Copyright 2012, Society of Petroleum Engineers This paper was prepared for presentation at the SPE Annual Technical Conference and Exhibition held in San Antonio, Texas, USA, 8-10 October 2012. 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.
Calculating and determining a range of Gas Initially In Place (GIIP) is one of the major challenges faced when optimizing a field development plan. Desired outcomes can be further complicated by geological characteristics which are uncertain and difficult to quantify; to the point where a physical solution is unattainable without the use of inappropriate and complicated software applications. Plackett-Burman Experimental Design (P-B ED) is a published and an innovative process which is simple, logical and efficient in managing uncertainty and appropriately defining the range of possible outcomes by utilizing simple, every day and user friendly software. P-B ED allows for effective planning and mitigation for the most likely outcome and the least. The geological uncertainties incorporated in the analysis are described in Part 1 of the Greater Dolphin Area Case Studies; SPE 158545.
The P-B ED workflow was applied to determine the range of GIIP for the Starfish field. Starfish is currently not on production and is located off the East Coast of Trinidad and is being considered for development. It is owned as a joint venture between Chevron and BG Trinidad and Tobago (operator). One of the main objectives of this process was to identify the P10, P50 and P90 geo-models which are then used for dynamic modeling and field development planning.
The Unconstrained Development Study (UDS) process was utilized for the field development planning of Starfish. A UDS is a process used to determine the optimum number of wells and their locations to develop a field. The P50 dynamic model was populated with hundreds of wells which were subsequently eliminated based on well performance and water breakthrough. This is an iterative process which has been recognized as an effective workflow for field development planning. Once the P50 reservoir outcome was optimized, both P10 and P90 geo-models were tested to ensure that the proposed development plan was also valid for the geological range.
After applying the UDS process; it was determined that four wells were required to optimally develop the field. This paper discusses the Experimental Design and UDS workflows, summarizes the lessons learned and recommends best practice for field development optimal recovery efficiency.
The Starfish field is located off the east coast of Trinidad. The field and is owned as a joint venture between Chevron and BG Trinidad and Tobago (operator) and has not yet been developed, see Figure 1. The Starfish discovery was made by the Starfish-1X well which was completed on 23rd November 1998. A second exploration well, Starfish-2 was also drilled. The D, E and G sand reservoirs at Starfish Field are Pleistocene-aged, shallow marine sandstones. Water depth at the field ranges from 120m to 180m (400ft to 600ft).
Repsol (operator), together with partners Petrotrin and National Gas Company of Trinidad and Tobago, took over operations of mature fields Teak, Samaan and Poui (TSP) Offshore Trinidad by end of 2005. With the intention of planning further development in the TSP reservoirs (comprising more than 10 vertically stacked main units, highly compartmentalized reservoirs with complex tectonic geometries) an indigenous comprehensive field evaluation was required. In order to perform a detailed analysis on all reservoirs, the effort would have been immense and would have delayed the decision making by years. Thus, a sand-by-sand Screening Project was carried out with the main objective of identifying the reservoirs with maximum potential so as to direct further technical effort on specific reservoirs for early monetization of the reserves.
Based on the results of sand-by-sand screening project, a prospect validation project for Teak Field was initiated - consisting of extensive field data acquisition, detailed interpretation and modeling workflows, adapted to the particular needs of mature fields. Several incremental opportunities identified during screening were validated and detailed modeling was performed to support further development. In some cases, the reservoir units that were identified to be having significant potential, turned out to be low on the priority list, as well as new and better than expected prospects appeared on the list. This paper outlines some examples and experiences from the prospect validation exercise.
On completion of this effort, the company acquired a holistic view of the asset in terms of projects and its remaining resources. So far, 21 localized static models and 15 dynamic simulation models have been completed resulting in the identification of 11 drilling candidates in Teak Field. A similar effort is planned for Samaan and Poui Fields in the near future. By dividing the problem into parts, the resources were optimized and the building-dynamic-model-for-everything was avoided.
