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Haryanto, Elin (Schlumberger) | Yersaiyn, Saltanat (Schlumberger) | Akram, Agha Hassan (Schlumberger) | Bouchet, Francois (Schlumberger) | Galal, Haytham (Schlumberger) | Basarudin, Mohd Ashraf (Schlumberger)
The reservoir management team is often facing a standardization challenge during audit and screening of inactive wells, especially if this task involves multiple mature oil reservoirs or fields. Such a well candidate screening process is normally required to select candidates for revival as well as plug and abandonment (P&A) candidates.
Shut-in wells across different fields may be sharing common issues such as pressure depletion, liquid loading, and high water cut, however, the severity of well-related problems varies from one field to the other. This is in addition to the variation of wellbore mechanical issues such as well-bore integrity, wellbore accessibility, and others. This paper aims to demonstrate a workflow to provide a quantitative ranking of wells. It can be used to standardize an audit process during multi-reservoir or multi-field inactive-well candidate screening study.
The standardization process was addressed by developing a tool that registers the shut-in well ranking upon completing the well potential and risk assessment process. Well level petroleum engineering and production data analysis such as decline curve analysis, nodal analysis and well modeling are performed to estimate the remaining well potential. Subsequently, to enable a comparison across different fields, behind pipe well potential was normalized using multi-field parameters. The audit process followed with well workover risking based on ease of workover intervention including workover options such as water shut off, remedial wellbore integrity work, stimulation and others where it also draws on local knowledge for well risk calculation. The approach presented in this study provides a comprehensive tool for both key performance indicators; remaining well potential and well risk, that are usually required to short-list wells for workovers.
The standardized audit process was demonstrated in a case study where a large number of shut-in wells from multiple mature oil fields were ranked. In this study, the 7 highest ranked wells were recognized as production enhancement candidates and conversely, a number of wells with the lowest ranking were identified for well abandonment. Through this standardized workflow, the well risk assessment was performed efficiently with tools that enable a consistent result across different fields. It helped to accelerate the reservoir management decision-making process in identifying wells with the most impact to increase the success probability during inactive well revival and workover. The workflow and the tool presented in this paper has the potential to be used as analytic tool or template and can be used as a live document that may be adopted to reduce the workload and improve shut-in well management.
Ali, Hamza (Schlumberger) | Shah, Abdur Rahman (Schlumberger) | Akram, Agha Hassan (Schlumberger) | Khan, Waqar Ali (Schlumberger) | Siddiqui, Fareed Iqbal (Pakistan Petroleum Limited) | Waheed, Abdul (Pakistan Petroleum Limited) | Ahmed, Faizan (Pakistan Petroleum Limited)
A recent study addressed the modelling challenges of Alpha* gas condensate field. Alpha gas condensate field has a gas in-place of about 1 TCF, and both condensate and black oil production in addition. The field has been producing from two reservoirs SI and DI, for the past 26 years. Alpha field is subdivided into two segments called the Central Area and the Northern Area which are separated by a fault as shown in Figure 2. * Not its real name. One of the most unusual features of Alpha field are the'phase switch wells'.
In the wellbore, phase segregation and density changes become significant during gauge pressure measurements. Static pressure surveys capture this change in density, provided the gauge is stationed at different depths in the lower part of the tubing, where this change is most expected. These static pressures are then corrected to datum depth to determine the depletion across the field.
Conventionally, a one step pressure correction is used to correct the pressures from the gauge station to datum depth using the wellbore pressure gradient. This approach assumes that the same gradient exists, both in the reservoir and in the wellbore, which is generally not true in the case of gas condensate reservoirs, as well as oil & water producers.
This paper presents a two-step pressure correction workflow for gas condensate reservoirs.It proposes to establish a gradient from pressure measurements acquired from lower gauge stations, as segregated fluid density changes even in the liquid column. This is the wellbore gradient. It makes use of PVT parameters to determine the gradient developed by the reservoir fluid, which is independent of the wellbore gradient, to ensure that the correction to datum depth incorporates the actual reservoir conditions.
It was observed that two step correction, which makes use of reservoir fluid gradient in 2nd step, provides pressure values comparable with formation testing results in contrast to single step corrected pressures.
This paper presents a step by step workflow and emphasizes how important it is to make use of actual reservoir conditions while correcting pressure measurements. Advantages and disadvantages of each correction method are also discussed.
IntroductionThis paper discusses the underlaying methodology of a two step workflow developed for static pressure correction in case of gas condensate reservoirs. PVT samples collected have been used to derive PVT parameters to compute the reservoir fluid gradient.While this paper focuses on workflows, results have also been listed in comparison with the conventional one step correction approach which highlights the importance of using this workflow while correcting pressure to improve accuracy and minimize error.
The subject Gas Field is located in the Sulaiman Fold Belt (SFB) in Pakistan. A realistic 3D static model was constructed for the challenging multiple reservoirs in the Field which included both clastics and carbonates. Four main reservoir horizons were modeled.
