Well#1 was completed as horizontal oil producer with Openhole Stand-Alone Sandscreens (OHSAS) across a thin reservoir with average thickness of 20ft in Field B. The first Autonomous Inflow Control Device (AICD) in PETRONAS was installed to ensure balanced contribution across horizontal zones with permeability contrasts and to prevent early water and gas breakthrough. Integrated real-time reservoir mapping-while-drilling technology for well placement optimization combined with industry-leading inflow control simulator for AICD placement were opted. The early well tests post drilling showed promising results with production rate doubled the expected rate with no sand production, low water cut and lower Gas to Oil Ratio (GOR). Reservoir Management Plan (RMP) for this oil rim requires continuous gas injection into gas cap and water injection into aquifer. However, due to low gas injection uptime caused by prolonged injection facilities constraints, the well's watercut continued to increase steadily from 0% to 80% within a year of production despite prudent surveillance and controlling of production during injector's downtime. After the gas injection performance has improved, the well was beaned up as part of oil rim management for withdrawal balancing. Unfortunately, a month later, the production rate showed a sudden spike with significantly low wellhead pressure, followed by hairline leak on its choke valve and leak at Crude Oil Transfer Pump (COTP) recycle line. Sand analysis by particle size distribution (PSD) confirmed OHSAS failure, while the high gas rate from well test results confirmed AICD failure. A multidisciplinary investigation team was immediately formed to determine the root cause of the failure event. Root Cause Failure Analysis (RCFA) method was opted to determine the causes of failures, including the reanalyzing of the OHSAS and AICD completion design. The well operating strategy was also reviewed thoroughly by utilizing the well parameters trending provided in the Exceptional Based Surveillance (EBS) Process Information (PI) ProcessBook. Thorough RCFA concluded that frequent platform interruptions and improper well start-up practices have created abrupt pressure changes in the wellbore, which has likely destabilized the natural sand pack around the OHSAS and created frequent burst of sand influx across AICDs. The operating of a high gas-oil ratio (GOR) and high watercut sand prone well without pre-determined AICD sand erosion toleration envelope have also likely contributed to the failure of AICDs. The delay in detection of OHSAS failure in Well#1 due to ineffective sand monitoring method thus resulted in severe sand production which caused severe leak at its choke valve and COTP recycle line.

As recognized as the most economical and effective measure to increase carbonate oil and gas well production, matrix acidising is widely used. The main feature of acidising and the key influence factor of increasing production is what kind of acid etched wormholes can be formed. The actual etched wormholes grow in disorder and randomly, that's why it is extremely difficult to describe by classical mathematical methods. Due to the lack of a quantitative calculation model for the growth law of acid-etched wormholes, penetration depth, competition and distribution patterns among different etched wormholes, an effective method for acidising parameters optimization cannot be formed. The stimulated production of different wells vary greatly. In order to establish the corresponding quantitative calculation model for geometric size of acid etched wormholes, three-dimensional competitive distribution of different wormholes, and production prediction, also to achieve the quantitative optimization of treatment parameters for different wells and improve oil and gas production, firstly, we designed and completed indoor core etched experiments and CT scanning technology to obtain the true three-dimensional morphology of linear acid etched wormholes. Besides, the radial wormholes in 14 cubic feet of super large cores were proven to meet the requirement of fractal. The fractal dimensions of these two wormhole types were also obtained. Furthermore, a quantitative calculation model for the wormhole length expansion was established. Secondly, according to the mathematical model of extending competition among different acid etched wormholes, the fractal distribution law of the length of wormholes in the vertical direction is obtained. Combined with the fractal wormhole length calculation model, a method to solve the dual fractal model by calculating the maximum wormhole length is given. Finally, the classic acidised production rate calculation model was revised. The influence of the three-dimensional expansion length and distribution of wormholes on the skin factor was considered in detail. The sensitivity of key acidising parameters, such as acid strength and pumping rate, was also analyzed. The results show that both the linear wormholes obtained from conventional cores and the radial wormholes obtained from super-large cores can be described by fractal geometry. The fractal dimension corresponding to the optimal pumping rate is 1.46-1.63. Considering the dual-fractal distribution of acid-etched wormholes, the skin factor is larger than that of the conventional equalization model. This is mainly due to the fact that the equalization model only uses the maximum length of the wormholes. This also explains why wells or layers with negative skin factors can still increase production rate after uniform acidising. At the same time, for a specific layer, there is a better acid strength and pumping rate. With these parameters, the acid consumption and predicted production rate are better, which provides a theoretical basis for the quantitative optimization of acidising treatment parameters.