Since the early days of the technique of well logging and the original water saturation equation developed by Archie, low resistivity pay was, practically speaking, a contradiction in terms. Through the years, however, this critical topic and its
practical implication for the exploration and development of oil & gas reservoirs has become recognized as a worldwide phenomenon of particular and challenging interest.
For this specific study, we will focus in the continental deposits, mainly composed of eolian facies, of the pre-Cretaceous Nia formation that we can further sub-divide into two main prospective dry gas units. The idiosyncrasy of these two siliciclastic
bodies is that they are exhibiting a lack of resistivity contrast between sands and adjacent shales and also with the water filled bottom section of the reservoir, resulting in complex formation evaluation process and problematical reserve calculation because the standard and practical "a, m & n" values are not anymore appropriate.
Despite a uniform mineralogy and clay content, the overall small grain size and relatively elevated amount of feldspars contribute actively to the presence of irreducible water which is not directly related to clay content but to micro-porosity, that
creates a "low contrast resistivity" pay (LCP) effect. Furthermore, when micro-pores are present, they exert a gradually increasing influence as Sw decreases. Their effect is to decrease the saturation exponent "n" and this reduction is related to
the degree of surface conduction constraints on current flow.
Therefore, we will present in this work a petrophysical approach that was adopted and validated in order to overcome these difficulties by combining a systematic and exhaustive laboratory core calibration along with proficient logging techniques
(i.e. mineralogical & NMR). In these relatively freshwater shaly sands logged conductivity is imperfectly modeled and unsuitable to derive an exact water saturation necessary for a precise OGIP calculation. Uncertainties will arise from a combination of various phenomenon including lack of resistivity contrast between pay and non-pay, dissimilarity in shape and size of the sand grains, variable irreducible water content and lack of knowledge of the effective concentration of clay exchange cations. Nevertheless, we will illustrate and evidence that it is still possible to resolve this LCP challenge with the integration of discrete core data, reliable continuous specialized electrical logs and non-linear saturation equation.
Stockhausen, Harald Wolfgang (Repsol YPF) | Garcia Sanchez, Daniel Gerardo (Repsol YPF) | Luongo, Sergio (Repsol YPF) | Surjaatmadja, Jim Basuki (Halliburton) | Loghry, Ray Allen (Halliburton Energy Services Group)
Copyright 2012, Society of Petroleum Engineers This paper was prepared for presentation at the EAGE Annual Conference & Exhibition incorporating SPE Europec held in Copenhagen, Denmark, 4-7 June 2012. 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 The use of hydrajetting for perforating of wells has been commonplace since the 1960s. During those early years, wells were relatively shallow, and jetting success was consistently demonstrated.
In Argentina, over the last decade mature field management has been of paramount importance in ensuring economic sustainability for many oil field operators. Success requires solving a specific suite of problems comprising mixed generations of technology (in particular logging tools), long and complex well histories and often the sheer size of the dataset.
The field in this case study has been in production since 1964 reaching its maximum production capacity of 32000 bpd during 1969, after which decline began. Consequent depletion from 140kg/cm2 to 20kg/cm2 drove the need for pressure support that was achieved through waterflooding which was implemented in two major campaigns during the 70's and the 80's. A total of 354 wells comprise the historical dataset with recent re-drills, extensions and infills bringing the total well count to 422. Re-evaluation of the remaining target via a series of studies carried out between 2006 and 2009 indicated an attractive opportunity for 7 spot waterflooding and saw the commencement of a massive re-development of the field.
Behaviour of recent wells has been worse than predicted. This deviation from expectation initiated a series of studies to better characterize the reservoir with the objective of re-defining targets for incremental development. Associated with these studies new geological and dynamic models were built using re-evaluated historical data integrated with information from 68 new wells and 8 new cores. In particular, the impact of textural variation and thin bed architecture on the meso-scale oil distribution was assessed allied with a range of different techniques to identify macro-scale compartmentalization. The result was an integrated model that enabled comprehensive re-evaluation of the remaining targets.
The approach used in this study to identify and characterize thin beds in this type of setting, define the impact on OOIP and determine the remaining oil in place in order to evaluate opportunities can assist many operators who experience various challenges associated with developing mature acreage.