The steps involved in the Reservoir engineering analyses were: analyze PVT, well test, Static Pressure Data, and Core. The static pressure analysis helped define hydraulic compartmentalization in the field.
WHFP measurements were not available in the desired accuracy and density. A surface network model was used with plant inlet pressure as the primary constraint in order to obtain the required information. Satellite based elevation information was used to establish an accurate model with respect to pressure drop due to liquid hold up in pipelines.
The History Match in the field was performed on a Zone by Zone basis. In the absence of a 3D seismic cube, many of the faults in the field could not be interpreted, yet their presence was predicted by a closely matching Sand Box Model. This was an important clue which led to a useful approach regarding the location of simulation faults distributed in the entire field. An innovative approach was used in order to calibrate the size of sand lenses in one of the zones.
The final step was the forecasting and development of Optimal Scenario using Economic analysis. Many scenarios were tested, and the optimal scenario was identified. Maximum use was made of existing wellbores through re-completion, and new drilling was minimized. Furthermore, the impact of increasing the currently low Gas Price was tested. It was concluded that doubling of the gas price of the field would increase the NPV 3 times delay abandonment by 6 years.
The Gas Field is located in the Sulaiman Fold Belt (SFB). Eighteen (18) wells in all, those have been drilled in the Field. Currently 12 wells are producing Gas. The primary target horizons in Field are the Sui Main Limestone (SML) and Lower Ranikot (LRKT). However, the Dunghun Limestone and Pab Sandstone are also producing in some of the wells. The depositional sequence consists of clastic and carbonate succession. The stratigraphy of the reservoirs is strongly influenced by the structural evolution of the Sulaiman Fold Belt and initial rifting of the Indian Plate.
Wireline formation testers are now in their third generation of development. These tools are used to measure formation pressure andpermeability, and to take fluid samples from the reservoir. Technological developments over the years have resulted in a modular tool that can obtain a clean formation fluid sample with minimal contamination. Sampling time varies from a few minutes to many hours depending upon different parameters i.e. depth of invasion, flow rate, formation permeability, anisotropy, porosity and the viscosity of the involved fluids including mud filtrate and formation fluids.
Total pumpout time required to obtain a clean sample is always of interest to both the operator and service company owing to economics, well stability and other factors. An approach is required that is flexible and that requires few parameters to estimate the pumpout time and the time for first formation fluid slug.
In this study a new polynomial model is developed to better estimate the time to first slug.
The new model was tested for different pumpouts from different wells and history matching was performed to test the accuracy of the model. A number of pumpouts were considered and all of those showed close matches. Software was developed to quickly calculate the total pumpout time at real time. Also in this study the previous model was tested and with the limited available data the new model showed much improved results over the previous model.
As an increasing percentage of the world's production comes from mature fields, there is a growing need for production enhancement techniques that are both rapid and easy to use for the practicing production engineers. For mature waterfloods, the ln(WOR) versus Np plot enables rapid well screening on the basis of incremental recovery factor, where WOR is the producing Water Oil Ratio and Np is the cumulative oil production. Published in-depth information on application of this tool is sparse. Yet, this is often the only tool available to the production engineer for evaluating development options, where a history-matched simulation model has not been maintained.
In this paper, the theoretical basis for the use of the ln(WOR) versus Np is reviewed and studied, and is used to arrive at practical guidelines for interpreting production data. Its applicability as a forecasting tool to single-layered and multilayered clastic, waterflooded reservoirs of varying heterogeneity is demonstrated. Numerical simulation models then predict the behaviour of this plot for a wide range of heterogeneities.
Production data is then analysed to show the applications of the theory for multilayered reservoirs. The ln(WOR) versus Np plots are analysed, and the impact of various factors is observed. The authors also demonstrate that, where applicable, this plot is the preferred decline curve for the following reasons:
- Ln(WOR) versus Np does not require any pressure data; only surface well test production history is required.
- It can be assumed that the ln(WOR) versus Np function is an approximate function of the reservoir only, and is decoupled from the outflow and facility constraints. This is especially useful when comparing artificial lift and drawdown strategies.
- It is a decline curve model that provides a forecast of water cut, which is indispensable on waterflood projects.
Introduction: Ln(WOR) vs. Np plots
As an increasing percentage of the world's production is from mature fields, there is an ever-growing need for production enhancement techniques which are both rapid and easy to use for the practicing production engineer in the field. Where the operator has maintained a reservoir simulation model, which is both history matched and contains sufficient granularity and accuracy to be used as a forecasting tool at the well level, the simulation model is the tool of choice. This is often not the case and production engineers have to revert to DCA (Decline Curve Analysis) in order to estimate production profiles and incremental reserves on a well by well basis. This paper reviews the use of the ln(WOR) vs. Np decline curve as applied to water-flooded reservoirs. Both the theoretical justification for the use of such a decline model as well as the practical guidelines for interpreting production data are covered in this paper.