Tight gas reservoirs are widely distributed in China, which occupies one-third of the total resources of natural gas. The typical development method is under primary depletion. However, the recovery of tight gas is only around 20%. It is necessary to explore a new technique to improve tight gas recovery. Injecting CO 2 into tight gas reservoirs is a novel trial to enhance gas recovery. The objective of this work is to verify and evaluate the effect supercritical CO 2 on enhancing gas recovery and analyze the feasibility of CO 2 enhance gas recovery of tight gas reservoir. Taken DND tight sandstone gas reservoir in North China as an example, 34 wells of DK13 wellblock were chosen as CO 2 Enhanced gas recovery pilot area with 10-year production history. Six injection scenarios were studied. Numerical simulation indicated that the recovery of the gas reservoir of DK13 well area was improved by 8-9.5 percent when CO 2 content of producers reaches 10 percent. The annual CO 2 Storage would be 62 million cubic meters (110 thousand tons) and the total CO 2 storage would be around 800million cubic meters (1.5 million tons). After the environmental parameter evaluation of injectors and producers, the anticorrosion schemes were put forward and the feasibility evaluation and schemes of facilities were presented. The analysis results indicated that DK13 wellblock was suitable for CO 2 enhanced gas recovery no matter geologic condition, injection & production technology and facilities. However, under the current economic conditions, DK13 wellblock was not suitable for CO 2 to enhance gas recovery. However, if gas price rise or low carbon strategy implement, the pilot test could be carried out. In brief, CO 2 could be an attractive option to successfully displace natural gas and decrease CO 2 emissions, which is a promising technology for reducing greenhouse gas emission and increasing the ultimate gas recovery of tight gas reservoirs. This economic analysis, along with reservoir simulation and laboratory studies that suggest the technical feasibility of CSEGR, demonstrates that CSEGR can be feasible and that a field pilot study of the process should be undertaken to test the concept further.

Many fields in South East Asia are suffering from sand production problems due to sensitive sandstone formation. Sand production increases with time and increasing water production. The production of sand induces loss of production, due to sand accumulation in the wellbore, and heavy operational costs such as frequent sand cleaning jobs, pump replacements, replacement of surface and downhole equipment, etc. An original sand control technology consisting of polymers injection and already deployed in gas wells, has been successfully tested in an offshore oil well. The technology utilizes polymers having a natural tendency to coat the surface of the pores by a thin gel-like film of around 1 µm. Contrary to the use of resins which aim at creating a solid around the wellbore, the polymer system maintains the center of the pores fully open for fluid flow, thus preserving oil or gas permeability while often reducing water permeability (a property known as RPM for Relative Permeability Modification). The advantage of such system is that the product can be injected in the bullhead mode and often, a reduction of water production is observed along the drop in sand production. In gas wells, the treatment lasts around 4 years and can be renewed periodically. A lab work was undertaken to screen out a polymer product well suited to actual reservoir conditions. We conducted bulk tests to evaluate product interaction on reservoir sand samples, and corefloods to evaluate in-situ performances. Treatment volume and concentration were determined after lab test. One of "Oil Well" candidate is located in Arjuna Field, offshore Indonesia. Downhole conditions are: Temperature = 178°F, salinity = 18000 ppmTDS, permeability = 140-300mD, two perforated intervals with total thickness of 67ft (ft-MD) with 38 ft Average Netpay Thickness, production rate = 800 bfpd. The well is under gas lift and needed to be cleaned out every 3 months because of sand accumulation. Polymer treatment was performed in two stages (bottom, then upper interval). A total volume of 150 m3 of polymer solution was pumped. Immediately after treatment, sand cut dropped from 1% to almost 0%. This enabled increasing the drawdown from 32/64’’ choke to 40/64’’, keeping the production sand free and sustained with time. This field test confirms the feasibility of the original sand control polymer technology both in gas wells and in oil wells, which opens high possibilities in the future.