During recent years, some wildcat wells located in remotes areas of the Peruvian Amazonian rainforest tested commercial volumes of oil and gas. Beyond this preliminary success, reservoir uncertainties due to seismic interpretations, and limited cores and log data impose complexity in reservoir characterization; major sources of uncertainties can be broadly group into three main categories: structural, rock & fluid properties and reservoir performance.
Applications of numerical simulation have been extended to conceptualize reservoir characterization in early development phases; coupled with statistical experimental design, montecarlo simulation and scenario analysis, numerical simulation become the most powerful tool to fulfill a complete sensitivity analysis with significantly fewer simulation runs towards sizing downhole and surface facilities, as well as, optimizing field development.
The proposed holistic approach was applied to a new lean gas condensate field in the Peruvian rainforest so as to sensitize production plateau, evaluate rock & fluid properties, field size and recovery factors, predict liquid yield performance, analyze water influx and optimize field development. Pareto plots and response model surfaces showed that porosity, permeability, position of gas water contacts and faults transmissibility are the main factors affecting field size, as well as, gas and liquid recovery. In addition, cumulative plots showed distribution of gas & condensate recoverable resources. Finally, a matrix of scenarios showed that blowdown strategy is the best development alternative for this lean gas condensate field.
The process of evaluation and planning the development of a new field is plagued by many uncertainties. The complexity of physics in conforming geology and predicting fluid flow throughout the reservoir makes difficult the task of reservoir modeling.
Four major sources of uncertainties have been indentified during reservoir modeling process1:
1. Geophysical uncertainties referred to time-to-depth conversion in seismic processing, fault positioning and time migration.
2. Geologic uncertainties about rock types and their heterogeneities, depositional environments and in place hydrocarbon volumes.
3. Petrophysical uncertainties related to net pay and Vclay calculations, rock properties spatial distributions and fluid contacts placing.
4. Dynamic uncertainties referred to relative permeability curves behavior, changes in hydrocarbon composition, fault transmissibilities, productivity and injectivity indexes, well skin, as well as, facilities and operational settings.
Gas condensate reservoirs show a complex behavior when they are produced below dew point pressure under isothermal conditions, due to the presence of a two-phase system, and the appearance of a condensate banking phenomena. Recent gas condensate field discoveries in Peru exhibited initial reservoir pressures slightly higher than dew point; as PVT reports indicated that retrograde liquid saturation would not exceed 4%, condensate drop-out was not presumed to be a significant problem affecting well productivity and production performance, and indeed, strategies to face this problem have been
Initial multirate tests run in the Peruvian gas condensate fields did show only a slightly indication of liquid drop-out in NIA formation (less than 5%), but some features of the existence of condensate banking were noticed in NOI and ENE reservoirs. As a consequence, it is worth to study the condensate drop-out phenomena as in many cases, it causes a permanent reduction in well productivity, and eventually, in recovery factor, even though is partially compensated by capillary number effects.
An integrated approach to model the condensate banking phenomena at well and fullfield scales, over the time, in Peruvian gas condensate fields is proposed by the combination of two powerful tools: well testing analysis and numerical compositional simulation; while the transient testing analysis, supported by a deconvolution algorithm, is used to evaluate "snapshots?? of the three or four regions representing the various mobility zones around the wellbore, the compositional simulation allows predicting how the condensate banking will evolve in the future, and how this phenomena will affect production performance. Preliminary results predict a reduction of gas and oil production and recovery between 3% and 5%.