Copyright 2010, Society of Petroleum Engineers This paper was prepared for presentation at the SPE Production and Operations Conference and Exhibition held in Tunis, Tunisia, 8-10 June 2010. This paper was selected for presentation by an SPE program committee following review of information contained in an abstract submitted by the author(s). Contents of the paper have not been reviewed by the Society of Petroleum Engineers and are subject to correction by the author(s). The material does not necessarily reflect any position of the Society of Petroleum Engineers, its officers, or members. Electronic reproduction, distribution, or storage of any part of this paper without the written consent of the Society of Petroleum Engineers is prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of SPE copyright. Abstract In many oil wells, production is commingled from several layers. In such environments, understanding the properties of individual layers is essential to reservoir surveillance and production optimization. The inflow properties that typically require measuring are productivity index (PI), water cut, and static reservoir pressure. These measurements have traditionally been taken with wireline-conveyed production logging tools (PLT); however, in many wells and operating environments, completion and logistic considerations make running these tools difficult or even impossible.
Copyright 2010, Society of Petroleum Engineers This paper was prepared for presentation at the SPE North Africa Technical Conference and Exhibition held in Cairo, Egypt, 14-17 February 2010. This paper was selected for presentation by an SPE program committee following review of information contained in an abstract submitted by the author(s). Contents of the paper have not been reviewed by the Society of Petroleum Engineers and are subject to correction by the author(s). The material does not necessarily reflect any position of the Society of Petroleum Engineers, its officers, or members. Electronic reproduction, distribution, or storage of any part of this paper without the written consent of the Society of Petroleum Engineers is prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of SPE copyright. Abstract A Paleocene dolomite in northeastern Libya was modeled using three porosity types: matrix porosity (intercrystalline plus the separate vugs), horizontal-to-subhorizontal solution-enlarged vuggy porosity generated by dissolution and named "touching vugs," and fracture porosity. The touching vugs, which acted like fractures in their dynamic behavior, are modeled as a very permeable discrete fracture network (DFN) in PETREL* seismic-to-simulation software. Their presence is known primarily due to pressure buildup analysis, and it is expected that they would be interconnected over hundreds of meters. The primary challenge in dual-media modeling is being able to characterize and predict the dynamic behavior of the complex matrix fracture touching vug system. There are three wells in this area of northeastern Libya with pressure buildups that have an unusually distinct and pronounced dual-porosity signature. Each well has been matched by adjusting the five primary parameters: matrix and fracture porosity and permeability, and the sigma shape factor.
A study was carried out to forecast the productivity of a hydraulically fractured well in a retrograde gas-condensate sandstone reservoir using a numerical model. The fracture was explicitly modeled as a set of high-conductivity cells.
At the gas velocities normally encountered in hydraulic fracture proppant packs, non-Darcy pressure drops dominate, and the apparent proppant permeability is one or two orders of magnitude lower than the Darcy permeability measured at single phase low-rate conditions. This is particularly true if a liquid phase is also flowing. The apparent permeability of the proppant is a function of:
Gas velocity (hence: rate and flowing pressure)
Ratio of free liquid rate to gas rate
Stress on the proppant
Type of proppant
Thus, apparent proppant permeability will vary with distance from the wellbore, increasing towards the tip of the fracture where liquid ratio and velocity are lower.
This variation of permeability was explicitly modeled in the proppant pack by dividing it into segments and calculating the permeability in each segment. As a result of this modeling, the impact of increased fracture length on productivity was found to be more significant than in simpler modeling where one permeability value is used for the entire proppant pack.
The variation of apparent proppant permeability along the length of the fracture and its impact on well productivity are discussed in this paper. A comparison of predicted well productivity is also made with the use of a constant permeability value for the proppant in numerical and analytic simulators. We will show that using a constant proppant permeability value results in an estimate of optimal fracture length that is too short.
An innovation in the methodology of conducting drillstem tests (DSTs) in tightgas reservoirs is presented, along with a simplification in the interpretationof the data obtained. DSTs in tight gas reservoirs are a problem because theflow rates are often too low to be measured by conventional equipment. In thesecases a normal flowing and buildup test should be followed by a closed chambertest to produce usable estimates of flow rates at various times during thepreceding normal flowing and buildup test. This estimated flow rate can then beused to interpret the buildup after the flow testing, which is produced byshutting the downhole valve.
In the interpretation of DST data from a tight gas reservoir, factors suchas the following have to be considered: 1) large variation of gas propertiesresulting from the large pressure range involved; 2) flow rate duration thatcan be many times shorter than the buildup period; 3) varying flow rate duringthe flowing part of the test; and 4) impact of boundaries andheterogeneities.
We show that a simple interpretation approach with constant flow rates andpseudo-pressure yields results that are within the intrinsic accuracy limitsexpected from such a test.
The benefits to the field interpreter of using the methods presented are 1)operational flexibility: if the well flows strongly enough the rate may bemeasured at surface; if it does not, a closed chamber test can be added; 2) thebenefit of the deeper radius of investigation of a test flowing at surface isretained; 3) field interpretation is simpler whether surface measurement ispossible or not.
The two major challenges that face the interpreter in tight gas DSTs are thedifficulty in measuring rate, and the selection of interpretation tools andtechniques.