Run-to-end (hereafter referred to "RTE") is a fit-for-purpose approach to manage late field life assets for realization of full potential through safe, reliable and cost effective operation by maximizing value at the end of economic life while complying to minimum technical standards through ALARP demonstration. RTE provides an overview of the multiple processes which shall be adopted and customized to the business needs of the intended facilities with the aim to minimize value leakage and ensuring safety until facility's cease of production prior to relinquishment or decommissioning. This RTE philosophy is to be applied to facilities that are within 5 years of its end of economic life so that value leakage can be minimized within the tolerable risk. The RTE provides an overview of development of case for change, guided process for the Operation & Maintenance philosophy changes and demonstration of risks mitigation & governance assurance. The safety risk of the facility shall be assessed and monitored through continuous ALARP demonstration. If the facility is deemed to be either no longer safe through ALARP or can no longer maintain a positive cash flow position, it is recommended that the facility to cease production operations and proceed with relinquishment or decommissioning activities. It has been implemented in one of late field life and resulting to 30% reduction of OPEX.

Unconventional reservoirs such as shale and tight sandstones that with ultra-low permeability, are becoming increasingly significant in global energy structures ( Pejman T, et al., 2017 ). For these reservoirs, successful hydraulic fracturing is the key to extract the hydrocarbon resources efficiently and economically. However, the intrinsic mechanisms of fracturing growth in the tight formations are still unclear. In practice, fracturing design mainly depends on hypothetical models and previous experience, which leads to difficulties in evaluating the performance of the fracturing jobs. Therefore, an improved method to optimize parameters for fracturing is necessary and beneficial to the industry. In this paper, a data-driven approach is used to evaluate the factors that dominate the production rate from tight sandstone formation in Changqing Field which is the largest oil field in China. In the model, the input parameters are classified into two categories: controllable parameters (e.g. stage numbers, fracturing fluid volume) and uncontrollable parameters (e.g. formation properties), and the output parameter is the accumulated oil production of the wells. Data for more than 100 wells from different formations and zones in Changqing Field are collected for this study. First, a stepwise data mining method is used to identify the correlations between the target parameter and all the available input parameters. Then, a machine learning model is developed to predict the well productivity for a given set of input parameters accurately. The model is validated by using separate data-sets from the same field. An optimize algorithm is combined with the data-driven model to maximize the cumulative oil production for wells by tuning the controllable parameters, which provides the optimized fracturing design. By using the developed model, low productivity wells are identified and new fracturing designs are recommended to improve the well productivity. This paper is useful for understanding the effects of designed fracturing parameters on well productivity in Changqing Oilfield. Furthermore, it can be extended to other unconventional oil fields by training the model with according data sets. The method helps operators to select more effective parameters for fracturing design, and therefore reduce the operation costs for fracturing and improve the oil and gas production.

Nonconventional wells (NCWs) are applied to increase the well deliverability and access the difficult formations. The nonconventional wells have been used to refer for the advanced wells such as highly deviated, horizontal, fishbones or multilateral wells. These wells offer a great potential to maximize the hydrocarbon recovery, however, it is difficult to predict their performance. In the literature, numerous mathematical models were developed to predict the well-productivity. However, the available models have been developed by employing one or more simplifying assumption(s), which may lead to over or under estimate the hydrocarbon production. This paper presents an effective technique to estimate the productivity for nonconventional wells. In this work, artificial intelligence (AI) technique was utilized to determine the well-productivity for wide range of conditions. The developed models can determine the well performance without introducing the complexity associated with the numerical approaches. Artificial neural network was utilized to estimate the hydrocarbon production for two types of nonconventional wells; fishbone multilateral and hydraulically fractured horizontal wells. Reliable models are presented to quantify the performance of nonconventional wells producing from heterogeneous and anisotropic formations. The developed models evaluate the importance of reservoir properties and well configuration on the well deliverability. Total of 850 data sets were utilized to construct the intelligence models and to validate the prediction performance. Moreover, mathematical equations were extracted utilizing the optimized ANN models. The extracted correlations showed acceptable prediction errors, the absolute error around 7.4% in average. The novelty of this work is that effective models are proposed to quantify the productivity of nonconventional wells. The proposed models can be utilized to refine commercial software to narrow down the deviations between the actual measurements and simulation outputs. Also, this work can contribute to enhance our understanding of the oil-field management by improving the prediction of well deliverability. Consequently, this study can help in optimizing the well planning for complex wells such as hydraulically fractured horizontal and fishbone multilateral wells.

