Cop~ht 1995, Sodefy of Petroleum Engineers, Inc.This paper wee prepared for presentation at the Western Regionei Meeting held in Bakersfield, CA, U.S.A., 8-10 March 1~5, This paper wee eafacfed for preaentatlon by an SPE Progrem timmiffee following review of information confeined in an absfraot submnted by the autfwr(e). Contenfe of the paper, se Waaanted, have not bean retiewed by the Sooiefy of Petroleum Engineers and are eubjact to correction by the aufhqs).The material, as presented, does not naceeeerlly reflect any position of the Sooikfy of Petroleum Engineere, ite officers, or members. Papera presented at SPE meetings era subject to pubikation review by Editorial Commhtees of the society of Pefrofaum Engineers. Parmkeebn to copy is rearrkfed to an ebatracf of nof rnc+e than S00 words, Illuetratbrra may not be oopiad. The abstract ahoufd oontain mrtepkuous eckn-gnwnt of where and by Wrom the peper is preeenterl Write Librerian, SPE,
TX 75083-3836, U.S.A., fax 01-972-952-9435. AbstractDuring a hydraulic fracturing treatment, it is important to ascertain the bottom hole pressure (BHP) in order to calculate the net pressure generated in the fracture. Net pressure trends are critical in the proppant stages because any incorrect interpretation may lead to an early termination of the treatment and hence the designed objectives may not be achieved. On other hand, continuing to pump the job even when a screen out is imminent may lead to a proppant pack in the tubular and may incur additional expenditure to clean up the well. In some treatments, BHP gauges, live annulus or dead strings may be used to monitor the net pressure. However, in most treatments such devices or methods may not be available. A majority of the hydraulic fracturing jobs, thus, rely on the pressures recorded at the surface to compute the net pressure.This study utilizes the surface pressure recorded during the treatment to compute the friction pressure drops during the proppant stages. Over 150 hydraulic fracturing jobs were used for the study. Friction pressure multipliers were generated for several proppant concentrations using the friction pressure data obtained from these treatments. These multipliers were analyzed in the light of key parameters that could affect the proppant friction, namely, gel concentration, proppant density, tubular internal diameter, and average flow velocity.A correlation, capable of predicting proppant friction pressure exponent was generated using the above-mentioned variables. An average deviation of around 0.23% was observed when the results obtained from the correlation were compared with friction pressures calculated in cases where bottom hole pressures were measured.Further, proppant friction exponents obtained from the correlation were used in several other jobs that were not part of the initial study and reasonably good pressure history matches were obtained. The simple form of the correlation can be easily programmed in a spreadsheet and has proved to be an efficient tool in computing net pressures while monitoring the jobs where the bottom hole pressures are not measured.
Summary This paper presents a model of foam rheology in porous media, based on a set of experimental data gathered in linear cores at rates relevant to matrix-acidizing conditions. Foam was found to behave as two-phase flow, with a minimum yield stress required to displace the gas phase. At high foam rates, foam was highly shear-thinning, and the pressure gradient within the foam bank was observed to be independent of the foam rate. It was also found that nitrogen solubility in the aqueous phase can explain the long-term behavior of foam banks under brine flow. The modeling is applied to foam-flow simulation. In a two-phase finite-difference simulator, foam flow is represented by modifying the relative permeability to gas at each timestep, as a function of the injection conditions. Surfactant transport and adsorption and gas solubility have also been integrated into the simulator. Comparisons between simulation results and diversion experiments are presented, and the possibility of extension to field conditions is demonstrated by simulation of a hypothetical field case. Finally, the effects of surfactant adsorption and foam-injection conditions on diversion efficiency are briefly discussed. Introduction Foam has been used increasingly for fluid-placement control during matrix acidizing over the past few years. While foam behavior under enhanced oil recovery conditions has been studied extensively, the mechanisms of foam diversion are not as well understood. The first studies of foam rheology in porous media showed that foam must be treated as a two-phase flow and that the liquid relative permeability curve is the same as it would be in the presence of a continuous gas phase. This assumption was used in the work presented here, although it was not checked experimentally.