A 3D integrated saturation model was built for the Sierras Blancas Formation of the Neuquén Basin, Argentina. The saturation model was based on core, logs and seismic data. History match of reservoir pressure and well productivities were taken into account to accurately determine the gas in place and productive reservoir boundaries, specifically using 3D seismic water saturation in the gas condensate formation. The Sierras Blancas Formation is an eolian deposit. In tight, wet and diagenetically altered regions, the seismic inversion porosity and acoustic impedance based models were not adequate to describe the gas in place distribution. Further, the effective gas permeabilities in the tighter part of the reservoir are a strong function of the initial water saturation as evidenced by fewer condensate and water blocking problems of horizontal wells that navigated through low water saturation, high permeability regions. Any relationship between seismic impedance and porosity correlation degraded in areas affected by secondary diagenetic processes therefore necessitating the use of a saturation parameter. 30 vertical wells that had DT curves were selected based on their production and spatial location in order to establish a correlation between log saturation and seismic attributes. Seismic saturation cubes were generated by multi-attribute seismic analysis and resampled into the simulation scale model. Log saturations were then co-kriged with the 3D seismic saturation. Water saturations obtained from the initialized simulation scale model were compared with the 2D saturation logs, the 3D seismic and the geological model scales. An objective function was defined to match the 3D seismic water saturation with the initialized simulation model water saturation. Model parameters were iterated until a satisfactory match with the initialized simulation model was obtained.
By focusing the saturation match at the initialization stage, seismic, geological, petrophysical and SCAL models were ensured to be consistent prior to the full history match. Well history matching was consequently achieved much more simply and quickly. This paper presents a new detailed methodology of 3D pseudo-seismic water saturation generation, modeling and simulation used to accurately define OGIP, the productive boundaries of the reservoir, and to design trajectories for new horizontal wells.
Unconventional reservoirs have burst with considerable force in oil and gas production worldwide. Shale Gas is one of them, with intense activity taking place in regions like North America. To achieve commercial production, these reservoirs should be stimulated through massive hydraulic fracturing and, frequently, through horizontal wells as a mean to enhance productivity.
In sedimentary terms, shales are fine-grained clastics rocks formed by consolidation of silts and clays. In log interpretation of conventional reservoirs, it is very common to observe that the clay parameters used to correct porosity and resistivity logs for clay effects are in fact read in shaly intervals rather than in pure clay. Although no considerable deviation have been observed in shaly sandstones, anyway these concepts and procedures must be reviewed to run log analysis in shale gas. Organic matter deposited with shales containing kerogen that matured as a result of overburden pressure and temperature, giving rise to source rocks that have yielded and expulsed hydrocarbons. Shale gas reservoir type is a source rock that has retained a portion of the hydrocarbon yielded during its geological history so that to evaluate the current hydrocarbon storage and production potential it is necessary to know the kerogen type and the level of TOC - total organic carbon - in the rock. Produced gas comes from both adsorbed gas in the organic matter and "free" gas trapped in the pores of the organic matter and in the inorganic portions of the matrix, i.e. quartz, calcite, dolomite.
In these unconventional reservoirs, gas volumes are estimated through a combination of geochemical analysis and log interpretation techniques. TOC, desorbed total gas content, adsorption isotherms, and kerogen maturity among other things can be measured in cores, sidewall samples and cuttings, in the laboratory. These data are used to estimate total desorbed gas content and adsorbed gas content which is part of the total gas. Also in laboratory, porosity, grain density, water saturation, permeability, mineral composition and elastic modules of the rock are measured. Laboratory measurement uncertainty is high and consistency between different providers appears to be low, with serious suspicions that procedures followed by different laboratories are the source of such differences. The permeability is one of the most important parameters, but at the same time, one of the most difficult to measure reliably in a shale gas. Core calibrated porosity, mineral composition, water saturation and elastic modules can be obtained through electric and radioactive logs. All these information is used to estimate log derived total gas volume which results are also subject to a high degree of uncertainty that must be overcome.
Once this key information is obtained, it is possible to estimate different gas in-situ volumes. Indeed, an estimate of porosity-resistivity based total gas in-situ and, on the other hand, geochemical based adsorbed gas in-situ can be performed. Log total gas in-situ can be, and it is advisable to do, compared with adsorbed gas estimations and also with another gas measurement called direct method - total gas desorption performed on formation samples. The difference between log total gas in-situ and adsorbed gas in situ should be the "free" gas in situ. Free gas occupies the pores of kerogen and matrix; also it can be stored in open natural fractures if such fractures are present.