In southern Pakistan, most wells in mature fields do not flow naturally and require delivery of supplemental energy into the wellbore through an artificial lift system. The existing portfolio of techniques, however, faces technical and economic challenges. Operators have tried numerous methods of deliquification such as soap injection, jet pumps, electrical submersible pumps, and conventional gas lift (GL). Those solutions differ in methodology and efficiency, but they unfortunately have failed either technically or economically in Pakistan. Because reviving dead wells is key to maximizing production with the most efficient and cost-effective method in Pakistan, a detailed screening of candidate wells was carried out to identify innovative artificial lift solutions. The deployment of GL valves using coiled tubing (CT) soon emerged as the best option, because it offered the highest returns in a cost-benefit analysis. Coiled tubing gas lift (CTGL) is a rigless solution that enables setting GL valves at the required depth, during any stage of a well life. It allows gas to be injected through CT with production through the CT-to-tubing annulus. This technology is also retrievable and replaceable when needed. Two pilot wells, that had been shut in since 2015, were selected from four shortlisted candidates through nodal analysis. Each system consisted of one CT string with multiple stations of unloading and orifice valves, spaced out at depths engineered to maximize each well’s productivity. In addition to a GL valve, each station included two CT external connectors and one self-aligning connector, which enabled efficient and safe connection between both CT ends during the deployment of the CTGL station. Additionally, specific CT pressure control equipment and wellhead adapters were used to secure and hang the CT string in the production tree and provide connection with the gas injection facilities at the surface. The first installation was conducted in a vertical well originally completed 4 1/2-in. monobore, deploying 1 1/2-in. CT string with four CTGL stations. The second installation was performed with 1 1/4-in. CT and five CTGL stations in a well originally completed with 7-in. liner and 2 7/8-in. production tubing. The wells were commissioned using existing surface infrastructure and were unloaded smoothly until the production stabilized at optimum rates near 420 B/D and 325 B/D respectively. This innovative artificial lift technique represents an effective and economical solution to restart production in mature fields where conventional artificial lift methods challenge well economics. This approach greatly rests on a thorough candidate selection process. The design and installation of two new CTGL systems was a first in the Middle East region and helped identify numerous best practices and lessons learned, which will speed up implementation of the methodology in other parts of the world.

Underbalanced drilling technology is widely used to reduce formation damage in the reservoir section and improve productivity with the resulting ancillary benefit of improved drilling performance. It involves drilling with a fluid whose equivalent hydrostatic pressure is lower than that of the formation being drilled. As a consequence of this lower hydrostatic pressure there is a continuous flow of hydrocarbons to surface which is handled by separation equipment and exported thru pipelines where they exist or burned at the flare if no transportation infrastructure is located near rig-site. The most prevalent method of implementing UBD drilling operations in Hassi Messaoud field for Sonatrach, involve using the concentric casing method to inject Nitrogen. Doing so ensures that downhole motor and MWD tools performance is not adversely affected by the presence of nitrogen gas lowering their performance. Concentric casing injection insures that the open hole section is only exposed to native crude further reducing the potential for reservoir formation damage. This is achieved by injecting single phase crude down the drill string and nitrogen is injected thru the well head between the tie back liner and previously set casing. The introduction of nitrogen in the main annulus is achieved by means of concentric casing injection ports this has the desired effect of lightening the hydrostatic pressure of the drilling fluid to lower than the reservoir pressure thereby leading to inflow of hydrocarbons while drilling ensues. The excess produced hydrocarbon is exported to nearby production facility. Drilling underbalance drastically reduced formation damage when compared to offset wells which was evident from production testing results. The well was drilled to TD, logged and completed underbalance as well, leading to crude production rate that is 4.5 times greater than average production rate of the nearest four offset wells in same production area which were drilled conventionally. Additionally, by producing the crude during underbalanced drilling operations prior to being handed over to production department, the well was able to recover 40% drilling cost which substantially offset the cost of UBD operations. This paper examines how the implementation of underbalance techniques resulted in successfully drilling, logging and completing the well in underbalance conditions resulting in significant productivity gains for the operator.