Although numerous sandstone and carbonate simulators have been developed during the past decade, few have been field validated. This paper addresses the field validation of a numerical simulator used for treatment design. Five matrix acidized wells were used for validation of the simulator. In most cases the simulator was within +10% of the actual skin reduction observed in the well. The simulator calculates the pressure at the formation face and within the multiple layers along the corresponding flow rates. Diversion and mineral dissolution with the corresponding permeability changes are also calculated for sandstone and carbonates. The key to simulator validation is good well data including pre and post-treatment pressure buildup analysis, PLT data, log and/or core data, formation mineralogy and the knowledge of the damage mechanism. Simulations indicate previously developed "rule of thumb" guidelines for mud acid volume may not yield the best results. When formation damage is shallow, as in some of the case histories the "rule of thumb" may results in the use of excessive acid, whereas, when damage is 2 to 3 feet from the wellbore higher volumes of acid are normally required. Simulations support the concept that diversion is essential and can easily be observed via the flow per layer output. This study indicates matrix treatment design is not engineered until it is simulated using valid models. Application of the validated simulator results in increased production and improved economics for the operator. A detailed description of the validation process and the supporting well data are presented. Introduction Sandstone matrix acidizing using mud acid formulations has been used for decades to remove siliceous formation damage. The damage can be formed during drilling, completion and/or production phases of a well, which can cause severe production decreases. Numerous papers have been written on laboratory and field studies directed at clay damage removal. These laboratory studies were conducted in support of development of acidizing simulators. However, none of the simulators were field validated. This paper will address this issue by using well documented case histories. The numerical simulator used in this study was previously described in the literature. The simulator is 2d and is capable of acidizing and diverting fluids. Fluid fingering, acid concentrations and fluid saturation at each point radially in the formation are calculated at each time step. The model considers diversion by using cake resistance or a pseudoskin correlation. Dissolution of the mineral species is based on a change in porosity. The porosity is converted to permeability based on a modified Labrid's formula. The three sandstone cases presented are graveled pack wells from the Gulf of Mexico. Two wells were suspected to have HEC polymer damage and the third well was suspected to have silt and clay damage. Information for each of the wells varied from detailed laboratory flow studies to porosity logs. The later is probably what most operators have for their well description. In all three cases we were able to model the pre and post skin results. The two carbonate cases are wells from the Middle East. They represent the acids used routinely in carbonate reservoirs (HCl and emulsified HCl). Two distinct models are used in the simulator process. The first model is cable of modeling wormhole growth used for non-retarded HCl whereas the second model assumes uniform dissolution by a emulsified (retarded) acid i.e. radial flow through all pore throats. Sandstone Acidizing Validation Case Histories Modeling. During sandstone acidizing the numerical simulator models the dissolution of formation damage and native minerals. P. 283^
fax 01-972-952-9435. AbstractAcidizing is a common method of stimulating horizonkd wells. The acidizing process is fimdamentally different when applied in a horizontal well compared with application in a vertical well. The fluid distribution in a horizontal well is tiected by a longer wellbore length a broader variation in the reservoir properties along the wellbore, and possibly diiTerent mechanical means to place the fluids in the wellbore. A comprehensive fluid placement model linked with a reservoir acidizing simulator is essential to precisely design acidizing treatments for horizontal wells.This paper presents a model of fluid placement in a horizontal well. The model predicts the placement of injected fluids by tracking the interfaces lxtween ditlerent fluids in the wellbore. It is capable of tracking muItipIe intetiaces for multiple injection stages in horizontal wells. For injection with coiled tubing, the model allows tubing tail movement during injeetion. It also handles simultaneous injection from the annnlus and from a tubing string. The fluid distribution generated from the model can be used as input information in a reservoir acidizing model for sandstone acidizing design. Both analytical and discretized solutions of the model are presented in the paper. Examples in the paper illustrate the effects of such factors as velocity of tubing movement, annular injection, and a non-uniform distribution of flow into the reservoir on fluid placement in an acidizing treatment.The fluid placement model can help to determine optimum tubing tail locations and optimal injection volumes of acids, to select the most appropriate diverting methods, OUCL hence, to maximize the benefits of an acidizing treatment.
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