The trade-off relationship amongst the critical objective functions is investigated via a rigorous sensitivity analysis using the proxy models. With the help of the developed model, the decision-makers can design ASP injection projects based on various project preferences. Moreover, the project risks can be understood by observing the stochastic outcomes of the optimized objective functions.

Casabe is a multilayer field (20 reservoirs distributed in 3 formations) characterized high heterogeneous nature, limited sand continuity, unfavorable mobility, and high sediment production due to a poor consolidation of the reservoir. The ongoing waterflooding process has a well defined five-spot pattern where injection wells have selective strings installed, and production is commingled. Under these conditions, shut-in wells for reservoir pressure acquisition are challenging activities with high operational risks related to compromised mechanical integrity and sediment production. Likewise, the commingled production scheme affects the deconvolute pressure data process and promotes crossflow effects leading to inconsistent results. Finally, stoping the well involves production loss and disruption in waterflooding balance. The reservoir pressure is a critical requirement to run an analytic optimization methodology implemented in 2017. Casabe had proven that selective injection string offers a unique opportunity to acquire quality reservoir pressure data by reservoir unit using the Downhole Dummy Pressure Sensors (DDPS), overcoming all the above issues when acquired in producers. This paper presents how a waterflooding optimization methodology coupled with a quality reservoir pressure acquisition enhanced reservoir surveillance by triggering actions to optimize the waterflooding volumetric balance, thus, reaching a production-injection system stabilization. This enhancement changed the area production decline trend and allowed to contact more zones and produce oil from constrained layers.

The La Cira-Infantas (LCI) oilfield was discovered and put in production in 1918. After a traditional reservoir depletion stage, a water flood (WF) operation was started in 1958. Redevelopment began in 2005 as a joint venture between Ecopetrol and Occidental (Oxy) using a combination of workovers, infill drilling, WF optimization, and other IOR/EOR methods. The field has been redeveloped using an average 20 to 25 acres per WF pattern, which were either inverted 5-spot or 7-spot configurations. Since 2005, selective completion strings were installed with side pocket mandrels controlling the vertical distribution and volume of water injected with each mandrel covering a group of sand layers. The selective completion was successfully implemented, and provided a significant boost in oil production. The field has multiple opportunities to increase oil production. Before performing these solutions, it was important to understand the producer-injector connectivity across the entire field. The capacitance resistance model (CRM) provided some insights on the interwell connectivity within the reservoir between injectors and producers, however it is difficult to correlate the CRM simulation results with multiple geological interpretations and reservoir characterizations using geostatistics. This paper presents a WF surveillance program with a focus on incremental oil recoveries from multiple stacked-sands. The injection and production profiles were very useful in improving WF conformance. The water injection profile was measured with a rigless tracer string. The production profile was initially estimated using petrophysical properties and fractional flow curves due to the difficulty of running a production logging tool (PLT) from every pumping well in complex multilayer reservoirs. It was important to validate the production profile with a couple of PLT pilot wells. In these pilot wells, we employed a Y-tool for a connection with the electric submersible pump (ESP) on one side; and the other side of the Y-tool served as a pass through for the PLT. The production and injection profiles provided insights for injector-producer well correlations between productive sand layers. Based on the well data, reservoir simulation models were created and have added value to our reservoir surveillance program, significantly increasing oil production, WF sweep efficiencies, and incremental oil recoveries in the mature LCI WF oil field.

This workflow evaluates reservoir souring risk for a deepwater development, taking into consideration dynamic reservoir characteristic effects over time, and incorporating detailed flow modelling of the system to assess H 2 S partitioning effects and to determine their design and operational impact. The objectives are: Showcase an integrated multi-domain approach to souring modeling from reservoir to facilities, provide a reservoir souring modeling workflow applicable to new and existing offshore waterflooding projects, and present a case study in which this workflow was successfully implemented at two distinct points of (pre-first oil and after eight years of production)of an existing development This unique workflow takes a holistic approach to reservoir souring prediction. This process may be implemented either pre-first oil or during field production in order to optimize souring mitigation strategies and operations, such as sulfate removal and nitrate injection. If the evaluation is to be undertaken before production operations, data will be more limited, however, this methodology has proved to still be effective in determining the risk associated with souring for that particular reservoir. All aspects of the system are considered: reservoir fluid characteristics, reservoir static and dynamic models, production system thermo-hydraulic and produced fluids thermodynamic performance, and the critical subsea and topsides design considerations. The workflow has been proven to simulate the souring process, the growth and respiration effect of SRB leading to H 2 S formation in the reservoir, as well as the biological reactions related with the injection of nitrate to inhibit these phenomena for a series of conditions using the latest modeling tools available. The approach helped understand a complex set of bio-chemical reactions involved in the production of H 2 S and its potential inhibition to avoid reservoir souring in a particular field. A sensitivity analysis using the integrated special reservoir simulation model was able to predict the effectiveness of nitrate injection and has also been used to guide the design phase, while supporting the subsequent optimization of the mitigation strategy supportbased on the evaluation of actual production data. The comprehensive modeling approach employed considers for variation in biological system characteristics, reservoir conditions, and hydrodynamics of the production system that affect the production of hydrogen sulfide. Production of elevated levels of H 2 S can generate material integrity issues including corrosion, health and safety issues, and loss of hydrocarbon value, since high H 2 S contents will reduce the monetary value of produced oil or gas. The field case study presents souring models calibrated and validated with actual data collected from the production streams during eight years of history and a set of sensitivity scenarios were analyzed to consider uncertainties in various simulation parameters. The results show that the dosage of calcium nitrate injected in this instance successfully controlled SRB growth and that no reservoir souring was detected. However, the application of the developed workflow allowed the operator to optimize the current Calcium Nitrate dosage, enabling a considerable reduction in the injection rate, which represented a key factor for operational costenabling subsequent operating expenditure reductions. The value added with this workflow, during waterflood management using seawater injection, allows operators to timely and clearly determine reservoir souring behavior and anticipate potential risks associated with it. The findings are also useful for supporting major design and operational decisions, including the development and optimization of souring management and mitigation techniques.