Offshore field was producing sweet crude oil by natural flow and gas lift since 1988. However, due to the limitation of gas supply in gas lift wells for offshore field and based on the field development study, a decision was made to install Electric Submersible Pumps (ESP) in offshore field as an artificial lift method to achieve Maximum Sustainable Capacity (MSC). Therefore, a first ESP installation in offshore field was taken place in October 2005 as recommended by reservoir management team. During ESP project, KJO faced challenges related to the monitoring program and to the operation efficiency in order to maximize the ESP run life and to reduce the production interruption. Based on monitoring programs and maintenance inspection on installed ESP wells, it was indicated that the majority of ESP failures occurred due to tubing leaks. Therefore, 20% of workover jobs for ESP wells were candidates because of tubing leaks. The paper will focus more on several field cases of ESP wells which were suffered from tubing leaks. The evaluation results based on empirical method, in which five (5) ESP wells had similar completion configuration and underperformance symptom. Challenges, methodology, work schedule, risk assessment, lesson learned and findings will be discussed. The monitoring programs and maintenance inspection on installed ESP wells resulted on great deal of benefits, which are related to maximize the ESP run life and avoid ESP premature failures to improve the operation efficiency in order to sustained maximum production target.

This paper describes the development of onshore brown field gas compression projects, with production from many hundreds of wells in remote locations. Gas is produced from both sweet and sour reservoirs, with differing decline characteristics and fluid compositions. The paper describes the impact of flow assurance design on the field development plan. The potential for liquid management difficulties are discussed, and a novel liquid management mitigation solution is proposed. The initial investigation used maps to identify the hydraulic optimum locations for gas compression plants (GCPs) in congested areas, followed by site visits. A number of GCPs were based on gas production rate, field location, gas plant capacity and compression power. Design was performed with remit to reuse as much of existing facilities as possible. Uncertainties in multiphase pressure and hold-up predictions on aging pipes required a conservative approach to hydraulics. Sensitivity analyses were performed on critical parameters. The pipeline network design was refined through a cycle of site visits to obtain pipeline corridors and GCPs land use permits. Diameters were optimized to lower liquid accumulation and mitigation implemented against uneven split of liquid flow through existing twin pipelines. Some pipelines upstream of GCPs were discovered to experience high levels of liquid accumulation. This is in agreement with operating experience. "U-bend" topography allows severe liquid accumulation and potential blockage, requiring frequent scraping for liquid management. The proposed solution is comprised by Liquid Separation Stations (LSSs). The LSSs are designed to remove bulk liquids at low points, which are transported via separate liquid pipelines to the GCPs slug catchers (SCs), then onwards to the gas plant. With remote location of LSSs, the design philosophy adopted for design was application of piping components according to ASME B31.8 code, instead of ASME vessel code (and the resultant required appurtenances). This allows very basic gas/liquid separation; and the ability to immediately drain liquids from the separator to maintain normal liquid levels. Consequently, with the ability to drain at rates within an adequate uncertainty factor, significant residence time in the LSS is not necessary, allowing the sizes to be kept within the confines of B31.8 code. Uncertainties in system design inputs and multiphase flow prediction in brownfield developments are highlighted. The proposed novel use of piping code to develop remote field separation for liquid management is discussed. This mitigation offers benefits of reducing operational issues associated with frequent scraping and liquid blocked pipelines.

Decline curve analysis is a widely used technique in evaluating well production performance and forecasting. One of the most commonly used decline curve modelling approaches is called Arp's model. This modelling approach has four fundamental assumptions. One of these assumptions is that the well is produced at constant bottomhole pressure (BHP). This assumption is usually approximated under real-production situation. Therefore, the objective of this study is to construct a novel mathematical workflow using modified decline curve models without violating constant pressure assumption, and use the production forecast to identify potential issues in the wellbore. In this data analytic process, using a large field data sets, the linear regression technique was implemented to convert variable pressure values into an equivalent constant pressure value. Consequently, this equivalent constant pressure was used to derive new gas rates using the back pressure equation. The new gas rates were used as input parameters in the new production performance as well as forecasting algorithm. Using MATLAB's toolbox, a large set of field gas production data were analysed, and the results showed very good agreement with insignificant margin of deviation. In addition, the new model prediction when compared with the actual production data enabled the user to detect events such as liquid loading (hydrocarbon) or water dropout phenomena. Consequently, the new algorithm was used to forecast the future production behaviour. A novel decline curve modelling algorithm without constant bottomhole pressure approximation is presented in this paper. In addition, the new algorithm also presents a tool for the reservoir engineers to identify events in the wellbore such as well loading with dropped out condensate or accumulation of conning water to create blockage of gas production.

This work describes an innovative application of Integrated Asset Model (IAM) implemented for Mexico Area-1, aiming to simulate the whole asset development. The context of application is strongly complex, since the asset is composed of five reservoirs, connected to the same Floating Production Storage and Offloading unit (FPSO). The reservoirs are separated and different in terms of structure, initial pressure regimes and characteristics of oil. A cross-platform model of the whole Area-1, has been developed in order to implement simulation constraints from asset to well level in a unique tool. Moreover, an innovative process was defined to increase the accuracy of the IAM, improving the control of the wells equipped with electrical submersible pumps (ESP), through the honouring of the ESP working conditions. Reservoir models include actually dedicated instructions to monitor and handle wells production according to gas-liquid ratio (GLR) at the ESP intake. This allows to operate the pumps as per design, obtaining more reliable simulation results. The IAM, combined and enhanced with the new process, enables to run several sensitivities comparing different technologies for network configurations and artificial lift systems in order to select the finest solution to maximize the production. The enhanced model, improved in reliability, permits, in fact, to dispose of a unique tool suitable for different purposes: multi-phase pump (MPP) deployment assessment, ESP design support, water injection handling and facilities sizing. In conclusion, the enhanced IAM merges all the constraints in a single apparatus allowing the monitoring of the asset from the reservoir to the network scale, by means of the generation of reliable fluid production profiles.

Recent experience in applying recurrent neural networks (RNNs) to interpreting Permannt Downhole Gauge (PDG) records has highlighted the potential utility of machine learning algorithms to learn reservoir behavior from data. The power of the RNN resides in its ability to retain information in a form of memory of previous patterns and information contained in the previous behavior of phenomena being modeled. This memory plays a role of informing the decision at the present time by using what happened in the past. This property suggests RNNs as a suitable choice to model sequences of reservoir information, even when the reservoir modeler is faced with incomplete knowledge of the underlying physical system. Convolutional Neural Networks (CNNs) are another variant of machine learning algorithms that have shown promise in sequence modeling domains, such as audio synthesis and machine translation. In this study, RNN and CNN were applied to tasks that traditionally would be modeled by a reservoir simulator. This was achieved by formulating the relationship between physical quantities of interest from subsurface reservoirs as a sequence mapping problem. In addition, the performance of a CNN layer as compared to RNN was evaluated systematically to investigate their capabilities in a variety of tasks of interest to the reservoir engineer. Preliminary results suggest that CNNs, with specific design modifications, are as capable as RNNs in modeling sequences of information and as reliable when making inferences to cases that has not been seen by the algorithm during training. Design details and reasons pertaining to the way these two seemingly different architectures process information, and handle memory are also discussed.

Steam-Assisted Gravity-Drainage (SAGD) is one of the most effective ways of recovering heavy oil. Injection of cold solvent into the SAGD formation is an enhancement to SAGD recovery technology to reduce the energy consumption and heat loss. SAGD process is a high energy-intensive process where it requires a high amount of steam to mobilize and recover the heavy oil. Besides, generation of steam requires the combustion of natural gas which adversely impacts the economics of SAGD, especially when the price for natural gas is high. Furthermore, large amounts of injected steam are retained in the reservoir where it reduces the thermal efficiency of the process. Therefore, this research aims to develop better recovery process with lower energy and emission intensities. In this study, a thermal compositional simulation was carried out using a commercial simulator to examine the performance of cold solvent in assisting heavy oil recovery. In this process, the cold solvent is injected into a mature heavy oil field where it has been recovering using SAGD process. The solvent will then utilize the energy retained in the reservoir to vaporize and spread within the steam chamber. The low temperature of the solvent will cool down the temperature of steam chamber where it enhances the solubility of solvent in the oleic phase and accelerates recovery. Carbon dioxide is chosen as the solvent for this process as it is considered as a lower-cost alternative compared to hydrocarbons. The simulation shows a secondary peak oil rate due to the cold solvent, followed by a steady increase in oil production rate. This is also aided by the viscosity reduction due to carbon dioxide solubility. Steam injection is ceased when a cold solvent is injected into the formation, hence significantly reducing the steam requirement in heavy oil recovery. Overall results show that the cold solvent process increases the oil recovery by 2%, reduces steam-oil-ratio, reduces total heat loss by 16% and reduces steam requirement by 24%. Hence, the advantageous results from the simulation prove that cold solvent is a profitable and energy-efficient recovery method in recovering mature SAGD formations.

Gas-lift technique plays an important role in sustaining oil production, especially from a mature field when the reservoirs’ natural energy becomes insufficient. However, optimally allocation of the gas injection rate in a large field through its gas-lift network system towards maximization of oil production rate is a challenging task. The conventional gas-lift optimization problems may become inefficient and incapable of modelling the gas-lift optimization in a large network system with problems associated with multi-objective, multi-constrained, and limited gas injection rate. The key objective of this study is to assess the feasibility of utilizing the Genetic Algorithm (GA) technique to optimize the allocation of the continuous gas-lift injection rate in a network system of a Middle Eastern oil field with 43 gas-lift injected wells through numerical modelling and simulation studies. Reservoir pressure and water cut sensitivity studies are performed to investigate the potential impacts of these parameters on well production performance and production life cycle of the field. Sample economics analysis are exercised to broaden the understanding of potential benefit of the implementation gas lift techniques in the field from both technical and economic viewpoint. In addition, while application of GA is not a new idea, this paper elaborates the GA based optimization techniques for improving the oil production rate by implementing gas lift in a large Middle Eastern oil field. The optimization model is presented step by step, so it can easily be followed, and be used as a guide, especially by frontline production engineers involved in designing and development of gas-lift system towards optimally allocation of gas injection rate to individual well in a network system for a field with limited gas injection rate.

D1 is an oil and gas field located offshore of Bintulu, Sarawak. It's a hub with several tie-in fields namely, D1-A, D1-B, D1-C, D2, D3, E1 and J1. Over the years, as more fields were tied-in to this hub, there have been significant increase in both oil and gas production. D1's facilities were designed to cater for high liquid flowrate. Hence, there was no need for a major topside modification to cater for increase in liquid production. However, with increasing associated gas (AG) produced from all these tie-in fields, a serious topside constraint arose concerning associated gas due to insufficient compressor ullage. Consequently, the excess gas which cannot be compressed had to be flared resulting in higher flaring/venting (FV) than the limit set by the host government authority. In order to avoid any FV violation, the field's operator had to increase the operating pressure of the low and high pressure (LP and HP) separators to reduce the amount of gas that was being flared. This paper describes the topside optimization that was diligently conducted over a period of 7 months to test and achieve an optimum production while maintaining FV within limits. Implementation of this effort involved process study to evaluate the compressor ullage availability verus current and future gas production from the hub. Based on this info, the operating philosophy of the existing 2 compressor trains at D1 were changed from 2 x100% to 2 x 50% in which both trains were put online concurrently instead of 1 unit running and 1 unit on standby. This new operating philosophy required changes to the compression system and re-strategizing the maintenance and spare parts management for both units to ensure sustainable operation over the long run. This zero-cost optimization revolves around 3 key performance indicators. Firstly, the excess gas that was previously flared can now be compressed and exported contributing to more than 100% increase in gas sales. Secondly, in line with the hub's efforts to reduce its carbon footprint, flare reduction of almost 50% was achieved. Finally, from subsurface perspective, running 2 compressor trains reduces the operating pressure of LP and HP separators by 1.5 barg and 2.5 barg respectively resulting in a significant reduction in backpressure to the wells. This improved oil recovery from wells across all the fields tied-in to D1 hub.

A new analytical procedure is introduced for the interpretation of pressure-transient data in oil producers with pronounced water production. The new mathematical model is applicable to flow conditions where segregated flow dominates the displacement process in the reservoir. Here, formation flow capacity and individual magnitudes of oil- and water-phase mobility are also determined, allowing accurate reservoir characterization under such complex flow conditions. Segregated flow is very common in natural porous rocks and is characterized by a sharp interface between oil and water. Hence, our new mathematical model mimics the dynamics of this flow mechanism by taking into consideration the individual contributions of oil and water from each reservoir zone. This novel mathematical model is utilized to extract formation flow capacity and mobility for both phases. An average fluid saturation can also be determined with a reasonable accuracy. The reservoir system in hand is represented by a two-layer model with no crossflow between the different zones in the reservoir. Because of gravity effects, oil is produced from the top layer while water is produced from the bottom one. Each reservoir layer has its own distinct static and dynamic properties, such as porosity, permeability, thickness, and petrophysical properties. A case study based on synthetic reservoir data is presented to demonstrate the application of the mathematical model in characterizing formation rocks. It is observed that conventional well-testing methods could produce inaccurate results when applied to reservoir systems influenced by segregated flow. Using the new model, a correction factor is derived to estimate absolute permeability values from the conventional well-testing analysis, producing a one-to-one transformation between dispersed and segregated flow. The conventional way of interpreting pressure-transient data for two-phase flow displacements under segregated conditions is based on an equivalent single-phase flow model that might produce inaccurate results and invalid estimates of flow capacity and phase mobility. Our new approach, therefore, is more representative for the system under consideration and captures the flow mechanism more robustly.

Unconventional gas developments in the Middle East are relatively new, compared to the established shale developments in the US. The Middle East developments are generally owned or controlled by a single entity, e.g. the national oil company, rather than the model often seen in the US of multiple operators focused on their particular ‘block’. This can lead to a different approach to the full field development (FFD), with more emphasis needed on de-risking projects, particularly during their early stages. This de-risking process is essential to limit the exposure of the single owner to the inherent uncertainties of an unconventional development as the scale of the project increases. This paper considers multiple areas of uncertainty and risk associated with an unconventional gas field development. From the necessity for clear project drivers and team alignment, through to the uncertainties of well production and water management, risks are identified with recommendations to help projects avoid pitfalls and manage the inherent risks of developing a large unconventional field in the Middle East. The paper concludes that a Middle Eastern project can't, in all cases, simply adopt the practices used in the US. The project may choose to take guidance from the US but since the operating environment is different, the risks, and therefore management of risks, will in many cases need to be addressed differently.

Ning201 Longmaxi shale gas play is located on the southwest edge of Sichuan Basin. Block Ning201 surface is very mountainous and elevation range of drilling pads is between 400 meters and 1300 meters. The target layer of shale gas exploration and development is mainly the Wufeng Formation of the Ordovician system and the organic-rich shale interval of the Lower Longxixi Formation of the Silurian system. The total thickness is between 30m and 50m, and the overall buried depth is 2300~3200m. Field development of Ning201 shale gas play was geared up in 2014. During early appraisal phase before 2014, average testing results of wells were 10~15×10 4 m 3 /d. 7 vertical appraisal wells and 50 horizontal wells have been drilled and 38 horizontal wells among them have been put into production to evaluate optimized development strategy until middle of 2017. Changning area accomplished the construction of 15×108 m 3 /a production capacity. During production appraisal phase, different well spacing pads were configured, and some cross-well interference testing were performed to determine optimal spacing in Ning201 block. Only qualitatively understanding can be achieved with spontaneous field efforts and quantitative evaluation of long-term impacts on production with varying initial rate control and well spacing is still missing. In this paper, an integrated modeling workflow was introduced to accurately simulate the production behavior of a representative shale gas well and to control production through a calibration model to optimize well spacing and maximize economic returns. The workflow begins with microseismic monitoring during shale gas well fracturing operations. Considering the fracturing pumping procedure, fluid and proppant volume and subsurface features, including formation, natural fractures and in-situ stresses, the heterogeneity of the hydraulic fracturing system propagation ensures that the simulated complex hydraulic fracturing network is in line with reality. After establishing a detailed hydraulic fracturing model, production performance is matched to history to better calibrate the conductivity of hydraulic fracture network in dynamic model as a relaible predicting tool.